content
stringlengths 1
1.05M
| input_ids
sequencelengths 1
883k
| ratio_char_token
float64 1
22.9
| token_count
int64 1
883k
|
|---|---|---|---|
# Copyright (C) 2014-2015 LiuLang <gsushzhsosgsu@gmail.com>
# Use of this source code is governed by GPLv3 license that can be found
# in http://www.gnu.org/licenses/gpl-3.0.html
import hashlib
import os
import zlib
CHUNK = 2 ** 20
| [
198,
2,
15069,
357,
34,
8,
1946,
12,
4626,
18258,
43,
648,
1279,
14542,
1530,
89,
11994,
418,
70,
2385,
31,
14816,
13,
785,
29,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
38644,
85,
18,
5964,
326,
460,
307,
1043,
198,
2,
287,
2638,
1378,
2503,
13,
41791,
13,
2398,
14,
677,
4541,
14,
70,
489,
12,
18,
13,
15,
13,
6494,
198,
198,
11748,
12234,
8019,
198,
11748,
28686,
198,
11748,
1976,
8019,
198,
198,
3398,
4944,
42,
796,
362,
12429,
1160,
628
] | 2.712644 | 87 |
#!/usr/bin/python
# encoding: utf-8
'''a rich client
1. for one server (instead of multi like in libmc.Client)
2. encapsulate @, ?, gc ...
use is instead of libmc.Client
'''
import telnetlib
import logging
import libmc
import string
import urllib
import itertools
import warnings
from collections import defaultdict
from beansdbadmin.core.hint import parse_new_hint_body
from beansdbadmin.core.data import parse_records
from beansdbadmin.core.hash import get_khash64
def get_buckets_keys_count(store):
""" return dict: buckets -> count """
st = {}
try:
for line in (store.get('@') or '').split('\n'):
if line:
d, _, c = line.split(' ')
if not d.endswith('/'):
continue
st[int(d[0], 16)] = int(c)
return st
except IOError:
raise Exception("cannot get @ from %s" % (store))
def get_primary_buckets(store):
""" return possible primary buckets, might be wrong on temporary nodes,
result is list of buckets in integer
"""
ss = get_buckets_keys_count(store)
bucket_list = ss.items()
bucket_list = [x for x in bucket_list if x[1] > 0]
if not bucket_list:
return None
bucket_list.sort(lambda a, b: cmp(a[1], b[1]), reverse=True)
result = [bucket_list[0]]
for i in bucket_list[1:]:
if result[-1][1] / i[1] >= 2:
break
result.append(i)
return [x[0] for x in result]
def get_key_info_disk(store, key):
'''return ver, vhash, flag, vsz, ts, fid, pos'''
info = store.get('??' + key)
if info:
return [int(x) for x in info.split()]
def test_new(addr, bucket):
b = bucket
c = DBClient(addr)
print "stats:", c.stats()
print 'version:', c.get_server_version()
print "isold:", c.is_old()
print "dir root:", c.get_dir("@")
print "bucket key count:", c.get_bucket_keys_count(int(b))
print "item_count:", c.item_count()
print "primary_buckets", get_primary_buckets(c)
leaf = c.get_dir("@" + b + "000000")
print "a dir leaf:", leaf
khash_str = list(leaf)[0]
print "a khash_str", khash_str
r = c.get_records_by_khash(khash_str)[0]
k = r[0]
print "key, len(value), (flag, tstamp, ver):", k, r[1], r[3:]
print "key info mem:", c.get_key_info_mem(k)
print "key info disk(ver, vhash, flag, vsz, ts, fid, pos):", \
c.get_key_info_disk(k)
print "key version:", c.get_version(k)
print "collision_summary", c.get_collision_summary(int(b))
print "gc status:", c.get_gc_status()
if __name__ == '__main__':
test_new("rosa3a:7900", '3')
| [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
2,
21004,
25,
3384,
69,
12,
23,
198,
7061,
6,
64,
5527,
5456,
198,
220,
220,
220,
352,
13,
329,
530,
4382,
357,
38070,
286,
5021,
588,
287,
9195,
23209,
13,
11792,
8,
198,
220,
220,
220,
362,
13,
32652,
5039,
2488,
11,
5633,
11,
308,
66,
2644,
198,
198,
1904,
318,
2427,
286,
9195,
23209,
13,
11792,
198,
7061,
6,
198,
198,
11748,
13632,
3262,
8019,
198,
11748,
18931,
198,
11748,
9195,
23209,
198,
11748,
4731,
198,
11748,
2956,
297,
571,
198,
11748,
340,
861,
10141,
198,
11748,
14601,
198,
6738,
17268,
1330,
4277,
11600,
198,
6738,
16567,
9945,
28482,
13,
7295,
13,
71,
600,
1330,
21136,
62,
3605,
62,
71,
600,
62,
2618,
198,
6738,
16567,
9945,
28482,
13,
7295,
13,
7890,
1330,
21136,
62,
8344,
3669,
198,
6738,
16567,
9945,
28482,
13,
7295,
13,
17831,
1330,
651,
62,
14636,
1077,
2414,
628,
628,
628,
198,
4299,
651,
62,
27041,
1039,
62,
13083,
62,
9127,
7,
8095,
2599,
198,
220,
220,
220,
37227,
1441,
8633,
25,
38674,
4613,
954,
37227,
198,
220,
220,
220,
336,
796,
23884,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1627,
287,
357,
8095,
13,
1136,
10786,
31,
11537,
393,
10148,
737,
35312,
10786,
59,
77,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1627,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
11,
4808,
11,
269,
796,
1627,
13,
35312,
10786,
705,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
288,
13,
437,
2032,
342,
10786,
14,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
336,
58,
600,
7,
67,
58,
15,
4357,
1467,
15437,
796,
493,
7,
66,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
336,
198,
220,
220,
220,
2845,
24418,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
66,
34574,
651,
2488,
422,
4064,
82,
1,
4064,
357,
8095,
4008,
628,
198,
4299,
651,
62,
39754,
62,
27041,
1039,
7,
8095,
2599,
198,
220,
220,
220,
37227,
1441,
1744,
4165,
38674,
11,
1244,
307,
2642,
319,
8584,
13760,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
318,
1351,
286,
38674,
287,
18253,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
37786,
796,
651,
62,
27041,
1039,
62,
13083,
62,
9127,
7,
8095,
8,
198,
220,
220,
220,
19236,
62,
4868,
796,
37786,
13,
23814,
3419,
198,
220,
220,
220,
19236,
62,
4868,
796,
685,
87,
329,
2124,
287,
19236,
62,
4868,
611,
2124,
58,
16,
60,
1875,
657,
60,
198,
220,
220,
220,
611,
407,
19236,
62,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198,
220,
220,
220,
19236,
62,
4868,
13,
30619,
7,
50033,
257,
11,
275,
25,
269,
3149,
7,
64,
58,
16,
4357,
275,
58,
16,
46570,
9575,
28,
17821,
8,
198,
220,
220,
220,
1255,
796,
685,
27041,
316,
62,
4868,
58,
15,
11907,
198,
220,
220,
220,
329,
1312,
287,
19236,
62,
4868,
58,
16,
25,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1255,
58,
12,
16,
7131,
16,
60,
1220,
1312,
58,
16,
60,
18189,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
13,
33295,
7,
72,
8,
198,
220,
220,
220,
1441,
685,
87,
58,
15,
60,
329,
2124,
287,
1255,
60,
628,
198,
4299,
651,
62,
2539,
62,
10951,
62,
39531,
7,
8095,
11,
1994,
2599,
198,
220,
220,
220,
705,
7061,
7783,
3326,
11,
410,
17831,
11,
6056,
11,
3691,
89,
11,
40379,
11,
49909,
11,
1426,
7061,
6,
198,
220,
220,
220,
7508,
796,
3650,
13,
1136,
10786,
3548,
6,
1343,
1994,
8,
198,
220,
220,
220,
611,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
600,
7,
87,
8,
329,
2124,
287,
7508,
13,
35312,
3419,
60,
628,
628,
628,
198,
198,
4299,
1332,
62,
3605,
7,
29851,
11,
19236,
2599,
198,
220,
220,
220,
275,
796,
19236,
198,
220,
220,
220,
269,
796,
20137,
11792,
7,
29851,
8,
198,
220,
220,
220,
3601,
366,
34242,
25,
1600,
269,
13,
34242,
3419,
198,
220,
220,
220,
3601,
705,
9641,
25,
3256,
269,
13,
1136,
62,
15388,
62,
9641,
3419,
198,
220,
220,
220,
3601,
366,
271,
727,
25,
1600,
269,
13,
271,
62,
727,
3419,
198,
220,
220,
220,
3601,
366,
15908,
6808,
25,
1600,
269,
13,
1136,
62,
15908,
7203,
31,
4943,
198,
220,
220,
220,
3601,
366,
27041,
316,
1994,
954,
25,
1600,
269,
13,
1136,
62,
27041,
316,
62,
13083,
62,
9127,
7,
600,
7,
65,
4008,
198,
220,
220,
220,
3601,
366,
9186,
62,
9127,
25,
1600,
269,
13,
9186,
62,
9127,
3419,
198,
220,
220,
220,
3601,
366,
39754,
62,
27041,
1039,
1600,
651,
62,
39754,
62,
27041,
1039,
7,
66,
8,
628,
220,
220,
220,
12835,
796,
269,
13,
1136,
62,
15908,
7203,
31,
1,
1343,
275,
1343,
366,
10535,
4943,
198,
220,
220,
220,
3601,
366,
64,
26672,
12835,
25,
1600,
12835,
198,
220,
220,
220,
479,
17831,
62,
2536,
796,
1351,
7,
33201,
38381,
15,
60,
198,
220,
220,
220,
3601,
366,
64,
479,
17831,
62,
2536,
1600,
479,
17831,
62,
2536,
198,
220,
220,
220,
374,
796,
269,
13,
1136,
62,
8344,
3669,
62,
1525,
62,
14636,
1077,
7,
14636,
1077,
62,
2536,
38381,
15,
60,
198,
220,
220,
220,
479,
796,
374,
58,
15,
60,
198,
220,
220,
220,
3601,
366,
2539,
11,
18896,
7,
8367,
828,
357,
32109,
11,
256,
301,
696,
11,
3326,
2599,
1600,
479,
11,
374,
58,
16,
4357,
374,
58,
18,
47715,
198,
220,
220,
220,
3601,
366,
2539,
7508,
1066,
25,
1600,
269,
13,
1136,
62,
2539,
62,
10951,
62,
11883,
7,
74,
8,
198,
220,
220,
220,
3601,
366,
2539,
7508,
11898,
7,
332,
11,
410,
17831,
11,
6056,
11,
3691,
89,
11,
40379,
11,
49909,
11,
1426,
2599,
1600,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
13,
1136,
62,
2539,
62,
10951,
62,
39531,
7,
74,
8,
198,
220,
220,
220,
3601,
366,
2539,
2196,
25,
1600,
269,
13,
1136,
62,
9641,
7,
74,
8,
198,
220,
220,
220,
3601,
366,
26000,
1166,
62,
49736,
1600,
269,
13,
1136,
62,
26000,
1166,
62,
49736,
7,
600,
7,
65,
4008,
198,
220,
220,
220,
3601,
366,
36484,
3722,
25,
1600,
269,
13,
1136,
62,
36484,
62,
13376,
3419,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1332,
62,
3605,
7203,
4951,
64,
18,
64,
25,
3720,
405,
1600,
705,
18,
11537,
198
] | 2.271637 | 1,167 |
import matplotlib.pyplot
__author__ = 'xiongyi'
line1 = [(200, 100), (200, 400)]
line2 = [(190, 190), (210, 210)]
if __name__ == '__main__':
matplotlib.pyplot.plot((line1[0][0],line1[1][0]),(line1[0][1],line1[1][1]))
matplotlib.pyplot.hold(True)
matplotlib.pyplot.plot((line2[0][0],line2[1][0]),(line2[0][1],line2[1][1]))
print(overlap())
matplotlib.pyplot.show()
| [
11748,
2603,
29487,
8019,
13,
9078,
29487,
198,
834,
9800,
834,
796,
705,
87,
295,
1360,
72,
6,
198,
1370,
16,
796,
47527,
2167,
11,
1802,
828,
357,
2167,
11,
7337,
15437,
198,
1370,
17,
796,
47527,
19782,
11,
19884,
828,
357,
21536,
11,
20064,
15437,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
2603,
29487,
8019,
13,
9078,
29487,
13,
29487,
19510,
1370,
16,
58,
15,
7131,
15,
4357,
1370,
16,
58,
16,
7131,
15,
46570,
7,
1370,
16,
58,
15,
7131,
16,
4357,
1370,
16,
58,
16,
7131,
16,
60,
4008,
198,
220,
220,
220,
2603,
29487,
8019,
13,
9078,
29487,
13,
2946,
7,
17821,
8,
628,
220,
220,
220,
2603,
29487,
8019,
13,
9078,
29487,
13,
29487,
19510,
1370,
17,
58,
15,
7131,
15,
4357,
1370,
17,
58,
16,
7131,
15,
46570,
7,
1370,
17,
58,
15,
7131,
16,
4357,
1370,
17,
58,
16,
7131,
16,
60,
4008,
198,
220,
220,
220,
3601,
7,
2502,
37796,
28955,
198,
220,
220,
220,
2603,
29487,
8019,
13,
9078,
29487,
13,
12860,
3419,
198
] | 2.120879 | 182 |
from sqlalchemy import select
from sqlalchemy.schema import Column
from .declarative import Model
class ModelLoader(Loader):
class AliasLoader(ModelLoader):
class ColumnLoader(Loader):
class TupleLoader(Loader):
class CallableLoader(Loader):
class ValueLoader(Loader):
| [
6738,
44161,
282,
26599,
1330,
2922,
198,
6738,
44161,
282,
26599,
13,
15952,
2611,
1330,
29201,
198,
198,
6738,
764,
32446,
283,
876,
1330,
9104,
628,
198,
198,
4871,
9104,
17401,
7,
17401,
2599,
628,
198,
4871,
978,
4448,
17401,
7,
17633,
17401,
2599,
628,
198,
4871,
29201,
17401,
7,
17401,
2599,
628,
198,
4871,
309,
29291,
17401,
7,
17401,
2599,
628,
198,
4871,
4889,
540,
17401,
7,
17401,
2599,
628,
198,
4871,
11052,
17401,
7,
17401,
2599,
198
] | 3.582278 | 79 |
# Standard imports
import logging
import math
import json
from uuid import UUID
from datetime import datetime, timedelta
import time
# Our imports
from emission.core.get_database import get_trip_db, get_section_db
import emission.analysis.result.carbon as carbon
import emission.core.common as common
import emission.net.api.stats as stats
from emission.core.wrapper.user import User
from emission.clients.leaderboard import leaderboard
from emission.clients.gamified import gamified
from emission.clients.recommendation import recommendation
from emission.clients.commontrips import commontrips
from emission.clients.data import data
# TODO: Consider subclassing to provide client specific user functions
# These are copy/pasted from our first client, the carshare study
# TODO: Simplify this. runBackgroundTasks are currently only invoked from the
# result precomputation code. We could change that code to pass in the day, and
# remove this interface. Extra credit: should we pass in the day, or a date
# range? Passing in the date range could make it possible for us to run the
# scripts more than once a day...
| [
2,
8997,
17944,
198,
11748,
18931,
198,
11748,
10688,
198,
11748,
33918,
198,
6738,
334,
27112,
1330,
471,
27586,
198,
6738,
4818,
8079,
1330,
4818,
8079,
11,
28805,
12514,
198,
11748,
640,
198,
198,
2,
3954,
17944,
198,
6738,
25592,
13,
7295,
13,
1136,
62,
48806,
1330,
651,
62,
39813,
62,
9945,
11,
651,
62,
5458,
62,
9945,
198,
11748,
25592,
13,
20930,
13,
20274,
13,
29255,
355,
6588,
198,
11748,
25592,
13,
7295,
13,
11321,
355,
2219,
198,
11748,
25592,
13,
3262,
13,
15042,
13,
34242,
355,
9756,
198,
6738,
25592,
13,
7295,
13,
48553,
13,
7220,
1330,
11787,
198,
6738,
25592,
13,
565,
2334,
13,
27940,
3526,
1330,
3554,
3526,
198,
6738,
25592,
13,
565,
2334,
13,
28483,
1431,
1330,
9106,
1431,
198,
6738,
25592,
13,
565,
2334,
13,
47335,
437,
341,
1330,
15602,
198,
6738,
25592,
13,
565,
2334,
13,
785,
8691,
380,
862,
1330,
725,
756,
380,
862,
198,
6738,
25592,
13,
565,
2334,
13,
7890,
1330,
1366,
198,
198,
2,
16926,
46,
25,
12642,
47611,
278,
284,
2148,
5456,
2176,
2836,
5499,
198,
198,
2,
2312,
389,
4866,
14,
79,
8992,
422,
674,
717,
5456,
11,
262,
5006,
43466,
2050,
198,
198,
2,
16926,
46,
25,
45157,
1958,
428,
13,
1057,
21756,
51,
6791,
389,
3058,
691,
24399,
422,
262,
198,
2,
1255,
662,
785,
1996,
341,
2438,
13,
775,
714,
1487,
326,
2438,
284,
1208,
287,
262,
1110,
11,
290,
198,
2,
4781,
428,
7071,
13,
17221,
3884,
25,
815,
356,
1208,
287,
262,
1110,
11,
393,
257,
3128,
198,
2,
2837,
30,
220,
46389,
287,
262,
3128,
2837,
714,
787,
340,
1744,
329,
514,
284,
1057,
262,
198,
2,
14750,
517,
621,
1752,
257,
1110,
986,
198
] | 3.947183 | 284 |
#!/usr/bin/env python
"""
HAR Formatter for REDbot.
"""
__author__ = "Jerome Renard <jerome.renard@gmail.com>"
__copyright__ = """\
Copyright (c) 2008-2010 Mark Nottingham
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
import operator
import nbhttp.error as nberr
import redbot.speak as rs
from redbot.formatter import Formatter
nl = u"\n"
# TODO: errors and status on stderr with CLI?
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
37811,
198,
39,
1503,
5178,
1436,
329,
23848,
13645,
13,
198,
37811,
198,
198,
834,
9800,
834,
796,
366,
36134,
462,
7152,
446,
1279,
44009,
462,
13,
918,
446,
31,
14816,
13,
785,
24618,
198,
834,
22163,
4766,
834,
796,
37227,
59,
198,
15269,
357,
66,
8,
3648,
12,
10333,
2940,
39802,
198,
198,
5990,
3411,
318,
29376,
7520,
11,
1479,
286,
3877,
11,
284,
597,
1048,
16727,
257,
4866,
198,
1659,
428,
3788,
290,
3917,
10314,
3696,
357,
1169,
366,
25423,
12340,
284,
1730,
198,
259,
262,
10442,
1231,
17504,
11,
1390,
1231,
17385,
262,
2489,
198,
1462,
779,
11,
4866,
11,
13096,
11,
20121,
11,
7715,
11,
14983,
11,
850,
43085,
11,
290,
14,
273,
3677,
198,
22163,
444,
286,
262,
10442,
11,
290,
284,
8749,
6506,
284,
4150,
262,
10442,
318,
198,
69,
700,
1348,
284,
466,
523,
11,
2426,
284,
262,
1708,
3403,
25,
198,
198,
464,
2029,
6634,
4003,
290,
428,
7170,
4003,
2236,
307,
3017,
287,
198,
439,
9088,
393,
8904,
16690,
286,
262,
10442,
13,
198,
198,
10970,
47466,
3180,
36592,
2389,
1961,
366,
1921,
3180,
1600,
42881,
34764,
56,
3963,
15529,
509,
12115,
11,
7788,
32761,
6375,
198,
3955,
49094,
11,
47783,
2751,
21728,
5626,
40880,
5390,
3336,
34764,
11015,
3963,
34482,
3398,
1565,
5603,
25382,
11,
198,
37,
46144,
7473,
317,
16652,
2149,
37232,
33079,
48933,
5357,
44521,
1268,
10913,
2751,
12529,
13,
3268,
8005,
49261,
50163,
3336,
198,
32,
24318,
20673,
6375,
27975,
38162,
9947,
367,
15173,
4877,
9348,
43031,
19146,
7473,
15529,
47666,
3955,
11,
29506,
25552,
6375,
25401,
198,
43,
3539,
25382,
11,
7655,
2767,
16879,
3268,
3537,
40282,
3963,
27342,
10659,
11,
309,
9863,
6375,
25401,
54,
24352,
11,
5923,
1797,
2751,
16034,
11,
198,
12425,
3963,
6375,
3268,
7102,
45,
24565,
13315,
3336,
47466,
6375,
3336,
23210,
6375,
25401,
5550,
1847,
20754,
3268,
198,
10970,
47466,
13,
198,
37811,
198,
198,
11748,
10088,
198,
198,
11748,
299,
65,
4023,
13,
18224,
355,
299,
527,
81,
198,
11748,
2266,
13645,
13,
47350,
355,
44608,
198,
198,
6738,
2266,
13645,
13,
687,
1436,
1330,
5178,
1436,
198,
198,
21283,
796,
334,
1,
59,
77,
1,
198,
198,
2,
16926,
46,
25,
8563,
290,
3722,
319,
336,
1082,
81,
351,
43749,
30,
628,
628
] | 3.576623 | 385 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020-2021 by Murray Altheim. All rights reserved. This file is part
# of the Robot Operating System project, released under the MIT License. Please
# see the LICENSE file included as part of this package.
#
# author: Murray Altheim
# created: 2020-09-19
# modified: 2020-09-19
#
import sys, colorsys
import ioexpander as io
from colorama import init, Fore, Style
init()
from lib.logger import Logger
# ..............................................................................
# return (( self._out_max - self._out_min ) * ( self.get_value() - self._in_min ) / ( self._in_max - self._in_min )) + self._out_min
#EOF
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
198,
2,
15069,
12131,
12,
1238,
2481,
416,
12164,
978,
1169,
320,
13,
1439,
2489,
10395,
13,
770,
2393,
318,
636,
198,
2,
286,
262,
16071,
24850,
4482,
1628,
11,
2716,
739,
262,
17168,
13789,
13,
4222,
198,
2,
766,
262,
38559,
24290,
2393,
3017,
355,
636,
286,
428,
5301,
13,
198,
2,
198,
2,
1772,
25,
220,
220,
12164,
978,
1169,
320,
198,
2,
2727,
25,
220,
12131,
12,
2931,
12,
1129,
198,
2,
9518,
25,
12131,
12,
2931,
12,
1129,
198,
2,
198,
198,
11748,
25064,
11,
7577,
893,
198,
11748,
33245,
11201,
4066,
355,
33245,
198,
6738,
3124,
1689,
1330,
2315,
11,
4558,
11,
17738,
198,
15003,
3419,
198,
198,
6738,
9195,
13,
6404,
1362,
1330,
5972,
1362,
198,
198,
2,
220,
23193,
2109,
16317,
198,
2,
220,
220,
220,
220,
220,
220,
1441,
14808,
2116,
13557,
448,
62,
9806,
532,
2116,
13557,
448,
62,
1084,
1267,
1635,
357,
2116,
13,
1136,
62,
8367,
3419,
532,
2116,
13557,
259,
62,
1084,
1267,
1220,
357,
2116,
13557,
259,
62,
9806,
532,
2116,
13557,
259,
62,
1084,
15306,
1343,
2116,
13557,
448,
62,
1084,
198,
198,
2,
4720,
37,
628
] | 3.212963 | 216 |
"""
Module: 'urequests' on esp32 1.12.0
"""
# MCU: (sysname='esp32', nodename='esp32', release='1.12.0', version='v1.12 on 2019-12-20', machine='ESP32 module (spiram) with ESP32')
# Stubber: 1.3.2
usocket = None
| [
37811,
198,
26796,
25,
705,
495,
421,
3558,
6,
319,
15024,
2624,
352,
13,
1065,
13,
15,
198,
37811,
198,
2,
13122,
52,
25,
357,
17597,
3672,
11639,
9774,
2624,
3256,
18666,
12453,
11639,
9774,
2624,
3256,
2650,
11639,
16,
13,
1065,
13,
15,
3256,
2196,
11639,
85,
16,
13,
1065,
319,
13130,
12,
1065,
12,
1238,
3256,
4572,
11639,
1546,
47,
2624,
8265,
357,
45564,
321,
8,
351,
9428,
2624,
11537,
198,
2,
41135,
527,
25,
352,
13,
18,
13,
17,
198,
198,
385,
5459,
796,
6045,
198
] | 2.393258 | 89 |
#!/usr/bin/env python
#-*- coding=utf-8 -*-
#
# Copyright 2012 Jike Inc. All Rights Reserved.
# Author: liwei@jike.com
import re
from urlparse import urlparse
parse1()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
12,
9,
12,
19617,
28,
40477,
12,
23,
532,
9,
12,
198,
2,
198,
2,
15069,
2321,
449,
522,
3457,
13,
1439,
6923,
33876,
13,
198,
2,
6434,
25,
7649,
42990,
31,
73,
522,
13,
785,
198,
198,
11748,
302,
198,
6738,
19016,
29572,
1330,
19016,
29572,
198,
29572,
16,
3419,
198
] | 2.725806 | 62 |
from kivy.uix.gridlayout import GridLayout
from kivy.uix.label import Label
from kivy.uix.textinput import TextInput
from kivy.garden.matplotlib.backend_kivyagg import FigureCanvasKivyAgg
from kivy.uix.anchorlayout import AnchorLayout
from kivy.uix.boxlayout import BoxLayout
from kivy.uix.button import Button
import matplotlib.pyplot as plt
import matplotlib
import datetime
from TransactionBook.model.Filter import Filter
from datetime import datetime
from kivy.uix.popup import Popup
from kivy.properties import NumericProperty, ReferenceListProperty
from kivy.uix.checkbox import CheckBox
from kivy.core.window import Window
if __name__ == "__main__":
from kivy.base import runTouchApp
c = MultiSelectPopUp(title="Test", option_list=["Item1", "Item2", "Item3"], callback=cb, option_init=[True, False, True])
runTouchApp(c) | [
6738,
479,
452,
88,
13,
84,
844,
13,
25928,
39786,
1330,
24846,
32517,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
18242,
1330,
36052,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
5239,
15414,
1330,
8255,
20560,
198,
6738,
479,
452,
88,
13,
70,
5872,
13,
6759,
29487,
8019,
13,
1891,
437,
62,
74,
452,
88,
9460,
1330,
11291,
6090,
11017,
42,
452,
88,
46384,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
3702,
273,
39786,
1330,
29253,
273,
32517,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
3524,
39786,
1330,
8315,
32517,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
16539,
1330,
20969,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
2603,
29487,
8019,
198,
11748,
4818,
8079,
198,
6738,
45389,
10482,
13,
19849,
13,
22417,
1330,
25853,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
12924,
929,
1330,
8099,
929,
198,
6738,
479,
452,
88,
13,
48310,
1330,
399,
39223,
21746,
11,
20984,
8053,
21746,
198,
6738,
479,
452,
88,
13,
84,
844,
13,
9122,
3524,
1330,
6822,
14253,
198,
6738,
479,
452,
88,
13,
7295,
13,
17497,
1330,
26580,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
422,
479,
452,
88,
13,
8692,
1330,
1057,
35211,
4677,
198,
220,
220,
220,
269,
796,
15237,
17563,
16979,
4933,
7,
7839,
2625,
14402,
1600,
3038,
62,
4868,
28,
14692,
7449,
16,
1600,
366,
7449,
17,
1600,
366,
7449,
18,
33116,
23838,
28,
21101,
11,
3038,
62,
15003,
41888,
17821,
11,
10352,
11,
6407,
12962,
198,
220,
220,
220,
1057,
35211,
4677,
7,
66,
8
] | 2.985816 | 282 |
from dataclasses import dataclass, field
from typing import List
from Car2 import Car
| [
6738,
4818,
330,
28958,
1330,
4818,
330,
31172,
11,
2214,
198,
6738,
19720,
1330,
7343,
198,
6738,
1879,
17,
1330,
1879,
628
] | 3.954545 | 22 |
import subprocess
import threading
import time
import errno
import socket
import urllib
import pathlib
from io import StringIO
from http.server import BaseHTTPRequestHandler, HTTPServer
import lib.stations as stations
import lib.epg2xml as epg2xml
import lib.channels_m3u as channels_m3u
from lib.templates import templates
# with help from https://www.acmesystems.it/python_http
# and https://stackoverflow.com/questions/21631799/how-can-i-pass-parameters-to-a-requesthandler
# mostly from https://github.com/ZeWaren/python-upnp-ssdp-example
# and https://stackoverflow.com/questions/46210672/python-2-7-streaming-http-server-supporting-multiple-connections-on-one-port
def start(config, locast, location):
serverSocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
serverSocket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
serverSocket.bind((config["main"]['bind_ip'], int(config["main"]['bind_port'])))
serverSocket.listen(int(config["main"]["concurrent_listeners"]))
print("Now listening for requests.")
for i in range(int(config["main"]["concurrent_listeners"])):
PlexHttpServer(serverSocket, config, locast, location)
| [
11748,
850,
14681,
198,
11748,
4704,
278,
198,
11748,
640,
198,
11748,
11454,
3919,
198,
11748,
17802,
198,
11748,
2956,
297,
571,
198,
11748,
3108,
8019,
198,
6738,
33245,
1330,
10903,
9399,
198,
6738,
2638,
13,
15388,
1330,
7308,
40717,
18453,
25060,
11,
38288,
18497,
198,
198,
11748,
9195,
13,
301,
602,
355,
8985,
198,
11748,
9195,
13,
538,
70,
17,
19875,
355,
2462,
70,
17,
19875,
198,
11748,
9195,
13,
354,
8961,
62,
76,
18,
84,
355,
9619,
62,
76,
18,
84,
198,
6738,
9195,
13,
11498,
17041,
1330,
24019,
628,
198,
2,
351,
1037,
422,
3740,
1378,
2503,
13,
330,
6880,
6781,
82,
13,
270,
14,
29412,
62,
4023,
198,
2,
290,
3740,
1378,
25558,
2502,
11125,
13,
785,
14,
6138,
507,
14,
20666,
34125,
2079,
14,
4919,
12,
5171,
12,
72,
12,
6603,
12,
17143,
7307,
12,
1462,
12,
64,
12,
25927,
30281,
628,
198,
198,
2,
4632,
422,
3740,
1378,
12567,
13,
785,
14,
36056,
54,
5757,
14,
29412,
12,
929,
37659,
12,
824,
26059,
12,
20688,
198,
2,
290,
3740,
1378,
25558,
2502,
11125,
13,
785,
14,
6138,
507,
14,
3510,
21536,
43864,
14,
29412,
12,
17,
12,
22,
12,
5532,
278,
12,
4023,
12,
15388,
12,
11284,
278,
12,
48101,
12,
8443,
507,
12,
261,
12,
505,
12,
634,
628,
198,
4299,
923,
7,
11250,
11,
1179,
459,
11,
4067,
2599,
198,
220,
220,
220,
4382,
39105,
796,
17802,
13,
44971,
7,
44971,
13,
8579,
62,
1268,
2767,
11,
17802,
13,
50,
11290,
62,
2257,
32235,
8,
198,
220,
220,
220,
4382,
39105,
13,
28709,
735,
8738,
7,
44971,
13,
50,
3535,
62,
50,
11290,
2767,
11,
17802,
13,
15821,
62,
2200,
19108,
2885,
7707,
11,
352,
8,
198,
220,
220,
220,
4382,
39105,
13,
21653,
19510,
11250,
14692,
12417,
1,
7131,
6,
21653,
62,
541,
6,
4357,
493,
7,
11250,
14692,
12417,
1,
7131,
6,
21653,
62,
634,
20520,
22305,
198,
220,
220,
220,
4382,
39105,
13,
4868,
268,
7,
600,
7,
11250,
14692,
12417,
1,
7131,
1,
1102,
14421,
62,
4868,
36014,
8973,
4008,
628,
220,
220,
220,
3601,
7203,
3844,
8680,
329,
7007,
19570,
198,
220,
220,
220,
329,
1312,
287,
2837,
7,
600,
7,
11250,
14692,
12417,
1,
7131,
1,
1102,
14421,
62,
4868,
36014,
8973,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
47176,
43481,
10697,
7,
15388,
39105,
11,
4566,
11,
1179,
459,
11,
4067,
8,
198
] | 2.942643 | 401 |
from django import template
from django.contrib.auth.decorators import login_required
from django.http import HttpResponse
from django.template import loader
| [
6738,
42625,
14208,
1330,
11055,
198,
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
12501,
273,
2024,
1330,
17594,
62,
35827,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
6738,
42625,
14208,
13,
28243,
1330,
40213,
628,
198
] | 3.809524 | 42 |
import os
from pathlib import Path
import numpy as np
AUDIO_FILENAME_ENDINGS = (".aiff", ".flac", ".m4a", ".mp3", ".ogg", ".opus", ".wav")
def get_file_paths(
root_path, filename_endings=AUDIO_FILENAME_ENDINGS, traverse_subdirectories=True
):
"""Return a list of paths to all files with the given filename extensions in a directory.
Also traverses subdirectories by default.
"""
file_paths = []
for root, dirs, filenames in os.walk(root_path):
filenames = sorted(filenames)
for filename in filenames:
input_path = os.path.abspath(root)
file_path = os.path.join(input_path, filename)
if filename.lower().endswith(filename_endings):
file_paths.append(Path(file_path))
if not traverse_subdirectories:
# prevent descending into subfolders
break
return file_paths
def calculate_rms(samples):
"""Given a numpy array of audio samples, return its Root Mean Square (RMS)."""
return np.sqrt(np.mean(np.square(samples), axis=-1))
def calculate_desired_noise_rms(clean_rms, snr):
"""
Given the Root Mean Square (RMS) of a clean sound and a desired signal-to-noise ratio (SNR),
calculate the desired RMS of a noise sound to be mixed in.
Based on https://github.com/Sato-Kunihiko/audio-SNR/blob/8d2c933b6c0afe6f1203251f4877e7a1068a6130/create_mixed_audio_file.py#L20
:param clean_rms: Root Mean Square (RMS) - a value between 0.0 and 1.0
:param snr: Signal-to-Noise (SNR) Ratio in dB - typically somewhere between -20 and 60
:return:
"""
a = float(snr) / 20
noise_rms = clean_rms / (10 ** a)
return noise_rms
def is_waveform_multichannel(samples):
"""
Return bool that answers the question: Is the given ndarray a multichannel waveform or not?
:param samples: numpy ndarray
:return:
"""
return len(samples.shape) > 1
def is_spectrogram_multichannel(spectrogram):
"""
Return bool that answers the question: Is the given ndarray a multichannel spectrogram?
:param samples: numpy ndarray
:return:
"""
return len(spectrogram.shape) > 2 and spectrogram.shape[-1] > 1
def convert_float_samples_to_int16(y):
"""Convert floating-point numpy array of audio samples to int16."""
if not issubclass(y.dtype.type, np.floating):
raise ValueError("input samples not floating-point")
return (y * np.iinfo(np.int16).max).astype(np.int16)
| [
11748,
28686,
198,
6738,
3108,
8019,
1330,
10644,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
48877,
9399,
62,
46700,
1677,
10067,
62,
10619,
20754,
796,
357,
1911,
64,
733,
1600,
27071,
2704,
330,
1600,
27071,
76,
19,
64,
1600,
27071,
3149,
18,
1600,
27071,
10332,
1600,
27071,
25790,
1600,
27071,
45137,
4943,
628,
198,
4299,
651,
62,
7753,
62,
6978,
82,
7,
198,
220,
220,
220,
6808,
62,
6978,
11,
29472,
62,
437,
654,
28,
48877,
9399,
62,
46700,
1677,
10067,
62,
10619,
20754,
11,
38138,
62,
7266,
12942,
1749,
28,
17821,
198,
2599,
198,
220,
220,
220,
37227,
13615,
257,
1351,
286,
13532,
284,
477,
3696,
351,
262,
1813,
29472,
18366,
287,
257,
8619,
13,
198,
220,
220,
220,
4418,
33038,
274,
850,
12942,
1749,
416,
4277,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2393,
62,
6978,
82,
796,
17635,
628,
220,
220,
220,
329,
6808,
11,
288,
17062,
11,
1226,
268,
1047,
287,
28686,
13,
11152,
7,
15763,
62,
6978,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1226,
268,
1047,
796,
23243,
7,
10379,
268,
1047,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
29472,
287,
1226,
268,
1047,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
6978,
796,
28686,
13,
6978,
13,
397,
2777,
776,
7,
15763,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2393,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
15414,
62,
6978,
11,
29472,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
29472,
13,
21037,
22446,
437,
2032,
342,
7,
34345,
62,
437,
654,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2393,
62,
6978,
82,
13,
33295,
7,
15235,
7,
7753,
62,
6978,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
38138,
62,
7266,
12942,
1749,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2948,
31491,
656,
850,
11379,
364,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
1441,
2393,
62,
6978,
82,
628,
198,
4299,
15284,
62,
81,
907,
7,
82,
12629,
2599,
198,
220,
220,
220,
37227,
15056,
257,
299,
32152,
7177,
286,
6597,
8405,
11,
1441,
663,
20410,
22728,
9276,
357,
49,
5653,
21387,
15931,
198,
220,
220,
220,
1441,
45941,
13,
31166,
17034,
7,
37659,
13,
32604,
7,
37659,
13,
23415,
7,
82,
12629,
828,
16488,
10779,
16,
4008,
628,
198,
4299,
15284,
62,
8906,
1202,
62,
3919,
786,
62,
81,
907,
7,
27773,
62,
81,
907,
11,
3013,
81,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
11259,
262,
20410,
22728,
9276,
357,
49,
5653,
8,
286,
257,
3424,
2128,
290,
257,
10348,
6737,
12,
1462,
12,
3919,
786,
8064,
357,
15571,
49,
828,
198,
220,
220,
220,
15284,
262,
10348,
371,
5653,
286,
257,
7838,
2128,
284,
307,
7668,
287,
13,
628,
220,
220,
220,
13403,
319,
3740,
1378,
12567,
13,
785,
14,
50,
5549,
12,
42,
403,
4449,
12125,
14,
24051,
12,
15571,
49,
14,
2436,
672,
14,
23,
67,
17,
66,
24,
2091,
65,
21,
66,
15,
8635,
21,
69,
1065,
3070,
28072,
69,
2780,
3324,
68,
22,
64,
940,
3104,
64,
5333,
1270,
14,
17953,
62,
76,
2966,
62,
24051,
62,
7753,
13,
9078,
2,
43,
1238,
198,
220,
220,
220,
1058,
17143,
3424,
62,
81,
907,
25,
20410,
22728,
9276,
357,
49,
5653,
8,
532,
257,
1988,
1022,
657,
13,
15,
290,
352,
13,
15,
198,
220,
220,
220,
1058,
17143,
3013,
81,
25,
26484,
12,
1462,
12,
2949,
786,
357,
15571,
49,
8,
33956,
287,
30221,
532,
6032,
7382,
1022,
532,
1238,
290,
3126,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
257,
796,
12178,
7,
16184,
81,
8,
1220,
1160,
198,
220,
220,
220,
7838,
62,
81,
907,
796,
3424,
62,
81,
907,
1220,
357,
940,
12429,
257,
8,
198,
220,
220,
220,
1441,
7838,
62,
81,
907,
628,
198,
198,
4299,
318,
62,
19204,
687,
62,
16680,
488,
4276,
7,
82,
12629,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
20512,
326,
7429,
262,
1808,
25,
1148,
262,
1813,
299,
67,
18747,
257,
1963,
488,
4276,
6769,
687,
393,
407,
30,
628,
220,
220,
220,
1058,
17143,
8405,
25,
299,
32152,
299,
67,
18747,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
18896,
7,
82,
12629,
13,
43358,
8,
1875,
352,
628,
198,
4299,
318,
62,
4443,
39529,
62,
16680,
488,
4276,
7,
4443,
39529,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
20512,
326,
7429,
262,
1808,
25,
1148,
262,
1813,
299,
67,
18747,
257,
1963,
488,
4276,
5444,
39529,
30,
628,
220,
220,
220,
1058,
17143,
8405,
25,
299,
32152,
299,
67,
18747,
198,
220,
220,
220,
1058,
7783,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
18896,
7,
4443,
39529,
13,
43358,
8,
1875,
362,
290,
5444,
39529,
13,
43358,
58,
12,
16,
60,
1875,
352,
628,
198,
4299,
10385,
62,
22468,
62,
82,
12629,
62,
1462,
62,
600,
1433,
7,
88,
2599,
198,
220,
220,
220,
37227,
3103,
1851,
12462,
12,
4122,
299,
32152,
7177,
286,
6597,
8405,
284,
493,
1433,
526,
15931,
198,
220,
220,
220,
611,
407,
1189,
549,
4871,
7,
88,
13,
67,
4906,
13,
4906,
11,
45941,
13,
48679,
803,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
15414,
8405,
407,
12462,
12,
4122,
4943,
198,
220,
220,
220,
1441,
357,
88,
1635,
45941,
13,
72,
10951,
7,
37659,
13,
600,
1433,
737,
9806,
737,
459,
2981,
7,
37659,
13,
600,
1433,
8,
198
] | 2.547325 | 972 |
s = "([}}])"
stack = []
if len(s) % 2 == 1:
print(False)
exit()
for i in s:
if i == "(":
stack.append("(")
elif i == "[":
stack.append("[")
elif i == "{":
stack.append("{")
elif i == ")":
if len(stack) < 1:
print(False)
exit()
if stack[-1] == "(":
stack.pop()
else:
print(False)
exit()
elif i == "]":
if len(stack) < 1:
print(False)
exit()
if stack[-1] == "[":
stack.pop()
else:
print(False)
exit()
elif i == "}":
if len(stack) < 1:
print(False)
exit()
if stack[-1] == "{":
stack.pop()
else:
print(False)
exit()
if len(stack) == 0:
print(True)
else:
print(False)
| [
82,
796,
366,
26933,
11709,
12962,
1,
198,
198,
25558,
796,
17635,
198,
198,
361,
18896,
7,
82,
8,
4064,
362,
6624,
352,
25,
198,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
8420,
3419,
198,
198,
1640,
1312,
287,
264,
25,
198,
220,
220,
220,
611,
1312,
6624,
30629,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
33295,
7203,
7,
4943,
198,
220,
220,
220,
1288,
361,
1312,
6624,
12878,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
33295,
7203,
58,
4943,
198,
220,
220,
220,
1288,
361,
1312,
6624,
45144,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
33295,
7203,
4895,
8,
198,
220,
220,
220,
1288,
361,
1312,
6624,
366,
8,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
25558,
8,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
8931,
58,
12,
16,
60,
6624,
30629,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
12924,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
220,
220,
220,
1288,
361,
1312,
6624,
366,
60,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
25558,
8,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
8931,
58,
12,
16,
60,
6624,
12878,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
12924,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
220,
220,
220,
1288,
361,
1312,
6624,
366,
92,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
25558,
8,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
8931,
58,
12,
16,
60,
6624,
45144,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8931,
13,
12924,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
198,
198,
361,
18896,
7,
25558,
8,
6624,
657,
25,
198,
220,
220,
220,
3601,
7,
17821,
8,
198,
17772,
25,
198,
220,
220,
220,
3601,
7,
25101,
8,
198
] | 1.647388 | 536 |
import random
import string
import os
from IPython.display import display, HTML
from .utils import html_loader
from .utils import get_content
from jinja2 import Template
| [
11748,
4738,
198,
11748,
4731,
198,
11748,
28686,
198,
198,
6738,
6101,
7535,
13,
13812,
1330,
3359,
11,
11532,
198,
6738,
764,
26791,
1330,
27711,
62,
29356,
198,
6738,
764,
26791,
1330,
651,
62,
11299,
198,
6738,
474,
259,
6592,
17,
1330,
37350,
628
] | 3.909091 | 44 |
from decimal import Decimal
from fixtures import * # noqa: F401,F403
from fixtures import TEST_NETWORK
from flaky import flaky # noqa: F401
from pyln.client import RpcError, Millisatoshi
from utils import (
only_one, wait_for, sync_blockheight, EXPERIMENTAL_FEATURES, COMPAT,
VALGRIND
)
import os
import pytest
import subprocess
import time
import unittest
def test_minconf_withdraw(node_factory, bitcoind):
"""Issue 2518: ensure that ridiculous confirmation levels don't overflow
The number of confirmations is used to compute a maximum height that is to
be accepted. If the current height is smaller than the number of
confirmations we wrap around and just select everything. The fix is to
clamp the maxheight parameter to a positive small number.
"""
amount = 1000000
# Don't get any funds from previous runs.
l1 = node_factory.get_node(random_hsm=True)
addr = l1.rpc.newaddr()['bech32']
# Add some funds to withdraw later
for i in range(10):
l1.bitcoin.rpc.sendtoaddress(addr, amount / 10**8 + 0.01)
bitcoind.generate_block(1)
wait_for(lambda: len(l1.rpc.listfunds()['outputs']) == 10)
with pytest.raises(RpcError):
l1.rpc.withdraw(destination=addr, satoshi=10000, feerate='normal', minconf=9999999)
def test_addfunds_from_block(node_factory, bitcoind):
"""Send funds to the daemon without telling it explicitly
"""
# Previous runs with same bitcoind can leave funds!
l1 = node_factory.get_node(random_hsm=True)
addr = l1.rpc.newaddr()['bech32']
bitcoind.rpc.sendtoaddress(addr, 0.1)
bitcoind.generate_block(1)
wait_for(lambda: len(l1.rpc.listfunds()['outputs']) == 1)
outputs = l1.db_query('SELECT value FROM outputs WHERE status=0;')
assert only_one(outputs)['value'] == 10000000
# The address we detect must match what was paid to.
output = only_one(l1.rpc.listfunds()['outputs'])
assert output['address'] == addr
# Send all our money to a P2WPKH address this time.
addr = l1.rpc.newaddr("bech32")['bech32']
l1.rpc.withdraw(addr, "all")
bitcoind.generate_block(1)
time.sleep(1)
# The address we detect must match what was paid to.
output = only_one(l1.rpc.listfunds()['outputs'])
assert output['address'] == addr
# this test does a 'listtransactions' on a yet unconfirmed channel
def test_fundchannel_listtransaction(node_factory, bitcoind):
l1, l2 = node_factory.get_nodes(2)
l1.fundwallet(10**6)
l1.connect(l2)
txid = l1.rpc.fundchannel(l2.info['id'], 10**5)['txid']
# next call warned about SQL Accessing a null column
# and crashed the daemon for accessing random memory or null
txs = l1.rpc.listtransactions()['transactions']
tx = [t for t in txs if t['hash'] == txid][0]
assert tx['blockheight'] == 0
def test_withdraw_nlocktime(node_factory):
"""
Test that we don't set the nLockTime to 0 for withdrawal transactions.
"""
l1 = node_factory.get_node(1)
l1.fundwallet(10**4)
addr = l1.rpc.newaddr()["bech32"]
tx = l1.rpc.withdraw(addr, 10**3)["tx"]
nlocktime = node_factory.bitcoind.rpc.decoderawtransaction(tx)["locktime"]
tip = node_factory.bitcoind.rpc.getblockcount()
assert nlocktime > 0 and nlocktime <= tip
| [
6738,
32465,
1330,
4280,
4402,
198,
6738,
34609,
1330,
1635,
220,
1303,
645,
20402,
25,
376,
21844,
11,
37,
31552,
198,
6738,
34609,
1330,
43001,
62,
12884,
33249,
198,
6738,
781,
15492,
1330,
781,
15492,
220,
1303,
645,
20402,
25,
376,
21844,
198,
6738,
279,
2645,
77,
13,
16366,
1330,
371,
14751,
12331,
11,
9212,
271,
265,
13704,
198,
6738,
3384,
4487,
1330,
357,
198,
220,
220,
220,
691,
62,
505,
11,
4043,
62,
1640,
11,
17510,
62,
9967,
17015,
11,
7788,
18973,
3955,
3525,
1847,
62,
15112,
47471,
11,
24301,
1404,
11,
198,
220,
220,
220,
26173,
10761,
12115,
198,
8,
198,
198,
11748,
28686,
198,
11748,
12972,
9288,
198,
11748,
850,
14681,
198,
11748,
640,
198,
11748,
555,
715,
395,
628,
198,
198,
4299,
1332,
62,
1084,
10414,
62,
4480,
19334,
7,
17440,
62,
69,
9548,
11,
1643,
1073,
521,
2599,
198,
220,
220,
220,
37227,
45147,
1679,
1507,
25,
4155,
326,
11441,
12641,
2974,
836,
470,
30343,
628,
220,
220,
220,
383,
1271,
286,
6216,
602,
318,
973,
284,
24061,
257,
5415,
6001,
326,
318,
284,
198,
220,
220,
220,
307,
6292,
13,
1002,
262,
1459,
6001,
318,
4833,
621,
262,
1271,
286,
198,
220,
220,
220,
6216,
602,
356,
14441,
1088,
290,
655,
2922,
2279,
13,
383,
4259,
318,
284,
198,
220,
220,
220,
29405,
262,
3509,
17015,
11507,
284,
257,
3967,
1402,
1271,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
2033,
796,
1802,
2388,
198,
220,
220,
220,
1303,
2094,
470,
651,
597,
5153,
422,
2180,
4539,
13,
198,
220,
220,
220,
300,
16,
796,
10139,
62,
69,
9548,
13,
1136,
62,
17440,
7,
25120,
62,
71,
5796,
28,
17821,
8,
198,
220,
220,
220,
37817,
796,
300,
16,
13,
81,
14751,
13,
3605,
29851,
3419,
17816,
1350,
354,
2624,
20520,
628,
220,
220,
220,
1303,
3060,
617,
5153,
284,
8399,
1568,
198,
220,
220,
220,
329,
1312,
287,
2837,
7,
940,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
13,
35395,
13,
81,
14751,
13,
21280,
83,
1170,
49380,
7,
29851,
11,
2033,
1220,
838,
1174,
23,
1343,
657,
13,
486,
8,
628,
220,
220,
220,
1643,
1073,
521,
13,
8612,
378,
62,
9967,
7,
16,
8,
628,
220,
220,
220,
4043,
62,
1640,
7,
50033,
25,
18896,
7,
75,
16,
13,
81,
14751,
13,
4868,
10990,
82,
3419,
17816,
22915,
82,
6,
12962,
6624,
838,
8,
198,
220,
220,
220,
351,
12972,
9288,
13,
430,
2696,
7,
49,
14751,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
13,
81,
14751,
13,
4480,
19334,
7,
16520,
1883,
28,
29851,
11,
3332,
13704,
28,
49388,
11,
730,
21620,
11639,
11265,
3256,
949,
10414,
28,
24214,
17032,
8,
628,
198,
4299,
1332,
62,
2860,
10990,
82,
62,
6738,
62,
9967,
7,
17440,
62,
69,
9548,
11,
1643,
1073,
521,
2599,
198,
220,
220,
220,
37227,
25206,
5153,
284,
262,
33386,
1231,
5149,
340,
11777,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
21801,
4539,
351,
976,
1643,
1073,
521,
460,
2666,
5153,
0,
198,
220,
220,
220,
300,
16,
796,
10139,
62,
69,
9548,
13,
1136,
62,
17440,
7,
25120,
62,
71,
5796,
28,
17821,
8,
628,
220,
220,
220,
37817,
796,
300,
16,
13,
81,
14751,
13,
3605,
29851,
3419,
17816,
1350,
354,
2624,
20520,
198,
220,
220,
220,
1643,
1073,
521,
13,
81,
14751,
13,
21280,
83,
1170,
49380,
7,
29851,
11,
657,
13,
16,
8,
198,
220,
220,
220,
1643,
1073,
521,
13,
8612,
378,
62,
9967,
7,
16,
8,
628,
220,
220,
220,
4043,
62,
1640,
7,
50033,
25,
18896,
7,
75,
16,
13,
81,
14751,
13,
4868,
10990,
82,
3419,
17816,
22915,
82,
6,
12962,
6624,
352,
8,
628,
220,
220,
220,
23862,
796,
300,
16,
13,
9945,
62,
22766,
10786,
46506,
1988,
16034,
23862,
33411,
3722,
28,
15,
26,
11537,
198,
220,
220,
220,
6818,
691,
62,
505,
7,
22915,
82,
8,
17816,
8367,
20520,
6624,
1802,
20483,
628,
220,
220,
220,
1303,
383,
2209,
356,
4886,
1276,
2872,
644,
373,
3432,
284,
13,
198,
220,
220,
220,
5072,
796,
691,
62,
505,
7,
75,
16,
13,
81,
14751,
13,
4868,
10990,
82,
3419,
17816,
22915,
82,
6,
12962,
198,
220,
220,
220,
6818,
5072,
17816,
21975,
20520,
6624,
37817,
628,
220,
220,
220,
1303,
16290,
477,
674,
1637,
284,
257,
350,
17,
25527,
42,
39,
2209,
428,
640,
13,
198,
220,
220,
220,
37817,
796,
300,
16,
13,
81,
14751,
13,
3605,
29851,
7203,
1350,
354,
2624,
4943,
17816,
1350,
354,
2624,
20520,
198,
220,
220,
220,
300,
16,
13,
81,
14751,
13,
4480,
19334,
7,
29851,
11,
366,
439,
4943,
198,
220,
220,
220,
1643,
1073,
521,
13,
8612,
378,
62,
9967,
7,
16,
8,
198,
220,
220,
220,
640,
13,
42832,
7,
16,
8,
628,
220,
220,
220,
1303,
383,
2209,
356,
4886,
1276,
2872,
644,
373,
3432,
284,
13,
198,
220,
220,
220,
5072,
796,
691,
62,
505,
7,
75,
16,
13,
81,
14751,
13,
4868,
10990,
82,
3419,
17816,
22915,
82,
6,
12962,
198,
220,
220,
220,
6818,
5072,
17816,
21975,
20520,
6624,
37817,
628,
628,
628,
628,
628,
198,
2,
428,
1332,
857,
257,
705,
4868,
7645,
4658,
6,
319,
257,
1865,
555,
36349,
6518,
198,
4299,
1332,
62,
10990,
17620,
62,
4868,
7645,
2673,
7,
17440,
62,
69,
9548,
11,
1643,
1073,
521,
2599,
198,
220,
220,
220,
300,
16,
11,
300,
17,
796,
10139,
62,
69,
9548,
13,
1136,
62,
77,
4147,
7,
17,
8,
198,
220,
220,
220,
300,
16,
13,
10990,
44623,
7,
940,
1174,
21,
8,
628,
220,
220,
220,
300,
16,
13,
8443,
7,
75,
17,
8,
198,
220,
220,
220,
27765,
312,
796,
300,
16,
13,
81,
14751,
13,
10990,
17620,
7,
75,
17,
13,
10951,
17816,
312,
6,
4357,
838,
1174,
20,
8,
17816,
17602,
312,
20520,
628,
220,
220,
220,
1303,
1306,
869,
7728,
546,
16363,
8798,
278,
257,
9242,
5721,
198,
220,
220,
220,
1303,
290,
14997,
262,
33386,
329,
22534,
4738,
4088,
393,
9242,
198,
220,
220,
220,
27765,
82,
796,
300,
16,
13,
81,
14751,
13,
4868,
7645,
4658,
3419,
17816,
7645,
4658,
20520,
628,
220,
220,
220,
27765,
796,
685,
83,
329,
256,
287,
27765,
82,
611,
256,
17816,
17831,
20520,
6624,
27765,
312,
7131,
15,
60,
198,
220,
220,
220,
6818,
27765,
17816,
9967,
17015,
20520,
6624,
657,
628,
198,
4299,
1332,
62,
4480,
19334,
62,
77,
5354,
2435,
7,
17440,
62,
69,
9548,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6208,
326,
356,
836,
470,
900,
262,
299,
25392,
7575,
284,
657,
329,
15220,
8945,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
300,
16,
796,
10139,
62,
69,
9548,
13,
1136,
62,
17440,
7,
16,
8,
198,
220,
220,
220,
300,
16,
13,
10990,
44623,
7,
940,
1174,
19,
8,
628,
220,
220,
220,
37817,
796,
300,
16,
13,
81,
14751,
13,
3605,
29851,
3419,
14692,
1350,
354,
2624,
8973,
198,
220,
220,
220,
27765,
796,
300,
16,
13,
81,
14751,
13,
4480,
19334,
7,
29851,
11,
838,
1174,
18,
8,
14692,
17602,
8973,
198,
220,
220,
220,
299,
5354,
2435,
796,
10139,
62,
69,
9548,
13,
2545,
1073,
521,
13,
81,
14751,
13,
12501,
12342,
707,
7645,
2673,
7,
17602,
8,
14692,
5354,
2435,
8973,
198,
220,
220,
220,
8171,
796,
10139,
62,
69,
9548,
13,
2545,
1073,
521,
13,
81,
14751,
13,
1136,
9967,
9127,
3419,
628,
220,
220,
220,
6818,
299,
5354,
2435,
1875,
657,
290,
299,
5354,
2435,
19841,
8171,
628
] | 2.637161 | 1,254 |
"""Provides plots of mutations for Isolates and Lines."""
from microbepy.common import constants as cn
from microbepy.common.dataframe_sorter import DataframeSorter
from microbepy.common.isolate import Isolate
from microbepy.common import util
from microbepy.correlation import genome_correlation
from microbepy.data.model_data_provider import ModelDataProvider
from microbepy.data import util_data
from microbepy.plot.mutation_cofraction import MutationCofraction
from microbepy.plot.util_plot import PlotParms
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
COLORS = ['red', 'green', 'blue']
SPECIES = {cn.SPECIES_MIX_DVH: "DVH",
cn.SPECIES_MIX_MMP: "MMP",
None: "both"}
FONTSIZE_TITLE = 16
FONTSIZE_LABEL = 8
MAX_LINES = 9
MIN_FRACTION = 0.25
THRESHOLD_FRAC = 0.2
MAX_SIGLVL = 0.01
COLORBAR_MIN = 1.0
COLORBAR_MAX = 4.0
| [
37811,
15946,
1460,
21528,
286,
220,
23005,
329,
1148,
349,
689,
290,
26299,
526,
15931,
198,
198,
6738,
4580,
65,
538,
88,
13,
11321,
1330,
38491,
355,
269,
77,
198,
6738,
4580,
65,
538,
88,
13,
11321,
13,
7890,
14535,
62,
82,
4337,
1330,
6060,
14535,
50,
4337,
198,
6738,
4580,
65,
538,
88,
13,
11321,
13,
271,
27976,
1330,
1148,
27976,
198,
6738,
4580,
65,
538,
88,
13,
11321,
1330,
7736,
198,
6738,
4580,
65,
538,
88,
13,
10215,
49501,
1330,
19270,
62,
10215,
49501,
198,
6738,
4580,
65,
538,
88,
13,
7890,
13,
19849,
62,
7890,
62,
15234,
1304,
1330,
9104,
6601,
29495,
198,
6738,
4580,
65,
538,
88,
13,
7890,
1330,
7736,
62,
7890,
198,
6738,
4580,
65,
538,
88,
13,
29487,
13,
76,
7094,
62,
1073,
69,
7861,
1330,
337,
7094,
34,
1659,
7861,
198,
6738,
4580,
65,
538,
88,
13,
29487,
13,
22602,
62,
29487,
1330,
28114,
47,
8357,
198,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
384,
397,
1211,
355,
3013,
82,
628,
198,
25154,
20673,
796,
37250,
445,
3256,
705,
14809,
3256,
705,
17585,
20520,
198,
48451,
11015,
796,
1391,
31522,
13,
48451,
11015,
62,
8895,
55,
62,
35,
53,
39,
25,
366,
35,
53,
39,
1600,
198,
220,
220,
220,
269,
77,
13,
48451,
11015,
62,
8895,
55,
62,
44,
7378,
25,
366,
44,
7378,
1600,
198,
220,
220,
220,
6045,
25,
366,
16885,
20662,
198,
37,
1340,
4694,
35400,
62,
49560,
2538,
796,
1467,
198,
37,
1340,
4694,
35400,
62,
48780,
3698,
796,
807,
198,
22921,
62,
34509,
1546,
796,
860,
198,
23678,
62,
10913,
44710,
796,
657,
13,
1495,
198,
4221,
19535,
39,
15173,
62,
10913,
2246,
796,
657,
13,
17,
198,
22921,
62,
50,
3528,
30976,
43,
796,
657,
13,
486,
198,
46786,
33,
1503,
62,
23678,
796,
352,
13,
15,
198,
46786,
33,
1503,
62,
22921,
796,
604,
13,
15,
628
] | 2.656627 | 332 |
# Copyright (c) 2017 Sony Corporation. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import os
from scipy.misc import imread
from args import get_args
import matplotlib.pyplot as plt
def encode_label(label):
'''
Converting pixel values to corresponding class numbers. Assuming that the input label in 3-dim(h,w,c) and in BGR fromat read from cv2
'''
h, w, c = label.shape
new_label = np.zeros((h, w, 1), dtype=np.int32)
cls_to_clr_map = get_color()
for i in range(cls_to_clr_map.shape[0]):
#new_label[(label == cls_to_clr_map[i])[:,:,0]] = i
#new_label[np.argwhere((label.astype(np.int32) == cls_to_clr_map[i]).all(axis=2))]=i
print(np.where((label.astype(np.int32) == [120, 0, 128]).all(axis=2)))
if i == 21:
new_label[np.where(
(label.astype(np.int32) == cls_to_clr_map[i]).all(axis=2))] = 255
else:
new_label[np.where(
(label.astype(np.int32) == cls_to_clr_map[i]).all(axis=2))] = i
return new_label
# this method should generate train-image.txt and train-label.txt
def main():
'''
Arguments:
train-file = txt file containing randomly selected image filenames to be taken as training set.
val-file = txt file containing randomly selected image filenames to be taken as validation set.
data-dir = dataset directory
Usage: python dataset_utils.py --train-file="" --val-file="" --data_dir=""
'''
args = get_args()
data_dir = args.data_dir
if not os.path.exists(data_dir+'SegmentationClass/' + 'encoded/'):
os.makedirs(data_dir+'SegmentationClass/' + 'encoded/')
for filename in os.listdir(data_dir+'SegmentationClass/'):
if os.path.isdir(data_dir+'SegmentationClass/' + filename):
continue
label = imread(data_dir+'SegmentationClass/' +
filename).astype('float32')
label = encode_label(label)
np.save(data_dir+'SegmentationClass/' + 'encoded/' +
filename.split('.')[0] + '.npy', label)
generate_path_files(args.data_dir, args.train_file, args.val_file)
if __name__ == '__main__':
main()
| [
2,
15069,
357,
66,
8,
2177,
10184,
10501,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28686,
198,
6738,
629,
541,
88,
13,
44374,
1330,
545,
961,
198,
6738,
26498,
1330,
651,
62,
22046,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
628,
198,
198,
4299,
37773,
62,
18242,
7,
18242,
2599,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
35602,
889,
17465,
3815,
284,
11188,
1398,
3146,
13,
33238,
326,
262,
5128,
6167,
287,
513,
12,
27740,
7,
71,
11,
86,
11,
66,
8,
290,
287,
347,
10761,
422,
265,
1100,
422,
269,
85,
17,
198,
220,
220,
220,
705,
7061,
628,
220,
220,
220,
289,
11,
266,
11,
269,
796,
6167,
13,
43358,
198,
220,
220,
220,
649,
62,
18242,
796,
45941,
13,
9107,
418,
19510,
71,
11,
266,
11,
352,
828,
288,
4906,
28,
37659,
13,
600,
2624,
8,
628,
220,
220,
220,
537,
82,
62,
1462,
62,
565,
81,
62,
8899,
796,
651,
62,
8043,
3419,
628,
220,
220,
220,
329,
1312,
287,
2837,
7,
565,
82,
62,
1462,
62,
565,
81,
62,
8899,
13,
43358,
58,
15,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3605,
62,
18242,
58,
7,
18242,
6624,
537,
82,
62,
1462,
62,
565,
81,
62,
8899,
58,
72,
12962,
58,
45299,
45299,
15,
11907,
796,
1312,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3605,
62,
18242,
58,
37659,
13,
853,
3003,
19510,
18242,
13,
459,
2981,
7,
37659,
13,
600,
2624,
8,
6624,
537,
82,
62,
1462,
62,
565,
81,
62,
8899,
58,
72,
35944,
439,
7,
22704,
28,
17,
4008,
22241,
72,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
37659,
13,
3003,
19510,
18242,
13,
459,
2981,
7,
37659,
13,
600,
2624,
8,
6624,
685,
10232,
11,
657,
11,
13108,
35944,
439,
7,
22704,
28,
17,
22305,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
6624,
2310,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
18242,
58,
37659,
13,
3003,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
18242,
13,
459,
2981,
7,
37659,
13,
600,
2624,
8,
6624,
537,
82,
62,
1462,
62,
565,
81,
62,
8899,
58,
72,
35944,
439,
7,
22704,
28,
17,
4008,
60,
796,
14280,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
18242,
58,
37659,
13,
3003,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
18242,
13,
459,
2981,
7,
37659,
13,
600,
2624,
8,
6624,
537,
82,
62,
1462,
62,
565,
81,
62,
8899,
58,
72,
35944,
439,
7,
22704,
28,
17,
4008,
60,
796,
1312,
628,
220,
220,
220,
1441,
649,
62,
18242,
628,
198,
2,
428,
2446,
815,
7716,
4512,
12,
9060,
13,
14116,
290,
4512,
12,
18242,
13,
14116,
628,
198,
4299,
1388,
33529,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
20559,
2886,
25,
198,
220,
220,
220,
4512,
12,
7753,
796,
256,
742,
2393,
7268,
15456,
6163,
2939,
1226,
268,
1047,
284,
307,
2077,
355,
3047,
900,
13,
198,
220,
220,
220,
1188,
12,
7753,
796,
256,
742,
2393,
7268,
15456,
6163,
2939,
1226,
268,
1047,
284,
307,
2077,
355,
21201,
900,
13,
198,
220,
220,
220,
1366,
12,
15908,
796,
27039,
8619,
198,
220,
220,
220,
29566,
25,
21015,
27039,
62,
26791,
13,
9078,
1377,
27432,
12,
7753,
33151,
1377,
2100,
12,
7753,
33151,
1377,
7890,
62,
15908,
33151,
198,
220,
220,
220,
705,
7061,
628,
220,
220,
220,
26498,
796,
651,
62,
22046,
3419,
198,
220,
220,
220,
1366,
62,
15908,
796,
26498,
13,
7890,
62,
15908,
628,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
1343,
705,
12685,
9043,
14,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
1343,
705,
12685,
9043,
14,
11537,
198,
220,
220,
220,
329,
29472,
287,
28686,
13,
4868,
15908,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
28686,
13,
6978,
13,
9409,
343,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
1343,
29472,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
796,
545,
961,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29472,
737,
459,
2981,
10786,
22468,
2624,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
796,
37773,
62,
18242,
7,
18242,
8,
198,
220,
220,
220,
220,
220,
220,
220,
45941,
13,
21928,
7,
7890,
62,
15908,
10,
6,
41030,
14374,
9487,
14,
6,
1343,
705,
12685,
9043,
14,
6,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29472,
13,
35312,
10786,
2637,
38381,
15,
60,
1343,
45302,
77,
9078,
3256,
6167,
8,
628,
220,
220,
220,
7716,
62,
6978,
62,
16624,
7,
22046,
13,
7890,
62,
15908,
11,
26498,
13,
27432,
62,
7753,
11,
26498,
13,
2100,
62,
7753,
8,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.506925 | 1,083 |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
#
import collections
import os
import torch
import math
from fairseq import bleu, data, options, utils
from fairseq.meters import AverageMeter, StopwatchMeter, TimeMeter
from fairseq.multiprocessing_trainer import MultiprocessingTrainer
from fairseq.progress_bar import progress_bar
from fairseq.sequence_generator import SequenceGenerator
def train(args, epoch, batch_offset, trainer, criterion, dataset, num_gpus):
"""Train the model for one epoch."""
itr = dataset.dataloader(args.train_subset, batch_size=args.batch_size,
test_batch_size=args.test_batch_size,
valid_batch_size=args.valid_batch_size,
num_workers=args.workers,
max_tokens=args.max_tokens, seed=args.seed, epoch=epoch,
max_positions=args.max_positions,
sample_without_replacement=args.sample_without_replacement)
loss_meter = AverageMeter()
bsz_meter = AverageMeter() # sentences per batch
wpb_meter = AverageMeter() # words per batch
wps_meter = TimeMeter() # words per second
clip_meter = AverageMeter() # % of updates clipped
gnorm_meter = AverageMeter() # gradient norm
desc = '| epoch {:03d}'.format(epoch)
lr = trainer.get_lr()
with progress_bar(itr, desc, leave=False) as t:
for i, sample in data.skip_group_enumerator(t, num_gpus, batch_offset):
loss, grad_norm = trainer.train_step(sample, criterion)
ntokens = sum(s['ntokens'] for s in sample)
src_size = sum(s['src_tokens'].size(0) for s in sample)
loss_meter.update(loss, ntokens)
bsz_meter.update(src_size)
wpb_meter.update(ntokens)
wps_meter.update(ntokens)
clip_meter.update(1 if grad_norm > args.clip_norm else 0)
gnorm_meter.update(grad_norm)
t.set_postfix(collections.OrderedDict([
('loss', '{:.2f} ({:.2f})'.format(loss, loss_meter.avg)),
('wps', '{:5d}'.format(round(wps_meter.avg))),
('wpb', '{:5d}'.format(round(wpb_meter.avg))),
('bsz', '{:5d}'.format(round(bsz_meter.avg))),
('lr', lr),
('clip', '{:3.0f}%'.format(clip_meter.avg * 100)),
('gnorm', '{:.4f}'.format(gnorm_meter.avg)),
]))
if i == 0:
# ignore the first mini-batch in words-per-second calculation
wps_meter.reset()
if args.save_interval > 0 and (i + 1) % args.save_interval == 0:
trainer.save_checkpoint(args, epoch, i + 1)
fmt = desc + ' | train loss {:2.2f} | train ppl {:3.2f}'
fmt += ' | s/checkpoint {:7d} | words/s {:6d} | words/batch {:6d}'
fmt += ' | bsz {:5d} | lr {:0.6f} | clip {:3.0f}% | gnorm {:.4f}'
t.write(fmt.format(loss_meter.avg, math.pow(2, loss_meter.avg),
round(wps_meter.elapsed_time),
round(wps_meter.avg),
round(wpb_meter.avg),
round(bsz_meter.avg),
lr, clip_meter.avg * 100,
gnorm_meter.avg))
def validate(args, epoch, trainer, criterion, dataset, subset, ngpus):
"""Evaluate the model on the validation set and return the average loss."""
itr = dataset.dataloader(subset, batch_size=None,
max_tokens=args.max_tokens,
max_positions=args.max_positions)
loss_meter = AverageMeter()
desc = '| epoch {:03d} | valid on \'{}\' subset'.format(epoch, subset)
with progress_bar(itr, desc, leave=False) as t:
for _, sample in data.skip_group_enumerator(t, ngpus):
ntokens = sum(s['ntokens'] for s in sample)
loss = trainer.valid_step(sample, criterion)
loss_meter.update(loss, ntokens)
t.set_postfix(loss='{:.2f}'.format(loss_meter.avg))
val_loss = loss_meter.avg
t.write(desc + ' | valid loss {:2.2f} | valid ppl {:3.2f}'
.format(val_loss, math.pow(2, val_loss)))
# update and return the learning rate
return val_loss
def score_test(args, model, dataset, subset, beam, cuda_device):
"""Evaluate the model on the test set and return the BLEU scorer."""
translator = SequenceGenerator([model], dataset.dst_dict, beam_size=beam)
if torch.cuda.is_available():
translator.cuda()
scorer = bleu.Scorer(dataset.dst_dict.pad(), dataset.dst_dict.eos(), dataset.dst_dict.unk())
itr = dataset.dataloader(subset, batch_size=4, max_positions=args.max_positions)
for _, _, ref, hypos in translator.generate_batched_itr(itr, cuda_device=cuda_device):
scorer.add(ref.int().cpu(), hypos[0]['tokens'].int().cpu())
return scorer
if __name__ == '__main__':
main()
| [
2,
15069,
357,
66,
8,
2177,
12,
25579,
11,
3203,
11,
3457,
13,
198,
2,
1439,
2489,
10395,
13,
198,
2,
198,
2,
770,
2723,
2438,
318,
11971,
739,
262,
5964,
1043,
287,
262,
38559,
24290,
2393,
287,
198,
2,
262,
6808,
8619,
286,
428,
2723,
5509,
13,
1052,
3224,
7264,
286,
12701,
2489,
198,
2,
460,
307,
1043,
287,
262,
28748,
15365,
2393,
287,
262,
976,
8619,
13,
198,
2,
198,
198,
11748,
17268,
198,
11748,
28686,
198,
11748,
28034,
198,
11748,
10688,
198,
198,
6738,
3148,
41068,
1330,
7245,
84,
11,
1366,
11,
3689,
11,
3384,
4487,
198,
6738,
3148,
41068,
13,
4164,
364,
1330,
13475,
44,
2357,
11,
13707,
8340,
44,
2357,
11,
3862,
44,
2357,
198,
6738,
3148,
41068,
13,
16680,
541,
305,
919,
278,
62,
2213,
10613,
1330,
7854,
541,
305,
919,
278,
2898,
10613,
198,
6738,
3148,
41068,
13,
33723,
62,
5657,
1330,
4371,
62,
5657,
198,
6738,
3148,
41068,
13,
43167,
62,
8612,
1352,
1330,
45835,
8645,
1352,
628,
198,
198,
4299,
4512,
7,
22046,
11,
36835,
11,
15458,
62,
28968,
11,
21997,
11,
34054,
11,
27039,
11,
997,
62,
31197,
385,
2599,
198,
220,
220,
220,
37227,
44077,
262,
2746,
329,
530,
36835,
526,
15931,
628,
220,
220,
220,
340,
81,
796,
27039,
13,
67,
10254,
1170,
263,
7,
22046,
13,
27432,
62,
7266,
2617,
11,
15458,
62,
7857,
28,
22046,
13,
43501,
62,
7857,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1332,
62,
43501,
62,
7857,
28,
22046,
13,
9288,
62,
43501,
62,
7857,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4938,
62,
43501,
62,
7857,
28,
22046,
13,
12102,
62,
43501,
62,
7857,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
22896,
28,
22046,
13,
22896,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
83,
482,
641,
28,
22046,
13,
9806,
62,
83,
482,
641,
11,
9403,
28,
22046,
13,
28826,
11,
36835,
28,
538,
5374,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
1930,
1756,
28,
22046,
13,
9806,
62,
1930,
1756,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6291,
62,
19419,
62,
35666,
5592,
28,
22046,
13,
39873,
62,
19419,
62,
35666,
5592,
8,
198,
220,
220,
220,
2994,
62,
27231,
796,
13475,
44,
2357,
3419,
198,
220,
220,
220,
275,
82,
89,
62,
27231,
796,
13475,
44,
2357,
3419,
220,
220,
220,
1303,
13439,
583,
15458,
198,
220,
220,
220,
266,
40842,
62,
27231,
796,
13475,
44,
2357,
3419,
220,
220,
220,
1303,
2456,
583,
15458,
198,
220,
220,
220,
266,
862,
62,
27231,
796,
3862,
44,
2357,
3419,
220,
220,
220,
220,
220,
220,
1303,
2456,
583,
1218,
198,
220,
220,
220,
10651,
62,
27231,
796,
13475,
44,
2357,
3419,
220,
220,
1303,
4064,
286,
5992,
49305,
198,
220,
220,
220,
19967,
579,
62,
27231,
796,
13475,
44,
2357,
3419,
220,
1303,
31312,
2593,
628,
220,
220,
220,
1715,
796,
705,
91,
36835,
46110,
3070,
67,
92,
4458,
18982,
7,
538,
5374,
8,
198,
220,
220,
220,
300,
81,
796,
21997,
13,
1136,
62,
14050,
3419,
198,
220,
220,
220,
351,
4371,
62,
5657,
7,
270,
81,
11,
1715,
11,
2666,
28,
25101,
8,
355,
256,
25,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
11,
6291,
287,
1366,
13,
48267,
62,
8094,
62,
268,
6975,
1352,
7,
83,
11,
997,
62,
31197,
385,
11,
15458,
62,
28968,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2994,
11,
3915,
62,
27237,
796,
21997,
13,
27432,
62,
9662,
7,
39873,
11,
34054,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
83,
482,
641,
796,
2160,
7,
82,
17816,
429,
482,
641,
20520,
329,
264,
287,
6291,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
62,
7857,
796,
2160,
7,
82,
17816,
10677,
62,
83,
482,
641,
6,
4083,
7857,
7,
15,
8,
329,
264,
287,
6291,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2994,
62,
27231,
13,
19119,
7,
22462,
11,
299,
83,
482,
641,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
82,
89,
62,
27231,
13,
19119,
7,
10677,
62,
7857,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
266,
40842,
62,
27231,
13,
19119,
7,
429,
482,
641,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
266,
862,
62,
27231,
13,
19119,
7,
429,
482,
641,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10651,
62,
27231,
13,
19119,
7,
16,
611,
3915,
62,
27237,
1875,
26498,
13,
15036,
62,
27237,
2073,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19967,
579,
62,
27231,
13,
19119,
7,
9744,
62,
27237,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
2617,
62,
7353,
13049,
7,
4033,
26448,
13,
35422,
1068,
35,
713,
26933,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
22462,
3256,
705,
90,
25,
13,
17,
69,
92,
37913,
25,
13,
17,
69,
30072,
4458,
18982,
7,
22462,
11,
2994,
62,
27231,
13,
615,
70,
36911,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
86,
862,
3256,
705,
90,
25,
20,
67,
92,
4458,
18982,
7,
744,
7,
86,
862,
62,
27231,
13,
615,
70,
4008,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
24142,
65,
3256,
705,
90,
25,
20,
67,
92,
4458,
18982,
7,
744,
7,
24142,
65,
62,
27231,
13,
615,
70,
4008,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
1443,
89,
3256,
705,
90,
25,
20,
67,
92,
4458,
18982,
7,
744,
7,
1443,
89,
62,
27231,
13,
615,
70,
4008,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
14050,
3256,
300,
81,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
15036,
3256,
705,
90,
25,
18,
13,
15,
69,
92,
4,
4458,
18982,
7,
15036,
62,
27231,
13,
615,
70,
1635,
1802,
36911,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19203,
4593,
579,
3256,
705,
90,
25,
13,
19,
69,
92,
4458,
18982,
7,
4593,
579,
62,
27231,
13,
615,
70,
36911,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
8856,
262,
717,
9927,
12,
43501,
287,
2456,
12,
525,
12,
12227,
17952,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
266,
862,
62,
27231,
13,
42503,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
26498,
13,
21928,
62,
3849,
2100,
1875,
657,
290,
357,
72,
1343,
352,
8,
4064,
26498,
13,
21928,
62,
3849,
2100,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21997,
13,
21928,
62,
9122,
4122,
7,
22046,
11,
36835,
11,
1312,
1343,
352,
8,
628,
220,
220,
220,
220,
220,
220,
220,
46996,
796,
1715,
1343,
705,
930,
4512,
2994,
46110,
17,
13,
17,
69,
92,
930,
4512,
279,
489,
46110,
18,
13,
17,
69,
92,
6,
198,
220,
220,
220,
220,
220,
220,
220,
46996,
15853,
705,
930,
264,
14,
9122,
4122,
46110,
22,
67,
92,
930,
2456,
14,
82,
46110,
21,
67,
92,
930,
2456,
14,
43501,
46110,
21,
67,
92,
6,
198,
220,
220,
220,
220,
220,
220,
220,
46996,
15853,
705,
930,
275,
82,
89,
46110,
20,
67,
92,
930,
300,
81,
46110,
15,
13,
21,
69,
92,
930,
10651,
46110,
18,
13,
15,
69,
92,
4,
930,
19967,
579,
46110,
13,
19,
69,
92,
6,
198,
220,
220,
220,
220,
220,
220,
220,
256,
13,
13564,
7,
69,
16762,
13,
18982,
7,
22462,
62,
27231,
13,
615,
70,
11,
10688,
13,
79,
322,
7,
17,
11,
2994,
62,
27231,
13,
615,
70,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2835,
7,
86,
862,
62,
27231,
13,
417,
28361,
62,
2435,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2835,
7,
86,
862,
62,
27231,
13,
615,
70,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2835,
7,
24142,
65,
62,
27231,
13,
615,
70,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2835,
7,
1443,
89,
62,
27231,
13,
615,
70,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
81,
11,
10651,
62,
27231,
13,
615,
70,
1635,
1802,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19967,
579,
62,
27231,
13,
615,
70,
4008,
628,
198,
4299,
26571,
7,
22046,
11,
36835,
11,
21997,
11,
34054,
11,
27039,
11,
24637,
11,
23370,
79,
385,
2599,
198,
220,
220,
220,
37227,
36,
2100,
4985,
262,
2746,
319,
262,
21201,
900,
290,
1441,
262,
2811,
2994,
526,
15931,
628,
220,
220,
220,
340,
81,
796,
27039,
13,
67,
10254,
1170,
263,
7,
7266,
2617,
11,
15458,
62,
7857,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
83,
482,
641,
28,
22046,
13,
9806,
62,
83,
482,
641,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
1930,
1756,
28,
22046,
13,
9806,
62,
1930,
1756,
8,
198,
220,
220,
220,
2994,
62,
27231,
796,
13475,
44,
2357,
3419,
628,
220,
220,
220,
1715,
796,
705,
91,
36835,
46110,
3070,
67,
92,
930,
4938,
319,
34373,
90,
32239,
6,
24637,
4458,
18982,
7,
538,
5374,
11,
24637,
8,
198,
220,
220,
220,
351,
4371,
62,
5657,
7,
270,
81,
11,
1715,
11,
2666,
28,
25101,
8,
355,
256,
25,
198,
220,
220,
220,
220,
220,
220,
220,
329,
4808,
11,
6291,
287,
1366,
13,
48267,
62,
8094,
62,
268,
6975,
1352,
7,
83,
11,
23370,
79,
385,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
83,
482,
641,
796,
2160,
7,
82,
17816,
429,
482,
641,
20520,
329,
264,
287,
6291,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2994,
796,
21997,
13,
12102,
62,
9662,
7,
39873,
11,
34054,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2994,
62,
27231,
13,
19119,
7,
22462,
11,
299,
83,
482,
641,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
2617,
62,
7353,
13049,
7,
22462,
11639,
90,
25,
13,
17,
69,
92,
4458,
18982,
7,
22462,
62,
27231,
13,
615,
70,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1188,
62,
22462,
796,
2994,
62,
27231,
13,
615,
70,
198,
220,
220,
220,
220,
220,
220,
220,
256,
13,
13564,
7,
20147,
1343,
705,
930,
4938,
2994,
46110,
17,
13,
17,
69,
92,
930,
4938,
279,
489,
46110,
18,
13,
17,
69,
92,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
764,
18982,
7,
2100,
62,
22462,
11,
10688,
13,
79,
322,
7,
17,
11,
1188,
62,
22462,
22305,
628,
220,
220,
220,
1303,
4296,
290,
1441,
262,
4673,
2494,
198,
220,
220,
220,
1441,
1188,
62,
22462,
628,
198,
4299,
4776,
62,
9288,
7,
22046,
11,
2746,
11,
27039,
11,
24637,
11,
15584,
11,
269,
15339,
62,
25202,
2599,
198,
220,
220,
220,
37227,
36,
2100,
4985,
262,
2746,
319,
262,
1332,
900,
290,
1441,
262,
347,
2538,
52,
30664,
526,
15931,
628,
220,
220,
220,
33417,
796,
45835,
8645,
1352,
26933,
19849,
4357,
27039,
13,
67,
301,
62,
11600,
11,
15584,
62,
7857,
28,
40045,
8,
198,
220,
220,
220,
611,
28034,
13,
66,
15339,
13,
271,
62,
15182,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
33417,
13,
66,
15339,
3419,
628,
220,
220,
220,
30664,
796,
7245,
84,
13,
3351,
11934,
7,
19608,
292,
316,
13,
67,
301,
62,
11600,
13,
15636,
22784,
27039,
13,
67,
301,
62,
11600,
13,
68,
418,
22784,
27039,
13,
67,
301,
62,
11600,
13,
2954,
28955,
198,
220,
220,
220,
340,
81,
796,
27039,
13,
67,
10254,
1170,
263,
7,
7266,
2617,
11,
15458,
62,
7857,
28,
19,
11,
3509,
62,
1930,
1756,
28,
22046,
13,
9806,
62,
1930,
1756,
8,
198,
220,
220,
220,
329,
4808,
11,
4808,
11,
1006,
11,
2537,
1930,
287,
33417,
13,
8612,
378,
62,
8664,
1740,
62,
270,
81,
7,
270,
81,
11,
269,
15339,
62,
25202,
28,
66,
15339,
62,
25202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
30664,
13,
2860,
7,
5420,
13,
600,
22446,
36166,
22784,
2537,
1930,
58,
15,
7131,
6,
83,
482,
641,
6,
4083,
600,
22446,
36166,
28955,
198,
220,
220,
220,
1441,
30664,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.104292 | 2,493 |
#!/usr/bin/env python
"""
This parses a log file series (i.e. log, log.1, log.2, etc..) and
outputs timing and call frequency information for HAL messages.
Hazen 5/18
"""
from datetime import datetime
import os
pattern = '%Y-%m-%d %H:%M:%S,%f'
def getIterable(dict_or_list):
"""
Returns an iterable given a dictionary of a list.
"""
if isinstance(dict_or_list, dict):
iterable = list(dict_or_list.values())
elif isinstance(dict_or_list, list):
iterable = dict_or_list
else:
raise Exception("Unknown type '" + str(type(dict_or_list)) + "'")
return iterable
def groupByMsgType(messages):
"""
Returns a dictionary keyed by message type, with a list of one or
more message objects per message type.
"""
return groupByX(lambda x : x.getType(),
messages)
def groupBySource(messages):
"""
Returns a dictionary keyed by message source, with a list of one or
more message objects per message source.
"""
return groupByX(lambda x : x.getSource(),
messages)
def groupByX(grp_fn, messages):
"""
Returns a dictionary keyed by the requested group.
"""
m_grp = {}
for msg in getIterable(messages):
# Ignore messages that we don't have all the timing for.
if msg.isComplete() or not ignore_incomplete:
m_type = grp_fn(msg)
if m_type in m_grp:
m_grp[m_type].append(msg)
else:
m_grp[m_type] = [msg]
return m_grp
def logTiming(basename, ignore_incomplete = False):
"""
Returns a dictionary of Message objects keyed by their ID number.
"""
zero_time = None
messages = {}
for ext in [".5", ".4", ".3", ".2", ".1", ""]:
fname = basename + ".out" + ext
if not os.path.exists(fname):
print(fname, "not found.")
continue
with open(fname) as fp:
for line in fp:
try:
[time, command] = map(lambda x: x.strip(), line.split(":hal4000:INFO:"))
except ValueError:
continue
if zero_time is None:
zero_time = time
# Message queued.
if (command.startswith("queued,")):
[m_id, source, m_type] = command.split(",")[1:]
messages[m_id] = Message(m_type = m_type,
source = source,
time = time,
zero_time = zero_time)
# Message sent.
elif (command.startswith("sent,")):
m_id = command.split(",")[1]
messages[m_id].sent(time)
# Message processed.
elif (command.startswith("processed,")):
m_id = command.split(",")[1]
messages[m_id].processed(time)
elif (command.startswith("worker done,")):
m_id = command.split(",")[1]
messages[m_id].incNWorkers()
# Ignore messages that we don't have all the timing for.
if not ignore_incomplete:
temp = {}
for m_id in messages:
msg = messages[m_id]
if msg.isComplete():
temp[m_id] = msg
return temp
else:
return messages
def processingTime(messages):
"""
Returns the total processing time for a collection of messages.
"""
accum_time = 0
for msg in getIterable(messages):
if isinstance(msg, list):
for elt in msg:
accum_time += elt.getProcessingTime()
else:
accum_time += msg.getProcessingTime()
return accum_time
def queuedTime(messages):
"""
Returns the total queued time for a a collection of messages.
"""
accum_time = 0
for msg in getIterable(messages):
if isinstance(msg, list):
for elt in msg:
accum_time += elt.getQueuedTime()
else:
accum_time += msg.getQueuedTime()
return accum_time
if (__name__ == "__main__"):
import sys
if (len(sys.argv) != 2):
print("usage: <log file>")
exit()
messages = logTiming(sys.argv[1])
groups = groupByMsgType(messages)
print()
print("All messages:")
for key in sorted(groups):
grp = groups[key]
print(key + ", {0:0d} counts, {1:.3f} seconds".format(len(grp), processingTime(grp)))
print("Total queued time {0:.3f} seconds".format(queuedTime(groups)))
print("Total processing time {0:.3f} seconds".format(processingTime(groups)))
print()
print("Film messages:")
groups = groupByMsgType(groupBySource(messages)["film"])
for key in sorted(groups):
grp = groups[key]
print(key + ", {0:0d} counts, {1:.3f} seconds".format(len(grp), processingTime(grp)))
print("Total processing time {0:.3f} seconds".format(processingTime(groups)))
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
37811,
198,
1212,
13544,
274,
257,
2604,
2393,
2168,
357,
72,
13,
68,
13,
2604,
11,
2604,
13,
16,
11,
2604,
13,
17,
11,
3503,
492,
8,
290,
198,
22915,
82,
10576,
290,
869,
8373,
1321,
329,
42968,
6218,
13,
198,
198,
39,
1031,
268,
642,
14,
1507,
198,
37811,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
11748,
28686,
628,
198,
33279,
796,
705,
4,
56,
12,
4,
76,
12,
4,
67,
4064,
39,
25,
4,
44,
25,
4,
50,
11,
4,
69,
6,
628,
198,
198,
4299,
651,
29993,
540,
7,
11600,
62,
273,
62,
4868,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
281,
11629,
540,
1813,
257,
22155,
286,
257,
1351,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
318,
39098,
7,
11600,
62,
273,
62,
4868,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
11629,
540,
796,
1351,
7,
11600,
62,
273,
62,
4868,
13,
27160,
28955,
198,
220,
220,
220,
1288,
361,
318,
39098,
7,
11600,
62,
273,
62,
4868,
11,
1351,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
11629,
540,
796,
8633,
62,
273,
62,
4868,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
20035,
2099,
705,
1,
1343,
965,
7,
4906,
7,
11600,
62,
273,
62,
4868,
4008,
1343,
24018,
4943,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1441,
11629,
540,
628,
198,
4299,
1448,
3886,
50108,
6030,
7,
37348,
1095,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
257,
22155,
1994,
276,
416,
3275,
2099,
11,
351,
257,
1351,
286,
530,
393,
198,
220,
220,
220,
517,
3275,
5563,
583,
3275,
2099,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
1448,
3886,
55,
7,
50033,
2124,
1058,
2124,
13,
1136,
6030,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
8,
628,
198,
4299,
1448,
3886,
7416,
7,
37348,
1095,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
257,
22155,
1994,
276,
416,
3275,
2723,
11,
351,
257,
1351,
286,
530,
393,
198,
220,
220,
220,
517,
3275,
5563,
583,
3275,
2723,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
1448,
3886,
55,
7,
50033,
2124,
1058,
2124,
13,
1136,
7416,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
8,
628,
198,
4299,
1448,
3886,
55,
7,
2164,
79,
62,
22184,
11,
6218,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
257,
22155,
1994,
276,
416,
262,
9167,
1448,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
285,
62,
2164,
79,
796,
23884,
198,
220,
220,
220,
220,
198,
220,
220,
220,
329,
31456,
287,
651,
29993,
540,
7,
37348,
1095,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
41032,
6218,
326,
356,
836,
470,
423,
477,
262,
10576,
329,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
31456,
13,
271,
20988,
3419,
393,
407,
8856,
62,
259,
20751,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
4906,
796,
1036,
79,
62,
22184,
7,
19662,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
285,
62,
4906,
287,
285,
62,
2164,
79,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
2164,
79,
58,
76,
62,
4906,
4083,
33295,
7,
19662,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
2164,
79,
58,
76,
62,
4906,
60,
796,
685,
19662,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1441,
285,
62,
2164,
79,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
198,
4299,
2604,
14967,
278,
7,
12093,
12453,
11,
8856,
62,
259,
20751,
796,
10352,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
257,
22155,
286,
16000,
5563,
1994,
276,
416,
511,
4522,
1271,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6632,
62,
2435,
796,
6045,
198,
220,
220,
220,
6218,
796,
23884,
628,
220,
220,
220,
329,
1070,
287,
685,
1911,
20,
1600,
27071,
19,
1600,
27071,
18,
1600,
27071,
17,
1600,
27071,
16,
1600,
13538,
5974,
628,
220,
220,
220,
220,
220,
220,
220,
277,
3672,
796,
1615,
12453,
1343,
27071,
448,
1,
1343,
1070,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
69,
3672,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
3672,
11,
366,
1662,
1043,
19570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
69,
3672,
8,
355,
277,
79,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1627,
287,
277,
79,
25,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
2435,
11,
3141,
60,
796,
3975,
7,
50033,
2124,
25,
2124,
13,
36311,
22784,
1627,
13,
35312,
7,
1298,
14201,
27559,
25,
10778,
11097,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
11052,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6632,
62,
2435,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6632,
62,
2435,
796,
640,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
16000,
8358,
1739,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
21812,
13,
9688,
2032,
342,
7203,
4188,
1739,
553,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
76,
62,
312,
11,
2723,
11,
285,
62,
4906,
60,
796,
3141,
13,
35312,
7,
2430,
38381,
16,
47715,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
58,
76,
62,
312,
60,
796,
16000,
7,
76,
62,
4906,
796,
285,
62,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
796,
2723,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
796,
640,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6632,
62,
2435,
796,
6632,
62,
2435,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
16000,
1908,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
357,
21812,
13,
9688,
2032,
342,
7203,
34086,
553,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
312,
796,
3141,
13,
35312,
7,
2430,
38381,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
58,
76,
62,
312,
4083,
34086,
7,
2435,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
16000,
13686,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
357,
21812,
13,
9688,
2032,
342,
7203,
14681,
276,
553,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
312,
796,
3141,
13,
35312,
7,
2430,
38381,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
58,
76,
62,
312,
4083,
14681,
276,
7,
2435,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
357,
21812,
13,
9688,
2032,
342,
7203,
28816,
1760,
553,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
62,
312,
796,
3141,
13,
35312,
7,
2430,
38381,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6218,
58,
76,
62,
312,
4083,
1939,
45,
12468,
364,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
41032,
6218,
326,
356,
836,
470,
423,
477,
262,
10576,
329,
13,
198,
220,
220,
220,
611,
407,
8856,
62,
259,
20751,
25,
198,
220,
220,
220,
220,
220,
220,
220,
20218,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
329,
285,
62,
312,
287,
6218,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
796,
6218,
58,
76,
62,
312,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
31456,
13,
271,
20988,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
58,
76,
62,
312,
60,
796,
31456,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
20218,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6218,
628,
198,
4299,
7587,
7575,
7,
37348,
1095,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
262,
2472,
7587,
640,
329,
257,
4947,
286,
6218,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10507,
62,
2435,
796,
657,
198,
220,
220,
220,
329,
31456,
287,
651,
29993,
540,
7,
37348,
1095,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
19662,
11,
1351,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1288,
83,
287,
31456,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10507,
62,
2435,
15853,
1288,
83,
13,
1136,
18709,
278,
7575,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10507,
62,
2435,
15853,
31456,
13,
1136,
18709,
278,
7575,
3419,
198,
220,
220,
220,
1441,
10507,
62,
2435,
628,
198,
4299,
8358,
1739,
7575,
7,
37348,
1095,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
16409,
262,
2472,
8358,
1739,
640,
329,
257,
257,
4947,
286,
6218,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10507,
62,
2435,
796,
657,
198,
220,
220,
220,
329,
31456,
287,
651,
29993,
540,
7,
37348,
1095,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
19662,
11,
1351,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1288,
83,
287,
31456,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10507,
62,
2435,
15853,
1288,
83,
13,
1136,
15681,
1739,
7575,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10507,
62,
2435,
15853,
31456,
13,
1136,
15681,
1739,
7575,
3419,
198,
220,
220,
220,
1441,
10507,
62,
2435,
628,
198,
361,
357,
834,
3672,
834,
6624,
366,
834,
12417,
834,
1,
2599,
628,
220,
220,
220,
1330,
25064,
198,
220,
220,
220,
220,
198,
220,
220,
220,
611,
357,
11925,
7,
17597,
13,
853,
85,
8,
14512,
362,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
26060,
25,
1279,
6404,
2393,
29,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
8420,
3419,
628,
220,
220,
220,
6218,
796,
2604,
14967,
278,
7,
17597,
13,
853,
85,
58,
16,
12962,
198,
220,
220,
220,
2628,
796,
1448,
3886,
50108,
6030,
7,
37348,
1095,
8,
628,
220,
220,
220,
3601,
3419,
198,
220,
220,
220,
3601,
7203,
3237,
6218,
25,
4943,
198,
220,
220,
220,
329,
1994,
287,
23243,
7,
24432,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1036,
79,
796,
2628,
58,
2539,
60,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
2539,
1343,
33172,
1391,
15,
25,
15,
67,
92,
9853,
11,
1391,
16,
25,
13,
18,
69,
92,
4201,
1911,
18982,
7,
11925,
7,
2164,
79,
828,
7587,
7575,
7,
2164,
79,
22305,
198,
220,
220,
220,
3601,
7203,
14957,
8358,
1739,
640,
1391,
15,
25,
13,
18,
69,
92,
4201,
1911,
18982,
7,
4188,
1739,
7575,
7,
24432,
22305,
198,
220,
220,
220,
3601,
7203,
14957,
7587,
640,
1391,
15,
25,
13,
18,
69,
92,
4201,
1911,
18982,
7,
36948,
7575,
7,
24432,
22305,
628,
220,
220,
220,
3601,
3419,
198,
220,
220,
220,
3601,
7203,
39750,
6218,
25,
4943,
198,
220,
220,
220,
2628,
796,
1448,
3886,
50108,
6030,
7,
8094,
3886,
7416,
7,
37348,
1095,
8,
14692,
26240,
8973,
8,
198,
220,
220,
220,
329,
1994,
287,
23243,
7,
24432,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1036,
79,
796,
2628,
58,
2539,
60,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
2539,
1343,
33172,
1391,
15,
25,
15,
67,
92,
9853,
11,
1391,
16,
25,
13,
18,
69,
92,
4201,
1911,
18982,
7,
11925,
7,
2164,
79,
828,
7587,
7575,
7,
2164,
79,
22305,
198,
220,
220,
220,
3601,
7203,
14957,
7587,
640,
1391,
15,
25,
13,
18,
69,
92,
4201,
1911,
18982,
7,
36948,
7575,
7,
24432,
22305,
628,
628
] | 2.05309 | 2,524 |
from django.core.management.base import BaseCommand
from django.utils import termcolors
from jsonschema import Draft4Validator
from jsonschema.exceptions import SchemaError
import json
| [
6738,
42625,
14208,
13,
7295,
13,
27604,
13,
8692,
1330,
7308,
21575,
198,
6738,
42625,
14208,
13,
26791,
1330,
3381,
4033,
669,
198,
6738,
44804,
684,
2395,
2611,
1330,
13650,
19,
47139,
1352,
198,
6738,
44804,
684,
2395,
2611,
13,
1069,
11755,
1330,
10011,
2611,
12331,
198,
11748,
33918,
628
] | 3.72 | 50 |
import cv2, time
import numpy as np
import Tkinter
"""
Wraps up some interfaces to opencv user interface methods (displaying
image frames, event handling, etc).
If desired, an alternative UI could be built and imported into get_pulse.py
instead. Opencv is used to perform much of the data analysis, but there is no
reason it has to be used to handle the UI as well. It just happens to be very
effective for our purposes.
"""
"""
The rest of this file defines some GUI plotting functionality. There are plenty
of other ways to do simple x-y data plots in python, but this application uses
cv2.imshow to do real-time data plotting and handle user interaction.
This is entirely independent of the data calculation functions, so it can be
replaced in the get_pulse.py application easily.
"""
def combine(left, right):
"""Stack images horizontally.
"""
h = max(left.shape[0], right.shape[0])
w = left.shape[1] + right.shape[1]
hoff = left.shape[0]
shape = list(left.shape)
shape[0] = h
shape[1] = w
comb = np.zeros(tuple(shape),left.dtype)
# left will be on left, aligned top, with right on right
comb[:left.shape[0],:left.shape[1]] = left
comb[:right.shape[0],left.shape[1]:] = right
return comb
| [
11748,
269,
85,
17,
11,
640,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
309,
74,
3849,
198,
198,
37811,
198,
36918,
862,
510,
617,
20314,
284,
1280,
33967,
2836,
7071,
5050,
357,
13812,
278,
198,
9060,
13431,
11,
1785,
9041,
11,
3503,
737,
198,
198,
1532,
10348,
11,
281,
5559,
12454,
714,
307,
3170,
290,
17392,
656,
651,
62,
79,
9615,
13,
9078,
220,
198,
38070,
13,
4946,
33967,
318,
973,
284,
1620,
881,
286,
262,
1366,
3781,
11,
475,
612,
318,
645,
198,
41181,
340,
468,
284,
307,
973,
284,
5412,
262,
12454,
355,
880,
13,
632,
655,
4325,
284,
307,
845,
198,
16803,
329,
674,
4959,
13,
198,
37811,
628,
198,
37811,
198,
464,
1334,
286,
428,
2393,
15738,
617,
25757,
29353,
11244,
13,
1318,
389,
6088,
198,
1659,
584,
2842,
284,
466,
2829,
2124,
12,
88,
1366,
21528,
287,
21015,
11,
475,
428,
3586,
3544,
220,
198,
33967,
17,
13,
320,
12860,
284,
466,
1103,
12,
2435,
1366,
29353,
290,
5412,
2836,
10375,
13,
198,
198,
1212,
318,
5000,
4795,
286,
262,
1366,
17952,
5499,
11,
523,
340,
460,
307,
220,
198,
260,
21820,
287,
262,
651,
62,
79,
9615,
13,
9078,
3586,
3538,
13,
198,
37811,
628,
198,
4299,
12082,
7,
9464,
11,
826,
2599,
198,
220,
220,
220,
37227,
25896,
4263,
36774,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
289,
796,
3509,
7,
9464,
13,
43358,
58,
15,
4357,
826,
13,
43358,
58,
15,
12962,
198,
220,
220,
220,
266,
796,
1364,
13,
43358,
58,
16,
60,
1343,
826,
13,
43358,
58,
16,
60,
198,
220,
220,
220,
289,
2364,
796,
1364,
13,
43358,
58,
15,
60,
198,
220,
220,
220,
220,
198,
220,
220,
220,
5485,
796,
1351,
7,
9464,
13,
43358,
8,
198,
220,
220,
220,
5485,
58,
15,
60,
796,
289,
198,
220,
220,
220,
5485,
58,
16,
60,
796,
266,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1974,
796,
45941,
13,
9107,
418,
7,
83,
29291,
7,
43358,
828,
9464,
13,
67,
4906,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
1364,
481,
307,
319,
1364,
11,
19874,
1353,
11,
351,
826,
319,
826,
198,
220,
220,
220,
1974,
58,
25,
9464,
13,
43358,
58,
15,
4357,
25,
9464,
13,
43358,
58,
16,
11907,
796,
1364,
198,
220,
220,
220,
1974,
58,
25,
3506,
13,
43358,
58,
15,
4357,
9464,
13,
43358,
58,
16,
5974,
60,
796,
826,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1441,
1974,
220,
220,
220,
198
] | 3.033254 | 421 |
# -*- coding: utf-8 -*-
# Natural Language Toolkit: Transformation-based learning
#
# Copyright (C) 2001-2018 NLTK Project
# Author: Marcus Uneson <marcus.uneson@gmail.com>
# based on previous (nltk2) version by
# Christopher Maloof, Edward Loper, Steven Bird
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
from __future__ import print_function, division
from collections import defaultdict, Counter
from nltk.tag import TaggerI
from nltk.tbl import Feature, Template
from nltk import jsontags
######################################################################
# Brill Templates
######################################################################
def nltkdemo18():
"""
Return 18 templates, from the original nltk demo, in multi-feature syntax
"""
return [
Template(Pos([-1])),
Template(Pos([1])),
Template(Pos([-2])),
Template(Pos([2])),
Template(Pos([-2, -1])),
Template(Pos([1, 2])),
Template(Pos([-3, -2, -1])),
Template(Pos([1, 2, 3])),
Template(Pos([-1]), Pos([1])),
Template(Word([-1])),
Template(Word([1])),
Template(Word([-2])),
Template(Word([2])),
Template(Word([-2, -1])),
Template(Word([1, 2])),
Template(Word([-3, -2, -1])),
Template(Word([1, 2, 3])),
Template(Word([-1]), Word([1])),
]
def nltkdemo18plus():
"""
Return 18 templates, from the original nltk demo, and additionally a few
multi-feature ones (the motivation is easy comparison with nltkdemo18)
"""
return nltkdemo18() + [
Template(Word([-1]), Pos([1])),
Template(Pos([-1]), Word([1])),
Template(Word([-1]), Word([0]), Pos([1])),
Template(Pos([-1]), Word([0]), Word([1])),
Template(Pos([-1]), Word([0]), Pos([1])),
]
def fntbl37():
"""
Return 37 templates taken from the postagging task of the
fntbl distribution http://www.cs.jhu.edu/~rflorian/fntbl/
(37 is after excluding a handful which do not condition on Pos[0];
fntbl can do that but the current nltk implementation cannot.)
"""
return [
Template(Word([0]), Word([1]), Word([2])),
Template(Word([-1]), Word([0]), Word([1])),
Template(Word([0]), Word([-1])),
Template(Word([0]), Word([1])),
Template(Word([0]), Word([2])),
Template(Word([0]), Word([-2])),
Template(Word([1, 2])),
Template(Word([-2, -1])),
Template(Word([1, 2, 3])),
Template(Word([-3, -2, -1])),
Template(Word([0]), Pos([2])),
Template(Word([0]), Pos([-2])),
Template(Word([0]), Pos([1])),
Template(Word([0]), Pos([-1])),
Template(Word([0])),
Template(Word([-2])),
Template(Word([2])),
Template(Word([1])),
Template(Word([-1])),
Template(Pos([-1]), Pos([1])),
Template(Pos([1]), Pos([2])),
Template(Pos([-1]), Pos([-2])),
Template(Pos([1])),
Template(Pos([-1])),
Template(Pos([-2])),
Template(Pos([2])),
Template(Pos([1, 2, 3])),
Template(Pos([1, 2])),
Template(Pos([-3, -2, -1])),
Template(Pos([-2, -1])),
Template(Pos([1]), Word([0]), Word([1])),
Template(Pos([1]), Word([0]), Word([-1])),
Template(Pos([-1]), Word([-1]), Word([0])),
Template(Pos([-1]), Word([0]), Word([1])),
Template(Pos([-2]), Pos([-1])),
Template(Pos([1]), Pos([2])),
Template(Pos([1]), Pos([2]), Word([1]))
]
def brill24():
"""
Return 24 templates of the seminal TBL paper, Brill (1995)
"""
return [
Template(Pos([-1])),
Template(Pos([1])),
Template(Pos([-2])),
Template(Pos([2])),
Template(Pos([-2, -1])),
Template(Pos([1, 2])),
Template(Pos([-3, -2, -1])),
Template(Pos([1, 2, 3])),
Template(Pos([-1]), Pos([1])),
Template(Pos([-2]), Pos([-1])),
Template(Pos([1]), Pos([2])),
Template(Word([-1])),
Template(Word([1])),
Template(Word([-2])),
Template(Word([2])),
Template(Word([-2, -1])),
Template(Word([1, 2])),
Template(Word([-1, 0])),
Template(Word([0, 1])),
Template(Word([0])),
Template(Word([-1]), Pos([-1])),
Template(Word([1]), Pos([1])),
Template(Word([0]), Word([-1]), Pos([-1])),
Template(Word([0]), Word([1]), Pos([1])),
]
def describe_template_sets():
"""
Print the available template sets in this demo, with a short description"
"""
import inspect
import sys
# a bit of magic to get all functions in this module
templatesets = inspect.getmembers(sys.modules[__name__], inspect.isfunction)
for (name, obj) in templatesets:
if name == "describe_template_sets":
continue
print(name, obj.__doc__, "\n")
######################################################################
# The Brill Tagger
######################################################################
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
12068,
15417,
16984,
15813,
25,
49127,
12,
3106,
4673,
198,
2,
198,
2,
15069,
357,
34,
8,
5878,
12,
7908,
22879,
51,
42,
4935,
198,
2,
6434,
25,
17068,
791,
42038,
1279,
3876,
9042,
13,
4015,
261,
31,
14816,
13,
785,
29,
198,
2,
220,
220,
1912,
319,
2180,
357,
77,
2528,
74,
17,
8,
2196,
416,
198,
2,
220,
220,
12803,
4434,
37711,
11,
10443,
406,
3575,
11,
8239,
14506,
198,
2,
10289,
25,
1279,
4023,
1378,
77,
2528,
74,
13,
2398,
15913,
198,
2,
1114,
5964,
1321,
11,
766,
220,
38559,
24290,
13,
51,
25010,
198,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
11,
7297,
198,
198,
6738,
17268,
1330,
4277,
11600,
11,
15034,
198,
198,
6738,
299,
2528,
74,
13,
12985,
1330,
309,
7928,
40,
198,
6738,
299,
2528,
74,
13,
83,
2436,
1330,
27018,
11,
37350,
198,
6738,
299,
2528,
74,
1330,
44804,
756,
3775,
628,
198,
29113,
29113,
4242,
2235,
198,
2,
33335,
5825,
17041,
198,
29113,
29113,
4242,
2235,
628,
198,
198,
4299,
299,
2528,
74,
9536,
78,
1507,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
1248,
24019,
11,
422,
262,
2656,
299,
2528,
74,
13605,
11,
287,
5021,
12,
30053,
15582,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
685,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
18,
11,
532,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
11,
513,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
18,
11,
532,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
11,
362,
11,
513,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
2361,
628,
198,
4299,
299,
2528,
74,
9536,
78,
1507,
9541,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
1248,
24019,
11,
422,
262,
2656,
299,
2528,
74,
13605,
11,
290,
36527,
257,
1178,
198,
220,
220,
220,
5021,
12,
30053,
3392,
357,
1169,
14052,
318,
2562,
7208,
351,
299,
2528,
74,
9536,
78,
1507,
8,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
299,
2528,
74,
9536,
78,
1507,
3419,
1343,
685,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
46570,
9678,
26933,
15,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
9678,
26933,
15,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
9678,
26933,
15,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
2361,
628,
198,
4299,
277,
429,
2436,
2718,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
5214,
24019,
2077,
422,
262,
1281,
16406,
4876,
286,
262,
198,
220,
220,
220,
277,
429,
2436,
6082,
2638,
1378,
2503,
13,
6359,
13,
73,
13415,
13,
15532,
14,
93,
81,
2704,
22618,
14,
69,
429,
2436,
14,
198,
220,
220,
220,
357,
2718,
318,
706,
23494,
257,
10089,
543,
466,
407,
4006,
319,
18574,
58,
15,
11208,
198,
220,
220,
220,
277,
429,
2436,
460,
466,
326,
475,
262,
1459,
299,
2528,
74,
7822,
2314,
2014,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
685,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
16,
46570,
9678,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
46570,
9678,
26933,
15,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
11,
362,
11,
513,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
18,
11,
532,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
18574,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
18574,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
18574,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
18574,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
18574,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
11,
513,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
18,
11,
532,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
9678,
26933,
15,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
9678,
26933,
15,
46570,
9678,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
9678,
26933,
12,
16,
46570,
9678,
26933,
15,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
9678,
26933,
15,
46570,
9678,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
46570,
18574,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
18574,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
18574,
26933,
17,
46570,
9678,
26933,
16,
60,
4008,
198,
220,
220,
220,
2361,
628,
198,
4299,
9547,
1731,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8229,
1987,
24019,
286,
262,
38915,
309,
9148,
3348,
11,
33335,
357,
21908,
8,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
685,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
18,
11,
532,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
11,
362,
11,
513,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
12,
17,
46570,
18574,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
21604,
26933,
16,
46570,
18574,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
17,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
17,
11,
532,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
11,
362,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
11,
657,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
11,
352,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
12,
16,
46570,
18574,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
12,
16,
46570,
18574,
26933,
12,
16,
12962,
828,
198,
220,
220,
220,
220,
220,
220,
220,
37350,
7,
26449,
26933,
15,
46570,
9678,
26933,
16,
46570,
18574,
26933,
16,
12962,
828,
198,
220,
220,
220,
2361,
628,
198,
4299,
6901,
62,
28243,
62,
28709,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
12578,
262,
1695,
11055,
5621,
287,
428,
13605,
11,
351,
257,
1790,
6764,
1,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1330,
10104,
198,
220,
220,
220,
1330,
25064,
628,
220,
220,
220,
1303,
257,
1643,
286,
5536,
284,
651,
477,
5499,
287,
428,
8265,
198,
220,
220,
220,
24019,
1039,
796,
10104,
13,
1136,
30814,
7,
17597,
13,
18170,
58,
834,
3672,
834,
4357,
10104,
13,
4468,
4575,
8,
198,
220,
220,
220,
329,
357,
3672,
11,
26181,
8,
287,
24019,
1039,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6624,
366,
20147,
4892,
62,
28243,
62,
28709,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
3672,
11,
26181,
13,
834,
15390,
834,
11,
37082,
77,
4943,
628,
198,
29113,
29113,
4242,
2235,
198,
2,
383,
33335,
309,
7928,
198,
29113,
29113,
4242,
2235,
198
] | 2.301616 | 2,228 |
import json
import logging
import sys
import numpy as np
import torch
from task_config import SuperGLUE_LABEL_MAPPING
from snorkel.mtl.data import MultitaskDataset
sys.path.append("..") # Adds higher directory to python modules path.
logger = logging.getLogger(__name__)
TASK_NAME = "WSC"
| [
11748,
33918,
198,
11748,
18931,
198,
11748,
25064,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
6738,
4876,
62,
11250,
1330,
3115,
8763,
8924,
62,
48780,
3698,
62,
44,
24805,
2751,
198,
198,
6738,
3013,
273,
7750,
13,
16762,
75,
13,
7890,
1330,
7854,
270,
2093,
27354,
292,
316,
198,
198,
17597,
13,
6978,
13,
33295,
7203,
492,
4943,
220,
1303,
34333,
2440,
8619,
284,
21015,
13103,
3108,
13,
628,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
198,
198,
51,
1921,
42,
62,
20608,
796,
366,
54,
6173,
1,
628,
198
] | 2.950495 | 101 |
import re
import json
__all__ = ["Simplimental"]
| [
11748,
302,
198,
11748,
33918,
198,
198,
834,
439,
834,
796,
14631,
8890,
489,
9134,
8973,
198
] | 2.941176 | 17 |
# This example shows how to read or modify the Axes Optimization settings using the RoboDK API and a JSON string.
# You can select "Axes optimization" in a robot machining menu or the robot parameters to view the axes optimization settings.
# It is possible to update the axes optimization settings attached to a robot or a robot machining project manually or using the API.
#
# More information about the RoboDK API here:
# https://robodk.com/doc/en/RoboDK-API.html
# For more information visit:
# https://robodk.com/doc/en/PythonAPI/robolink.html
from robolink import * # RoboDK API
# JSON tools
import json
# Start the RoboDK API
RDK = Robolink()
# Ask the user to select a robot arm (6 axis robot wich can have external axes)
robot = RDK.ItemUserPick("Select a robot arm",ITEM_TYPE_ROBOT_ARM)
# Default optimization settings test template
AxesOptimSettings = {
# Optimization parameters:
"Active": 1, # Use generic axes optimization: 0=Disabled or 1=Enabled
"Algorithm": 2, # Optimization algorithm to use: 1=Nelder Mead, 2=Samples, 3=Samples+Nelder Mead
"MaxIter": 650, # Max. number of iterations
"Tol": 0.0016, # Tolerance to stop iterations
# Absolute Reference joints (double):
"AbsJnt_1": 104.17,
"AbsJnt_2": 11.22,
"AbsJnt_3": 15.97,
"AbsJnt_4": -87.48,
"AbsJnt_5": -75.36,
"AbsJnt_6": 63.03,
"AbsJnt_7": 174.13,
"AbsJnt_8": 173.60,
"AbsJnt_9": 0,
# Using Absolute reference joints (0: No, 1: Yes):
"AbsOn_1": 1,
"AbsOn_2": 1,
"AbsOn_3": 1,
"AbsOn_4": 1,
"AbsOn_5": 1,
"AbsOn_6": 1,
"AbsOn_7": 1,
"AbsOn_8": 1,
"AbsOn_9": 1,
# Weight for absolute reference joints (double):
"AbsW_1": 100,
"AbsW_2": 100,
"AbsW_3": 100,
"AbsW_4": 89,
"AbsW_5": 90,
"AbsW_6": 92,
"AbsW_7": 92,
"AbsW_8": 96,
"AbsW_9": 50,
# Using for relative joint motion smoothing (0: No, 1: Yes):
"RelOn_1": 1,
"RelOn_2": 1,
"RelOn_3": 1,
"RelOn_4": 1,
"RelOn_5": 1,
"RelOn_6": 1,
"RelOn_7": 1,
"RelOn_8": 1,
"RelOn_9": 1,
# Weight for relative joint motion (double):
"RelW_1": 5,
"RelW_2": 47,
"RelW_3": 44,
"RelW_4": 43,
"RelW_5": 36,
"RelW_6": 47,
"RelW_7": 53,
"RelW_8": 59,
"RelW_9": 0,
}
# Update one value, for example, make it active:
ToUpdate = {}
ToUpdate["Active"] = 1
json_str = json.dumps(json.dumps(ToUpdate))
status = robot.setParam("OptimAxes", json_str)
print(status)
# Example to make a partial or full update
count = 1
while True:
for i in range(7):
# Partial update
ToUpdate = {}
ToUpdate["AbsJnt_" + str(i+1)] = (count+i)*4
ToUpdate["AbsOn_" + str(i+1)] = count % 2
ToUpdate["AbsW_" + str(i+1)] = (count+i)
json_str = json.dumps(json.dumps(ToUpdate))
status = robot.setParam("OptimAxes", json_str)
print(status)
# Full update
#OptimAxes_TEST["RefJoint_" + str(i+1)] = (count+i)*4
#OptimAxes_TEST["RefWeight_" + str(i+1)] = (count+i)
#OptimAxes_TEST["RefOn_" + str(i+1)] = count % 2
# Full update
#print(robot.setParam("OptimAxes", str(AxesOptimSettings)))
count = count + 1
# Read settings
json_data = robot.setParam("OptimAxes")
json_object = json.loads(json_data)
print(json.dumps(json_object, indent=4))
pause(0.2)
# Example to read the current axes optimization settings:
while True:
json_data = robot.setParam("OptimAxes")
json_object = json.loads(json_data)
print(json.dumps(json_object, indent=4))
pause(0.2)
| [
2,
770,
1672,
2523,
703,
284,
1100,
393,
13096,
262,
12176,
274,
30011,
1634,
6460,
1262,
262,
39702,
48510,
7824,
290,
257,
19449,
4731,
13,
198,
2,
921,
460,
2922,
366,
31554,
274,
23989,
1,
287,
257,
9379,
3235,
3191,
6859,
393,
262,
9379,
10007,
284,
1570,
262,
34197,
23989,
6460,
13,
198,
2,
632,
318,
1744,
284,
4296,
262,
34197,
23989,
6460,
7223,
284,
257,
9379,
393,
257,
9379,
3235,
3191,
1628,
14500,
393,
1262,
262,
7824,
13,
198,
2,
198,
2,
3125,
1321,
546,
262,
39702,
48510,
7824,
994,
25,
198,
2,
3740,
1378,
22609,
375,
74,
13,
785,
14,
15390,
14,
268,
14,
14350,
78,
48510,
12,
17614,
13,
6494,
198,
2,
1114,
517,
1321,
3187,
25,
198,
2,
3740,
1378,
22609,
375,
74,
13,
785,
14,
15390,
14,
268,
14,
37906,
17614,
14,
22609,
349,
676,
13,
6494,
198,
198,
6738,
3857,
349,
676,
1330,
1635,
220,
220,
220,
1303,
39702,
48510,
7824,
198,
198,
2,
19449,
4899,
198,
11748,
33918,
198,
198,
2,
7253,
262,
39702,
48510,
7824,
198,
35257,
42,
796,
3851,
349,
676,
3419,
198,
198,
2,
16981,
262,
2836,
284,
2922,
257,
9379,
3211,
357,
21,
16488,
9379,
266,
488,
460,
423,
7097,
34197,
8,
198,
305,
13645,
796,
31475,
42,
13,
7449,
12982,
31686,
7203,
17563,
257,
9379,
3211,
1600,
2043,
3620,
62,
25216,
62,
49,
9864,
2394,
62,
33456,
8,
198,
198,
2,
15161,
23989,
6460,
1332,
11055,
198,
31554,
274,
27871,
320,
26232,
796,
1391,
198,
220,
220,
220,
1303,
30011,
1634,
10007,
25,
198,
220,
220,
220,
366,
13739,
1298,
352,
11,
1303,
5765,
14276,
34197,
23989,
25,
657,
28,
7279,
4510,
393,
352,
28,
20491,
198,
220,
220,
220,
366,
2348,
42289,
1298,
362,
11,
1303,
30011,
1634,
11862,
284,
779,
25,
352,
28,
8199,
6499,
21910,
11,
362,
28,
50,
12629,
11,
513,
28,
50,
12629,
10,
8199,
6499,
21910,
198,
220,
220,
220,
366,
11518,
29993,
1298,
22626,
11,
1303,
5436,
13,
1271,
286,
34820,
198,
220,
220,
220,
366,
51,
349,
1298,
657,
13,
405,
1433,
11,
1303,
309,
37668,
284,
2245,
34820,
628,
220,
220,
220,
1303,
36532,
20984,
24039,
357,
23352,
2599,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
16,
1298,
14436,
13,
1558,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
17,
1298,
1367,
13,
1828,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
18,
1298,
1315,
13,
5607,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
19,
1298,
532,
5774,
13,
2780,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
20,
1298,
532,
2425,
13,
2623,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
21,
1298,
8093,
13,
3070,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
22,
1298,
27621,
13,
1485,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
23,
1298,
28174,
13,
1899,
11,
198,
220,
220,
220,
366,
24849,
41,
429,
62,
24,
1298,
657,
11,
628,
220,
220,
220,
1303,
8554,
36532,
4941,
24039,
357,
15,
25,
1400,
11,
352,
25,
3363,
2599,
198,
220,
220,
220,
366,
24849,
2202,
62,
16,
1298,
352,
11,
220,
198,
220,
220,
220,
366,
24849,
2202,
62,
17,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
18,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
19,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
20,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
21,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
22,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
23,
1298,
352,
11,
198,
220,
220,
220,
366,
24849,
2202,
62,
24,
1298,
352,
11,
628,
220,
220,
220,
1303,
14331,
329,
4112,
4941,
24039,
357,
23352,
2599,
198,
220,
220,
220,
366,
24849,
54,
62,
16,
1298,
1802,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
17,
1298,
1802,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
18,
1298,
1802,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
19,
1298,
9919,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
20,
1298,
4101,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
21,
1298,
10190,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
22,
1298,
10190,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
23,
1298,
9907,
11,
198,
220,
220,
220,
366,
24849,
54,
62,
24,
1298,
2026,
11,
628,
220,
220,
220,
1303,
8554,
329,
3585,
6466,
6268,
32746,
722,
357,
15,
25,
1400,
11,
352,
25,
3363,
2599,
198,
220,
220,
220,
366,
6892,
2202,
62,
16,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
17,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
18,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
19,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
20,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
21,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
22,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
23,
1298,
352,
11,
198,
220,
220,
220,
366,
6892,
2202,
62,
24,
1298,
352,
11,
628,
220,
220,
220,
1303,
14331,
329,
3585,
6466,
6268,
357,
23352,
2599,
198,
220,
220,
220,
366,
6892,
54,
62,
16,
1298,
642,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
17,
1298,
6298,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
18,
1298,
5846,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
19,
1298,
5946,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
20,
1298,
4570,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
21,
1298,
6298,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
22,
1298,
7192,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
23,
1298,
7863,
11,
198,
220,
220,
220,
366,
6892,
54,
62,
24,
1298,
657,
11,
198,
92,
198,
198,
2,
10133,
530,
1988,
11,
329,
1672,
11,
787,
340,
4075,
25,
198,
2514,
10260,
796,
23884,
198,
2514,
10260,
14692,
13739,
8973,
796,
352,
198,
17752,
62,
2536,
796,
33918,
13,
67,
8142,
7,
17752,
13,
67,
8142,
7,
2514,
10260,
4008,
198,
13376,
796,
9379,
13,
2617,
22973,
7203,
27871,
320,
31554,
274,
1600,
33918,
62,
2536,
8,
198,
4798,
7,
13376,
8,
198,
198,
2,
17934,
284,
787,
257,
13027,
393,
1336,
4296,
198,
9127,
796,
352,
198,
4514,
6407,
25,
220,
220,
220,
220,
198,
220,
220,
220,
329,
1312,
287,
2837,
7,
22,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
43689,
4296,
198,
220,
220,
220,
220,
220,
220,
220,
1675,
10260,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
1675,
10260,
14692,
24849,
41,
429,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
357,
9127,
10,
72,
27493,
19,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1675,
10260,
14692,
24849,
2202,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
954,
4064,
362,
198,
220,
220,
220,
220,
220,
220,
220,
1675,
10260,
14692,
24849,
54,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
357,
9127,
10,
72,
8,
628,
220,
220,
220,
220,
220,
220,
220,
33918,
62,
2536,
796,
33918,
13,
67,
8142,
7,
17752,
13,
67,
8142,
7,
2514,
10260,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
3722,
796,
9379,
13,
2617,
22973,
7203,
27871,
320,
31554,
274,
1600,
33918,
62,
2536,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
13376,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
6462,
4296,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
27871,
320,
31554,
274,
62,
51,
6465,
14692,
8134,
41,
1563,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
357,
9127,
10,
72,
27493,
19,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
27871,
320,
31554,
274,
62,
51,
6465,
14692,
8134,
25844,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
357,
9127,
10,
72,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
27871,
320,
31554,
274,
62,
51,
6465,
14692,
8134,
2202,
62,
1,
1343,
965,
7,
72,
10,
16,
15437,
796,
954,
4064,
362,
628,
220,
220,
220,
1303,
6462,
4296,
198,
220,
220,
220,
1303,
4798,
7,
305,
13645,
13,
2617,
22973,
7203,
27871,
320,
31554,
274,
1600,
965,
7,
31554,
274,
27871,
320,
26232,
22305,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
954,
796,
954,
1343,
352,
628,
220,
220,
220,
1303,
4149,
6460,
198,
220,
220,
220,
33918,
62,
7890,
796,
9379,
13,
2617,
22973,
7203,
27871,
320,
31554,
274,
4943,
198,
220,
220,
220,
33918,
62,
15252,
796,
33918,
13,
46030,
7,
17752,
62,
7890,
8,
198,
220,
220,
220,
3601,
7,
17752,
13,
67,
8142,
7,
17752,
62,
15252,
11,
33793,
28,
19,
4008,
198,
220,
220,
220,
14985,
7,
15,
13,
17,
8,
198,
220,
220,
220,
220,
198,
198,
2,
17934,
284,
1100,
262,
1459,
34197,
23989,
6460,
25,
198,
4514,
6407,
25,
198,
220,
220,
220,
33918,
62,
7890,
796,
9379,
13,
2617,
22973,
7203,
27871,
320,
31554,
274,
4943,
198,
220,
220,
220,
33918,
62,
15252,
796,
33918,
13,
46030,
7,
17752,
62,
7890,
8,
198,
220,
220,
220,
3601,
7,
17752,
13,
67,
8142,
7,
17752,
62,
15252,
11,
33793,
28,
19,
4008,
198,
220,
220,
220,
14985,
7,
15,
13,
17,
8,
198
] | 2.274547 | 1,599 |
from slr_parser.grammar import Grammar
import unittest
if __name__ == '__main__':
unittest.main()
| [
6738,
1017,
81,
62,
48610,
13,
4546,
3876,
1330,
20159,
3876,
198,
11748,
555,
715,
395,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.625 | 40 |
# Generated by Django 3.1 on 2020-09-08 07:43
from django.db import migrations, models
import django.db.models.deletion
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
319,
12131,
12,
2931,
12,
2919,
8753,
25,
3559,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
198,
11748,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
628
] | 2.904762 | 42 |
import torch
import numpy as np
from mpi4py import MPI
from parallel_pytorch.ops import tensor_merge
from parallel_pytorch.utils import abort_on_exception
def run_all():
test_1()
test_2()
if __name__ == '__main__':
run_all()
| [
11748,
28034,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
285,
14415,
19,
9078,
1330,
4904,
40,
198,
198,
6738,
10730,
62,
9078,
13165,
354,
13,
2840,
1330,
11192,
273,
62,
647,
469,
198,
6738,
10730,
62,
9078,
13165,
354,
13,
26791,
1330,
15614,
62,
261,
62,
1069,
4516,
628,
628,
198,
4299,
1057,
62,
439,
33529,
198,
220,
220,
220,
1332,
62,
16,
3419,
198,
220,
220,
220,
1332,
62,
17,
3419,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1057,
62,
439,
3419,
198
] | 2.595745 | 94 |
"""Day 07"""
if __name__ == '__main__':
process('test.txt')
process('input.txt')
| [
37811,
12393,
8753,
37811,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1429,
10786,
9288,
13,
14116,
11537,
198,
220,
220,
220,
1429,
10786,
15414,
13,
14116,
11537,
198
] | 2.432432 | 37 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
utilities
@author: boyangzhao
"""
import pandas as pd
import re
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
315,
2410,
198,
31,
9800,
25,
2933,
648,
89,
23778,
198,
37811,
198,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
302,
198
] | 2.32 | 50 |
#!/usr/bin/python3.7
# Copyright 2020 Aragubas
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# -- Imports -- #
from ENGINE import APPDATA as reg
from ENGINE import UTILS as utils
import ENGINE as tge
from Fogoso.MAIN import ClassesUtils as gameObjs
from Fogoso import MAIN as gameMain
import pygame, sys
import importlib
import time
from random import randint
OptionsScreen_DebugModeEnabled = gameObjs.UpDownButton
OptionsScreen_RandomWindowTitle = gameObjs.UpDownButton
OptionsScreen_NumberFormatting = gameObjs.UpDownButton
ElementsX = 0
ElementsY = 0
| [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
13,
22,
198,
2,
220,
220,
15069,
12131,
943,
363,
549,
292,
198,
2,
198,
2,
220,
220,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
220,
220,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
220,
220,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
220,
220,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
220,
220,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
220,
220,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
220,
220,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
220,
220,
11247,
739,
262,
13789,
13,
198,
2,
198,
2,
198,
198,
2,
1377,
1846,
3742,
1377,
1303,
198,
6738,
36924,
8881,
1330,
3486,
5760,
13563,
355,
842,
198,
6738,
36924,
8881,
1330,
19255,
45484,
355,
3384,
4487,
198,
11748,
36924,
8881,
355,
256,
469,
198,
198,
6738,
33381,
28213,
13,
5673,
1268,
1330,
38884,
18274,
4487,
355,
983,
5944,
8457,
198,
6738,
33381,
28213,
1330,
8779,
1268,
355,
983,
13383,
198,
198,
11748,
12972,
6057,
11,
25064,
198,
198,
11748,
1330,
8019,
198,
11748,
640,
198,
6738,
4738,
1330,
43720,
600,
198,
198,
29046,
23901,
62,
27509,
19076,
20491,
796,
983,
5944,
8457,
13,
4933,
8048,
21864,
198,
29046,
23901,
62,
29531,
27703,
19160,
796,
983,
5944,
8457,
13,
4933,
8048,
21864,
198,
29046,
23901,
62,
15057,
26227,
889,
796,
983,
5944,
8457,
13,
4933,
8048,
21864,
198,
198,
36,
3639,
55,
796,
657,
198,
36,
3639,
56,
796,
657,
628
] | 3.328221 | 326 |
from robotpy_ext.control.toggle import Toggle
from robotpy_ext.misc.precise_delay import NotifierDelay
| [
6738,
9379,
9078,
62,
2302,
13,
13716,
13,
44256,
1330,
34098,
198,
6738,
9379,
9078,
62,
2302,
13,
44374,
13,
3866,
37561,
62,
40850,
1330,
1892,
7483,
13856,
323,
628,
628
] | 3.419355 | 31 |
'''
This file contains test cases for tflearn
'''
import tensorflow.compat.v1 as tf
import tflearn
import unittest
if __name__ == "__main__":
unittest.main() | [
7061,
6,
198,
220,
220,
220,
770,
2393,
4909,
1332,
2663,
329,
256,
27919,
1501,
198,
7061,
6,
198,
198,
11748,
11192,
273,
11125,
13,
5589,
265,
13,
85,
16,
355,
48700,
198,
11748,
256,
27919,
1501,
198,
11748,
555,
715,
395,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419
] | 2.609375 | 64 |
#!/usr/bin/python3
# *****************************************************************************
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
# ******************************************************************************
import json
import os
import sys
import subprocess
if __name__ == "__main__":
success = True
try:
subprocess.run('cd /root; fab install-libs', shell=True, check=True)
except:
success = False
reply = dict()
reply['request_id'] = os.environ['request_id']
if success:
reply['status'] = 'ok'
else:
reply['status'] = 'err'
reply['response'] = dict()
try:
with open("/root/result.json") as f:
reply['response']['result'] = json.loads(f.read())
except:
reply['response']['result'] = {"error": "Failed to open result.json"}
reply['response']['log'] = "/var/log/datalab/{0}/{0}_{1}_{2}.log".format(os.environ['conf_resource'],
os.environ['project_name'],
os.environ['request_id'])
with open("/response/{}_{}_{}.json".format(os.environ['conf_resource'], os.environ['project_name'],
os.environ['request_id']), 'w') as response_file:
response_file.write(json.dumps(reply))
try:
subprocess.run('chmod 666 /response/*', shell=True, check=True)
except:
success = False
if not success:
sys.exit(1) | [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
198,
198,
2,
41906,
17174,
4557,
35625,
198,
2,
198,
2,
49962,
284,
262,
24843,
10442,
5693,
357,
1921,
37,
8,
739,
530,
198,
2,
393,
517,
18920,
5964,
11704,
13,
220,
4091,
262,
28536,
2393,
198,
2,
9387,
351,
428,
670,
329,
3224,
1321,
198,
2,
5115,
6634,
9238,
13,
220,
383,
7054,
37,
16625,
428,
2393,
198,
2,
284,
345,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
198,
2,
366,
34156,
15341,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
198,
2,
351,
262,
13789,
13,
220,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
198,
2,
3788,
9387,
739,
262,
13789,
318,
9387,
319,
281,
198,
2,
366,
1921,
3180,
1,
29809,
1797,
11,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
198,
2,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
220,
4091,
262,
13789,
329,
262,
198,
2,
2176,
3303,
15030,
21627,
290,
11247,
198,
2,
739,
262,
13789,
13,
198,
2,
198,
2,
41906,
17174,
46068,
1174,
198,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
850,
14681,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1943,
796,
6407,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
850,
14681,
13,
5143,
10786,
10210,
1220,
15763,
26,
7843,
2721,
12,
8019,
82,
3256,
7582,
28,
17821,
11,
2198,
28,
17821,
8,
198,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1943,
796,
10352,
628,
220,
220,
220,
10971,
796,
8633,
3419,
198,
220,
220,
220,
10971,
17816,
25927,
62,
312,
20520,
796,
28686,
13,
268,
2268,
17816,
25927,
62,
312,
20520,
198,
220,
220,
220,
611,
1943,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10971,
17816,
13376,
20520,
796,
705,
482,
6,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10971,
17816,
13376,
20520,
796,
705,
8056,
6,
628,
220,
220,
220,
10971,
17816,
26209,
20520,
796,
8633,
3419,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7203,
14,
15763,
14,
20274,
13,
17752,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10971,
17816,
26209,
6,
7131,
6,
20274,
20520,
796,
33918,
13,
46030,
7,
69,
13,
961,
28955,
198,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10971,
17816,
26209,
6,
7131,
6,
20274,
20520,
796,
19779,
18224,
1298,
366,
37,
6255,
284,
1280,
1255,
13,
17752,
20662,
628,
220,
220,
220,
10971,
17816,
26209,
6,
7131,
6,
6404,
20520,
796,
12813,
7785,
14,
6404,
14,
67,
10254,
397,
14,
90,
15,
92,
14,
90,
15,
92,
23330,
16,
92,
23330,
17,
27422,
6404,
1911,
18982,
7,
418,
13,
268,
2268,
17816,
10414,
62,
31092,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
268,
2268,
17816,
16302,
62,
3672,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
268,
2268,
17816,
25927,
62,
312,
6,
12962,
628,
220,
220,
220,
351,
1280,
7203,
14,
26209,
14,
90,
92,
23330,
92,
23330,
27422,
17752,
1911,
18982,
7,
418,
13,
268,
2268,
17816,
10414,
62,
31092,
6,
4357,
28686,
13,
268,
2268,
17816,
16302,
62,
3672,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
268,
2268,
17816,
25927,
62,
312,
20520,
828,
705,
86,
11537,
355,
2882,
62,
7753,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
62,
7753,
13,
13564,
7,
17752,
13,
67,
8142,
7,
47768,
4008,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
850,
14681,
13,
5143,
10786,
354,
4666,
43364,
1220,
26209,
15211,
3256,
7582,
28,
17821,
11,
2198,
28,
17821,
8,
198,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1943,
796,
10352,
628,
220,
220,
220,
611,
407,
1943,
25,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
37023,
7,
16,
8
] | 2.567148 | 901 |
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""
config settings, will be used in finetune.py
"""
from easydict import EasyDict as edict
import mindspore.common.dtype as mstype
from .bert_model import BertConfig
cfg = edict({
'task': 'NER',
'num_labels': 41,
'data_file': '',
'schema_file': None,
'finetune_ckpt': '',
'use_crf': False,
'clue_benchmark': False,
})
bert_net_cfg = BertConfig(
batch_size=8 if not cfg.clue_benchmark else 1,
seq_length=512,
vocab_size=30522,
hidden_size=1024,
num_hidden_layers=24,
num_attention_heads=16,
intermediate_size=4096,
hidden_act="gelu",
hidden_dropout_prob=0.0,
attention_probs_dropout_prob=0.0,
max_position_embeddings=512,
type_vocab_size=2,
initializer_range=0.02,
use_relative_positions=False,
input_mask_from_dataset=True,
token_type_ids_from_dataset=True,
dtype=mstype.float32,
compute_type=mstype.float16,
)
| [
2,
15069,
12131,
43208,
21852,
1766,
1539,
12052,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
2,
38093,
2559,
18604,
198,
198,
37811,
198,
11250,
6460,
11,
481,
307,
973,
287,
957,
316,
1726,
13,
9078,
198,
37811,
198,
198,
6738,
2562,
11600,
1330,
16789,
35,
713,
355,
1225,
713,
198,
198,
11748,
2000,
2777,
382,
13,
11321,
13,
67,
4906,
355,
285,
301,
2981,
198,
6738,
764,
4835,
62,
19849,
1330,
22108,
16934,
198,
198,
37581,
796,
1225,
713,
15090,
198,
220,
220,
220,
705,
35943,
10354,
705,
21479,
3256,
198,
220,
220,
220,
705,
22510,
62,
23912,
1424,
10354,
6073,
11,
198,
220,
220,
220,
705,
7890,
62,
7753,
10354,
705,
3256,
198,
220,
220,
220,
705,
15952,
2611,
62,
7753,
10354,
6045,
11,
198,
220,
220,
220,
705,
15643,
316,
1726,
62,
694,
457,
10354,
705,
3256,
198,
220,
220,
220,
705,
1904,
62,
6098,
69,
10354,
10352,
11,
198,
220,
220,
220,
705,
565,
518,
62,
26968,
4102,
10354,
10352,
11,
198,
30072,
198,
198,
4835,
62,
3262,
62,
37581,
796,
22108,
16934,
7,
198,
220,
220,
220,
15458,
62,
7857,
28,
23,
611,
407,
30218,
70,
13,
565,
518,
62,
26968,
4102,
2073,
352,
11,
198,
220,
220,
220,
33756,
62,
13664,
28,
25836,
11,
198,
220,
220,
220,
12776,
397,
62,
7857,
28,
22515,
1828,
11,
198,
220,
220,
220,
7104,
62,
7857,
28,
35500,
11,
198,
220,
220,
220,
997,
62,
30342,
62,
75,
6962,
28,
1731,
11,
198,
220,
220,
220,
997,
62,
1078,
1463,
62,
16600,
28,
1433,
11,
198,
220,
220,
220,
19898,
62,
7857,
28,
1821,
4846,
11,
198,
220,
220,
220,
7104,
62,
529,
2625,
25280,
84,
1600,
198,
220,
220,
220,
7104,
62,
14781,
448,
62,
1676,
65,
28,
15,
13,
15,
11,
198,
220,
220,
220,
3241,
62,
1676,
1443,
62,
14781,
448,
62,
1676,
65,
28,
15,
13,
15,
11,
198,
220,
220,
220,
3509,
62,
9150,
62,
20521,
67,
654,
28,
25836,
11,
198,
220,
220,
220,
2099,
62,
18893,
397,
62,
7857,
28,
17,
11,
198,
220,
220,
220,
4238,
7509,
62,
9521,
28,
15,
13,
2999,
11,
198,
220,
220,
220,
779,
62,
43762,
62,
1930,
1756,
28,
25101,
11,
198,
220,
220,
220,
5128,
62,
27932,
62,
6738,
62,
19608,
292,
316,
28,
17821,
11,
198,
220,
220,
220,
11241,
62,
4906,
62,
2340,
62,
6738,
62,
19608,
292,
316,
28,
17821,
11,
198,
220,
220,
220,
288,
4906,
28,
76,
301,
2981,
13,
22468,
2624,
11,
198,
220,
220,
220,
24061,
62,
4906,
28,
76,
301,
2981,
13,
22468,
1433,
11,
198,
8,
198
] | 2.80354 | 565 |
# -*- coding: utf-8 -*-
# utopia-cms 2020. Anbal Pacheco.
from django.core.management import BaseCommand
from django.db.utils import IntegrityError
from apps import core_articleviewedby_mdb
from core.models import ArticleViewedBy
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
3384,
24464,
12,
46406,
12131,
13,
1052,
6893,
350,
4891,
1073,
13,
198,
198,
6738,
42625,
14208,
13,
7295,
13,
27604,
1330,
7308,
21575,
198,
6738,
42625,
14208,
13,
9945,
13,
26791,
1330,
39348,
12331,
198,
198,
6738,
6725,
1330,
4755,
62,
20205,
1177,
276,
1525,
62,
9132,
65,
198,
6738,
4755,
13,
27530,
1330,
10172,
7680,
276,
3886,
628
] | 3.106667 | 75 |
import torch
import torch.nn as nn
from torch.optim import SGD
import MinkowskiEngine as ME
from MinkowskiEngine.modules.resnet_block import BasicBlock, Bottleneck
from examples.common import data_loader
from examples.resnet import ResNetBase
if __name__ == '__main__':
# loss and network
criterion = nn.CrossEntropyLoss()
net = MinkUNet14A(in_channels=3, out_channels=5, D=2)
print(net)
# a data loader must return a tuple of coords, features, and labels.
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
net = net.to(device)
optimizer = SGD(net.parameters(), lr=1e-2)
for i in range(10):
optimizer.zero_grad()
# Get new data
coords, feat, label = data_loader(is_classification=False)
input = ME.SparseTensor(feat, coords=coords).to(device)
label = label.to(device)
# Forward
output = net(input)
# Loss
loss = criterion(output.F, label)
print('Iteration: ', i, ', Loss: ', loss.item())
# Gradient
loss.backward()
optimizer.step()
# Saving and loading a network
torch.save(net.state_dict(), 'test.pth')
net.load_state_dict(torch.load('test.pth'))
| [
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
6738,
28034,
13,
40085,
1330,
26147,
35,
198,
198,
11748,
337,
676,
12079,
13798,
355,
11948,
198,
198,
6738,
337,
676,
12079,
13798,
13,
18170,
13,
411,
3262,
62,
9967,
1330,
14392,
12235,
11,
14835,
43163,
198,
198,
6738,
6096,
13,
11321,
1330,
1366,
62,
29356,
198,
6738,
6096,
13,
411,
3262,
1330,
1874,
7934,
14881,
628,
628,
628,
628,
628,
628,
628,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1303,
2994,
290,
3127,
198,
220,
220,
220,
34054,
796,
299,
77,
13,
21544,
14539,
28338,
43,
793,
3419,
198,
220,
220,
220,
2010,
796,
337,
676,
4944,
316,
1415,
32,
7,
259,
62,
354,
8961,
28,
18,
11,
503,
62,
354,
8961,
28,
20,
11,
360,
28,
17,
8,
198,
220,
220,
220,
3601,
7,
3262,
8,
628,
220,
220,
220,
1303,
257,
1366,
40213,
1276,
1441,
257,
46545,
286,
763,
3669,
11,
3033,
11,
290,
14722,
13,
198,
220,
220,
220,
3335,
796,
28034,
13,
25202,
10786,
66,
15339,
6,
611,
28034,
13,
66,
15339,
13,
271,
62,
15182,
3419,
2073,
705,
36166,
11537,
628,
220,
220,
220,
2010,
796,
2010,
13,
1462,
7,
25202,
8,
198,
220,
220,
220,
6436,
7509,
796,
26147,
35,
7,
3262,
13,
17143,
7307,
22784,
300,
81,
28,
16,
68,
12,
17,
8,
628,
220,
220,
220,
329,
1312,
287,
2837,
7,
940,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
13,
22570,
62,
9744,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3497,
649,
1366,
198,
220,
220,
220,
220,
220,
220,
220,
763,
3669,
11,
2218,
11,
6167,
796,
1366,
62,
29356,
7,
271,
62,
4871,
2649,
28,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
796,
11948,
13,
50,
29572,
51,
22854,
7,
27594,
11,
763,
3669,
28,
1073,
3669,
737,
1462,
7,
25202,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
796,
6167,
13,
1462,
7,
25202,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
19530,
198,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
2010,
7,
15414,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
22014,
198,
220,
220,
220,
220,
220,
220,
220,
2994,
796,
34054,
7,
22915,
13,
37,
11,
6167,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
29993,
341,
25,
46083,
1312,
11,
46083,
22014,
25,
46083,
2994,
13,
9186,
28955,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17701,
1153,
198,
220,
220,
220,
220,
220,
220,
220,
2994,
13,
1891,
904,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
7509,
13,
9662,
3419,
628,
220,
220,
220,
1303,
34689,
290,
11046,
257,
3127,
198,
220,
220,
220,
28034,
13,
21928,
7,
3262,
13,
5219,
62,
11600,
22784,
705,
9288,
13,
79,
400,
11537,
198,
220,
220,
220,
2010,
13,
2220,
62,
5219,
62,
11600,
7,
13165,
354,
13,
2220,
10786,
9288,
13,
79,
400,
6,
4008,
198
] | 2.458661 | 508 |
"""TODO."""
from setuptools import setup
setup(
name='nginx-access-tailer',
version='0.1',
author='swfrench',
url='https://github.com/swfrench/nginx-tailer',
packages=['nginx_access_tailer',],
license='BSD three-clause license',
entry_points={
'console_scripts': ['nginx-access-tailer = nginx_access_tailer.__main__:main'],
},
install_requires=[
'python-gflags >= 3.1.1',
'google-cloud-monitoring >= 0.25.0',
],
test_suite='nose.collector',
tests_require=['nose', 'mock'],
)
| [
37811,
51,
3727,
46,
526,
15931,
198,
198,
6738,
900,
37623,
10141,
1330,
9058,
198,
198,
40406,
7,
198,
220,
220,
220,
1438,
11639,
782,
28413,
12,
15526,
12,
13199,
263,
3256,
198,
220,
220,
220,
2196,
11639,
15,
13,
16,
3256,
198,
220,
220,
220,
1772,
11639,
2032,
69,
3532,
3256,
198,
220,
220,
220,
19016,
11639,
5450,
1378,
12567,
13,
785,
14,
2032,
69,
3532,
14,
782,
28413,
12,
13199,
263,
3256,
198,
220,
220,
220,
10392,
28,
17816,
782,
28413,
62,
15526,
62,
13199,
263,
3256,
4357,
198,
220,
220,
220,
5964,
11639,
21800,
1115,
12,
565,
682,
5964,
3256,
198,
220,
220,
220,
5726,
62,
13033,
34758,
198,
220,
220,
220,
220,
220,
220,
220,
705,
41947,
62,
46521,
10354,
37250,
782,
28413,
12,
15526,
12,
13199,
263,
796,
299,
42822,
62,
15526,
62,
13199,
263,
13,
834,
12417,
834,
25,
12417,
6,
4357,
198,
220,
220,
220,
8964,
198,
220,
220,
220,
2721,
62,
47911,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
705,
29412,
12,
70,
33152,
18189,
513,
13,
16,
13,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
13297,
12,
17721,
12,
41143,
278,
18189,
657,
13,
1495,
13,
15,
3256,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
1332,
62,
2385,
578,
11639,
77,
577,
13,
33327,
273,
3256,
198,
220,
220,
220,
5254,
62,
46115,
28,
17816,
77,
577,
3256,
705,
76,
735,
6,
4357,
198,
8,
198
] | 2.259259 | 243 |
# Copyright (c) 2017 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .. import helpers
from . import integration
| [
2,
15069,
357,
66,
8,
2177,
8180,
10501,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
6738,
11485,
1330,
49385,
198,
6738,
764,
1330,
11812,
628,
198
] | 3.890244 | 164 |
#!/usr/bin/env python
# -*- coding: utf-8 -*
import os
from setuptools import find_packages, setup
# allow setup.py to be run from any path
os.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir)))
with open('requirements.txt') as f:
install_requires = f.read().splitlines()
setup(
name='persistent-celery-beat-scheduler',
version='0.1.1.dev0',
packages=find_packages('src', exclude=('tests',)),
package_dir={'': 'src'},
include_package_data=True,
zip_safe=False,
description=(
'Celery Beat Scheduler that stores the scheduler data in Redis.'
),
author='Richard O\'Dwyer',
author_email='richard@richard.do',
license='Apache 2',
long_description='https://github.com/richardasaurus/persistent-celery-beat-scheduler',
install_requires=install_requires,
classifiers=[
'Intended Audience :: Developers',
'Operating System :: OS Independent',
'Programming Language :: Python',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.2',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Topic :: Internet :: WWW/HTTP',
],
)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
198,
198,
11748,
28686,
198,
198,
6738,
900,
37623,
10141,
1330,
1064,
62,
43789,
11,
9058,
198,
198,
2,
1249,
9058,
13,
9078,
284,
307,
1057,
422,
597,
3108,
198,
418,
13,
354,
15908,
7,
418,
13,
6978,
13,
27237,
6978,
7,
418,
13,
6978,
13,
22179,
7,
418,
13,
6978,
13,
397,
2777,
776,
7,
834,
7753,
834,
828,
28686,
13,
26037,
343,
22305,
198,
198,
4480,
1280,
10786,
8897,
18883,
13,
14116,
11537,
355,
277,
25,
198,
220,
220,
220,
2721,
62,
47911,
796,
277,
13,
961,
22446,
35312,
6615,
3419,
198,
198,
40406,
7,
198,
220,
220,
220,
1438,
11639,
19276,
7609,
12,
7015,
88,
12,
12945,
12,
1416,
704,
18173,
3256,
198,
220,
220,
220,
2196,
11639,
15,
13,
16,
13,
16,
13,
7959,
15,
3256,
198,
220,
220,
220,
10392,
28,
19796,
62,
43789,
10786,
10677,
3256,
19607,
28,
10786,
41989,
3256,
36911,
198,
220,
220,
220,
5301,
62,
15908,
34758,
7061,
25,
705,
10677,
6,
5512,
198,
220,
220,
220,
2291,
62,
26495,
62,
7890,
28,
17821,
11,
198,
220,
220,
220,
19974,
62,
21230,
28,
25101,
11,
198,
220,
220,
220,
6764,
16193,
198,
220,
220,
220,
220,
220,
220,
220,
705,
34,
417,
1924,
12568,
27774,
18173,
326,
7000,
262,
6038,
18173,
1366,
287,
2297,
271,
2637,
198,
220,
220,
220,
10612,
198,
220,
220,
220,
1772,
11639,
22245,
440,
43054,
35,
86,
9860,
3256,
198,
220,
220,
220,
1772,
62,
12888,
11639,
7527,
446,
31,
7527,
446,
13,
4598,
3256,
198,
220,
220,
220,
5964,
11639,
25189,
4891,
362,
3256,
198,
220,
220,
220,
890,
62,
11213,
11639,
5450,
1378,
12567,
13,
785,
14,
7527,
446,
292,
22302,
14,
19276,
7609,
12,
7015,
88,
12,
12945,
12,
1416,
704,
18173,
3256,
198,
220,
220,
220,
2721,
62,
47911,
28,
17350,
62,
47911,
11,
198,
220,
220,
220,
1398,
13350,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
705,
5317,
1631,
7591,
1240,
7904,
34152,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
18843,
803,
4482,
7904,
7294,
13362,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
17,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
18,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
20,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
21,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
33221,
7904,
4455,
7904,
13505,
54,
14,
40717,
3256,
198,
220,
220,
220,
16589,
198,
8,
198
] | 2.584466 | 515 |
import collections
import unittest
import driver
from driver.protocol import *
_server = ('localhost', 11211)
_dead_retry = 30
_socket_timeout = 3
_max_receive_size = 4096
def _raise_exception(message):
raise Exception(message)
| [
11748,
17268,
198,
11748,
555,
715,
395,
198,
11748,
4639,
198,
6738,
4639,
13,
11235,
4668,
1330,
1635,
198,
198,
62,
15388,
796,
19203,
36750,
3256,
13539,
1157,
8,
198,
62,
25124,
62,
1186,
563,
796,
1542,
198,
62,
44971,
62,
48678,
796,
513,
198,
62,
9806,
62,
260,
15164,
62,
7857,
796,
42479,
628,
628,
198,
4299,
4808,
40225,
62,
1069,
4516,
7,
20500,
2599,
198,
220,
220,
220,
5298,
35528,
7,
20500,
8,
198
] | 3.118421 | 76 |
# --------------
# Import packages
import numpy as np
import pandas as pd
from scipy.stats import mode
path
# code starts here
bank = pd.read_csv(path)
categorical_var = bank.select_dtypes(include = 'object')
print(categorical_var)
numerical_var = bank.select_dtypes(include = 'number')
print(numerical_var)
# code ends here
# --------------
# code starts here
banks = bank.drop('Loan_ID',axis = 1)
print(banks)
print(banks.isnull().sum())
bank_mode = banks.mode().iloc[0]
banks = banks.fillna(bank_mode)
#code ends here
# --------------
# Code starts here
avg_loan_amount = banks.pivot_table(index=['Gender','Married','Self_Employed'],values = 'LoanAmount')
# code ends here
# --------------
# code starts here
loan_approved_se = ((banks['Self_Employed']=='Yes') & (banks['Loan_Status']=='Y')).value_counts()
#print(loan_approved_se)
loan_approved_nse = ((banks['Self_Employed']=='No') & (banks['Loan_Status']=='Y')).value_counts()
print(loan_approved_nse)
Loan_Status = 614
percentage_se = (56/Loan_Status)*100
percentage_nse = (366/Loan_Status)*100
# code ends here
# --------------
# code starts here
loan_term = banks['Loan_Amount_Term'].apply (lambda x : int(x)/12)
print(loan_term.value_counts())
big_loan = [i for i in loan_term if i >= 25]
big_loan_term = len(big_loan)
print(big_loan_term)
#[loan_term.value_counts()[i] for i in range(len(loan_terms)) if loan_term.value_counts().index[i] >= 25]
# code ends here
# --------------
# code starts here
loan_groupby = banks.groupby('Loan_Status')
loan_groupby = loan_groupby['ApplicantIncome','Credit_History']
mean_values = loan_groupby.mean()
# code ends here
| [
2,
220,
26171,
198,
2,
17267,
10392,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
629,
541,
88,
13,
34242,
1330,
4235,
220,
198,
220,
198,
198,
6978,
198,
198,
2,
2438,
4940,
994,
198,
17796,
796,
279,
67,
13,
961,
62,
40664,
7,
6978,
8,
198,
66,
2397,
12409,
62,
7785,
796,
3331,
13,
19738,
62,
67,
19199,
7,
17256,
796,
705,
15252,
11537,
198,
4798,
7,
66,
2397,
12409,
62,
7785,
8,
198,
77,
6975,
605,
62,
7785,
796,
3331,
13,
19738,
62,
67,
19199,
7,
17256,
796,
705,
17618,
11537,
198,
4798,
7,
77,
6975,
605,
62,
7785,
8,
198,
198,
2,
2438,
5645,
994,
628,
198,
2,
220,
26171,
198,
2,
2438,
4940,
994,
198,
43558,
796,
3331,
13,
14781,
10786,
43,
24611,
62,
2389,
3256,
22704,
796,
352,
8,
198,
4798,
7,
43558,
8,
198,
4798,
7,
43558,
13,
271,
8423,
22446,
16345,
28955,
198,
17796,
62,
14171,
796,
6341,
13,
14171,
22446,
346,
420,
58,
15,
60,
198,
43558,
796,
6341,
13,
20797,
2616,
7,
17796,
62,
14171,
8,
198,
198,
2,
8189,
5645,
994,
628,
198,
2,
220,
26171,
198,
2,
6127,
4940,
994,
198,
615,
70,
62,
5439,
272,
62,
17287,
796,
6341,
13,
79,
45785,
62,
11487,
7,
9630,
28,
17816,
41394,
41707,
7676,
2228,
41707,
24704,
62,
29733,
276,
6,
4357,
27160,
796,
705,
43,
24611,
31264,
11537,
628,
198,
198,
2,
2438,
5645,
994,
628,
198,
198,
2,
220,
26171,
198,
2,
2438,
4940,
994,
628,
198,
198,
5439,
272,
62,
29137,
62,
325,
796,
14808,
43558,
17816,
24704,
62,
29733,
276,
20520,
855,
6,
5297,
11537,
1222,
357,
43558,
17816,
43,
24611,
62,
19580,
20520,
855,
6,
56,
11537,
737,
8367,
62,
9127,
82,
3419,
198,
2,
4798,
7,
5439,
272,
62,
29137,
62,
325,
8,
198,
5439,
272,
62,
29137,
62,
77,
325,
796,
14808,
43558,
17816,
24704,
62,
29733,
276,
20520,
855,
6,
2949,
11537,
1222,
357,
43558,
17816,
43,
24611,
62,
19580,
20520,
855,
6,
56,
11537,
737,
8367,
62,
9127,
82,
3419,
198,
4798,
7,
5439,
272,
62,
29137,
62,
77,
325,
8,
198,
43,
24611,
62,
19580,
796,
718,
1415,
198,
25067,
496,
62,
325,
796,
357,
3980,
14,
43,
24611,
62,
19580,
27493,
3064,
198,
25067,
496,
62,
77,
325,
796,
357,
32459,
14,
43,
24611,
62,
19580,
27493,
3064,
628,
628,
198,
2,
2438,
5645,
994,
628,
198,
2,
220,
26171,
198,
2,
2438,
4940,
994,
198,
198,
5439,
272,
62,
4354,
796,
6341,
17816,
43,
24611,
62,
31264,
62,
40596,
6,
4083,
39014,
357,
50033,
2124,
1058,
493,
7,
87,
20679,
1065,
8,
198,
4798,
7,
5439,
272,
62,
4354,
13,
8367,
62,
9127,
82,
28955,
198,
14261,
62,
5439,
272,
796,
685,
72,
329,
1312,
287,
8063,
62,
4354,
611,
1312,
18189,
1679,
60,
198,
14261,
62,
5439,
272,
62,
4354,
796,
18896,
7,
14261,
62,
5439,
272,
8,
198,
4798,
7,
14261,
62,
5439,
272,
62,
4354,
8,
198,
198,
2,
58,
5439,
272,
62,
4354,
13,
8367,
62,
9127,
82,
3419,
58,
72,
60,
329,
1312,
287,
2837,
7,
11925,
7,
5439,
272,
62,
38707,
4008,
611,
8063,
62,
4354,
13,
8367,
62,
9127,
82,
22446,
9630,
58,
72,
60,
18189,
1679,
60,
198,
2,
2438,
5645,
994,
628,
628,
198,
2,
220,
26171,
198,
2,
2438,
4940,
994,
198,
5439,
272,
62,
8094,
1525,
796,
6341,
13,
8094,
1525,
10786,
43,
24611,
62,
19580,
11537,
198,
5439,
272,
62,
8094,
1525,
796,
8063,
62,
8094,
1525,
17816,
33583,
415,
818,
2958,
41707,
23690,
62,
18122,
20520,
198,
32604,
62,
27160,
796,
8063,
62,
8094,
1525,
13,
32604,
3419,
628,
198,
2,
2438,
5645,
994,
628,
198
] | 2.680713 | 617 |
# This file is part of Patsy
# Copyright (C) 2013 Nathaniel Smith <njs@pobox.com>
# See file LICENSE.txt for license information.
# Regression tests for fixed bugs (when not otherwise better covered somewhere
# else)
from patsy import (EvalEnvironment, dmatrix, build_design_matrices,
PatsyError, Origin)
| [
2,
770,
2393,
318,
636,
286,
47216,
88,
198,
2,
15069,
357,
34,
8,
2211,
49536,
4176,
1279,
77,
8457,
31,
79,
672,
1140,
13,
785,
29,
198,
2,
4091,
2393,
38559,
24290,
13,
14116,
329,
5964,
1321,
13,
198,
198,
2,
3310,
2234,
5254,
329,
5969,
11316,
357,
12518,
407,
4306,
1365,
5017,
7382,
198,
2,
2073,
8,
198,
198,
6738,
279,
1381,
88,
1330,
357,
36,
2100,
31441,
11,
288,
6759,
8609,
11,
1382,
62,
26124,
62,
6759,
45977,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
47216,
88,
12331,
11,
19349,
8,
198
] | 3.018519 | 108 |
__all__ = ['imread', 'imsave']
import numpy as np
from PIL import Image
from ...util import img_as_ubyte, img_as_uint
def imread(fname, dtype=None, img_num=None, **kwargs):
"""Load an image from file.
Parameters
----------
fname : str or file
File name or file-like-object.
dtype : numpy dtype object or string specifier
Specifies data type of array elements.
img_num : int, optional
Specifies which image to read in a file with multiple images
(zero-indexed).
kwargs : keyword pairs, optional
Addition keyword arguments to pass through.
Notes
-----
Files are read using the Python Imaging Library.
See PIL docs [1]_ for a list of supported formats.
References
----------
.. [1] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html
"""
if isinstance(fname, str):
with open(fname, 'rb') as f:
im = Image.open(f)
return pil_to_ndarray(im, dtype=dtype, img_num=img_num)
else:
im = Image.open(fname)
return pil_to_ndarray(im, dtype=dtype, img_num=img_num)
def pil_to_ndarray(image, dtype=None, img_num=None):
"""Import a PIL Image object to an ndarray, in memory.
Parameters
----------
Refer to ``imread``.
"""
try:
# this will raise an IOError if the file is not readable
image.getdata()[0]
except IOError as e:
site = "http://pillow.readthedocs.org/en/latest/installation.html#external-libraries"
pillow_error_message = str(e)
error_message = ('Could not load "%s" \n'
'Reason: "%s"\n'
'Please see documentation at: %s'
% (image.filename, pillow_error_message, site))
raise ValueError(error_message)
frames = []
grayscale = None
i = 0
while 1:
try:
image.seek(i)
except EOFError:
break
frame = image
if img_num is not None and img_num != i:
image.getdata()[0]
i += 1
continue
if image.format == 'PNG' and image.mode == 'I' and dtype is None:
dtype = 'uint16'
if image.mode == 'P':
if grayscale is None:
grayscale = _palette_is_grayscale(image)
if grayscale:
frame = image.convert('L')
else:
if image.format == 'PNG' and 'transparency' in image.info:
frame = image.convert('RGBA')
else:
frame = image.convert('RGB')
elif image.mode == '1':
frame = image.convert('L')
elif 'A' in image.mode:
frame = image.convert('RGBA')
elif image.mode == 'CMYK':
frame = image.convert('RGB')
if image.mode.startswith('I;16'):
shape = image.size
dtype = '>u2' if image.mode.endswith('B') else '<u2'
if 'S' in image.mode:
dtype = dtype.replace('u', 'i')
frame = np.fromstring(frame.tobytes(), dtype)
frame.shape = shape[::-1]
else:
frame = np.array(frame, dtype=dtype)
frames.append(frame)
i += 1
if img_num is not None:
break
if hasattr(image, 'fp') and image.fp:
image.fp.close()
if img_num is None and len(frames) > 1:
return np.array(frames)
elif frames:
return frames[0]
elif img_num:
raise IndexError('Could not find image #%s' % img_num)
def _palette_is_grayscale(pil_image):
"""Return True if PIL image in palette mode is grayscale.
Parameters
----------
pil_image : PIL image
PIL Image that is in Palette mode.
Returns
-------
is_grayscale : bool
True if all colors in image palette are gray.
"""
assert pil_image.mode == 'P'
# get palette as an array with R, G, B columns
palette = np.asarray(pil_image.getpalette()).reshape((256, 3))
# Not all palette colors are used; unused colors have junk values.
start, stop = pil_image.getextrema()
valid_palette = palette[start:stop + 1]
# Image is grayscale if channel differences (R - G and G - B)
# are all zero.
return np.allclose(np.diff(valid_palette), 0)
def ndarray_to_pil(arr, format_str=None):
"""Export an ndarray to a PIL object.
Parameters
----------
Refer to ``imsave``.
"""
if arr.ndim == 3:
arr = img_as_ubyte(arr)
mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]]
elif format_str in ['png', 'PNG']:
mode = 'I;16'
mode_base = 'I'
if arr.dtype.kind == 'f':
arr = img_as_uint(arr)
elif arr.max() < 256 and arr.min() >= 0:
arr = arr.astype(np.uint8)
mode = mode_base = 'L'
else:
arr = img_as_uint(arr)
else:
arr = img_as_ubyte(arr)
mode = 'L'
mode_base = 'L'
try:
array_buffer = arr.tobytes()
except AttributeError:
array_buffer = arr.tostring() # Numpy < 1.9
if arr.ndim == 2:
im = Image.new(mode_base, arr.T.shape)
try:
im.frombytes(array_buffer, 'raw', mode)
except AttributeError:
im.fromstring(array_buffer, 'raw', mode) # PIL 1.1.7
else:
image_shape = (arr.shape[1], arr.shape[0])
try:
im = Image.frombytes(mode, image_shape, array_buffer)
except AttributeError:
im = Image.fromstring(mode, image_shape, array_buffer) # PIL 1.1.7
return im
def imsave(fname, arr, format_str=None, **kwargs):
"""Save an image to disk.
Parameters
----------
fname : str or file-like object
Name of destination file.
arr : ndarray of uint8 or float
Array (image) to save. Arrays of data-type uint8 should have
values in [0, 255], whereas floating-point arrays must be
in [0, 1].
format_str: str
Format to save as, this is defaulted to PNG if using a file-like
object; this will be derived from the extension if fname is a string
kwargs: dict
Keyword arguments to the Pillow save function (or tifffile save
function, for Tiff files). These are format dependent. For example,
Pillow's JPEG save function supports an integer ``quality`` argument
with values in [1, 95], while TIFFFile supports a ``compress``
integer argument with values in [0, 9].
Notes
-----
Use the Python Imaging Library.
See PIL docs [1]_ for a list of other supported formats.
All images besides single channel PNGs are converted using `img_as_uint8`.
Single Channel PNGs have the following behavior:
- Integer values in [0, 255] and Boolean types -> img_as_uint8
- Floating point and other integers -> img_as_uint16
References
----------
.. [1] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html
"""
# default to PNG if file-like object
if not isinstance(fname, str) and format_str is None:
format_str = "PNG"
# Check for png in filename
if (isinstance(fname, str)
and fname.lower().endswith(".png")):
format_str = "PNG"
arr = np.asanyarray(arr)
if arr.dtype.kind == 'b':
arr = arr.astype(np.uint8)
if arr.ndim not in (2, 3):
raise ValueError("Invalid shape for image array: %s" % (arr.shape, ))
if arr.ndim == 3:
if arr.shape[2] not in (3, 4):
raise ValueError("Invalid number of channels in image array.")
img = ndarray_to_pil(arr, format_str=format_str)
img.save(fname, format=format_str, **kwargs)
| [
834,
439,
834,
796,
37250,
320,
961,
3256,
705,
12078,
1015,
20520,
198,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
350,
4146,
1330,
7412,
198,
198,
6738,
2644,
22602,
1330,
33705,
62,
292,
62,
549,
88,
660,
11,
33705,
62,
292,
62,
28611,
628,
198,
4299,
545,
961,
7,
69,
3672,
11,
288,
4906,
28,
14202,
11,
33705,
62,
22510,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
37227,
8912,
281,
2939,
422,
2393,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
277,
3672,
1058,
965,
393,
2393,
198,
220,
220,
220,
220,
220,
220,
9220,
1438,
393,
2393,
12,
2339,
12,
15252,
13,
198,
220,
220,
220,
288,
4906,
1058,
299,
32152,
288,
4906,
2134,
393,
4731,
1020,
7483,
198,
220,
220,
220,
220,
220,
220,
18291,
6945,
1366,
2099,
286,
7177,
4847,
13,
198,
220,
220,
220,
33705,
62,
22510,
1058,
493,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
18291,
6945,
543,
2939,
284,
1100,
287,
257,
2393,
351,
3294,
4263,
198,
220,
220,
220,
220,
220,
220,
357,
22570,
12,
9630,
276,
737,
198,
220,
220,
220,
479,
86,
22046,
1058,
21179,
14729,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
3060,
653,
21179,
7159,
284,
1208,
832,
13,
628,
220,
220,
220,
11822,
198,
220,
220,
220,
37404,
198,
220,
220,
220,
13283,
389,
1100,
1262,
262,
11361,
48656,
10074,
13,
198,
220,
220,
220,
4091,
350,
4146,
34165,
685,
16,
60,
62,
329,
257,
1351,
286,
4855,
17519,
13,
628,
220,
220,
220,
31458,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
11485,
685,
16,
60,
2638,
1378,
27215,
322,
13,
961,
83,
704,
420,
82,
13,
2398,
14,
268,
14,
42861,
14,
4993,
2070,
14,
9060,
12,
7753,
12,
687,
1381,
13,
6494,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
318,
39098,
7,
69,
3672,
11,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
69,
3672,
11,
705,
26145,
11537,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
545,
796,
7412,
13,
9654,
7,
69,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
5560,
62,
1462,
62,
358,
18747,
7,
320,
11,
288,
4906,
28,
67,
4906,
11,
33705,
62,
22510,
28,
9600,
62,
22510,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
545,
796,
7412,
13,
9654,
7,
69,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5560,
62,
1462,
62,
358,
18747,
7,
320,
11,
288,
4906,
28,
67,
4906,
11,
33705,
62,
22510,
28,
9600,
62,
22510,
8,
628,
198,
4299,
5560,
62,
1462,
62,
358,
18747,
7,
9060,
11,
288,
4906,
28,
14202,
11,
33705,
62,
22510,
28,
14202,
2599,
198,
220,
220,
220,
37227,
20939,
257,
350,
4146,
7412,
2134,
284,
281,
299,
67,
18747,
11,
287,
4088,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
33973,
284,
7559,
320,
961,
15506,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
428,
481,
5298,
281,
24418,
12331,
611,
262,
2393,
318,
407,
31744,
198,
220,
220,
220,
220,
220,
220,
220,
2939,
13,
1136,
7890,
3419,
58,
15,
60,
198,
220,
220,
220,
2845,
24418,
12331,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2524,
796,
366,
4023,
1378,
27215,
322,
13,
961,
83,
704,
420,
82,
13,
2398,
14,
268,
14,
42861,
14,
17350,
341,
13,
6494,
2,
22615,
12,
75,
11127,
1,
198,
220,
220,
220,
220,
220,
220,
220,
28774,
62,
18224,
62,
20500,
796,
965,
7,
68,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4049,
62,
20500,
796,
19203,
23722,
407,
3440,
36521,
82,
1,
3467,
77,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
45008,
25,
36521,
82,
1,
59,
77,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5492,
766,
10314,
379,
25,
4064,
82,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
9060,
13,
34345,
11,
28774,
62,
18224,
62,
20500,
11,
2524,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7,
18224,
62,
20500,
8,
198,
220,
220,
220,
13431,
796,
17635,
198,
220,
220,
220,
1036,
592,
38765,
796,
6045,
198,
220,
220,
220,
1312,
796,
657,
198,
220,
220,
220,
981,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
13,
36163,
7,
72,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
412,
19238,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
628,
220,
220,
220,
220,
220,
220,
220,
611,
33705,
62,
22510,
318,
407,
6045,
290,
33705,
62,
22510,
14512,
1312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2939,
13,
1136,
7890,
3419,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1312,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2939,
13,
18982,
6624,
705,
47,
10503,
6,
290,
2939,
13,
14171,
6624,
705,
40,
6,
290,
288,
4906,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
4906,
796,
705,
28611,
1433,
6,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2939,
13,
14171,
6624,
705,
47,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1036,
592,
38765,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1036,
592,
38765,
796,
4808,
18596,
5857,
62,
271,
62,
2164,
592,
38765,
7,
9060,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1036,
592,
38765,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
43,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2939,
13,
18982,
6624,
705,
47,
10503,
6,
290,
705,
7645,
11944,
6,
287,
2939,
13,
10951,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
48192,
4339,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
36982,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2939,
13,
14171,
6624,
705,
16,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
43,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
705,
32,
6,
287,
2939,
13,
14171,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
48192,
4339,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2939,
13,
14171,
6624,
705,
24187,
56,
42,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
2939,
13,
1102,
1851,
10786,
36982,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2939,
13,
14171,
13,
9688,
2032,
342,
10786,
40,
26,
1433,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5485,
796,
2939,
13,
7857,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
4906,
796,
705,
29,
84,
17,
6,
611,
2939,
13,
14171,
13,
437,
2032,
342,
10786,
33,
11537,
2073,
705,
27,
84,
17,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
50,
6,
287,
2939,
13,
14171,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
4906,
796,
288,
4906,
13,
33491,
10786,
84,
3256,
705,
72,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
45941,
13,
6738,
8841,
7,
14535,
13,
83,
26730,
4879,
22784,
288,
4906,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
13,
43358,
796,
5485,
58,
3712,
12,
16,
60,
628,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5739,
796,
45941,
13,
18747,
7,
14535,
11,
288,
4906,
28,
67,
4906,
8,
628,
220,
220,
220,
220,
220,
220,
220,
13431,
13,
33295,
7,
14535,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1312,
15853,
352,
628,
220,
220,
220,
220,
220,
220,
220,
611,
33705,
62,
22510,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
611,
468,
35226,
7,
9060,
11,
705,
46428,
11537,
290,
2939,
13,
46428,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2939,
13,
46428,
13,
19836,
3419,
628,
220,
220,
220,
611,
33705,
62,
22510,
318,
6045,
290,
18896,
7,
37805,
8,
1875,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
45941,
13,
18747,
7,
37805,
8,
198,
220,
220,
220,
1288,
361,
13431,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
13431,
58,
15,
60,
198,
220,
220,
220,
1288,
361,
33705,
62,
22510,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
12901,
12331,
10786,
23722,
407,
1064,
2939,
220,
1303,
4,
82,
6,
4064,
33705,
62,
22510,
8,
628,
198,
4299,
4808,
18596,
5857,
62,
271,
62,
2164,
592,
38765,
7,
79,
346,
62,
9060,
2599,
198,
220,
220,
220,
37227,
13615,
6407,
611,
350,
4146,
2939,
287,
27043,
4235,
318,
1036,
592,
38765,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
5560,
62,
9060,
1058,
350,
4146,
2939,
198,
220,
220,
220,
220,
220,
220,
220,
350,
4146,
7412,
326,
318,
287,
3175,
5857,
4235,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
318,
62,
2164,
592,
38765,
1058,
20512,
198,
220,
220,
220,
220,
220,
220,
220,
6407,
611,
477,
7577,
287,
2939,
27043,
389,
12768,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6818,
5560,
62,
9060,
13,
14171,
6624,
705,
47,
6,
198,
220,
220,
220,
1303,
651,
27043,
355,
281,
7177,
351,
371,
11,
402,
11,
347,
15180,
198,
220,
220,
220,
27043,
796,
45941,
13,
292,
18747,
7,
79,
346,
62,
9060,
13,
1136,
18596,
5857,
3419,
737,
3447,
1758,
19510,
11645,
11,
513,
4008,
198,
220,
220,
220,
1303,
1892,
477,
27043,
7577,
389,
973,
26,
21958,
7577,
423,
18556,
3815,
13,
198,
220,
220,
220,
923,
11,
2245,
796,
5560,
62,
9060,
13,
1136,
2302,
260,
2611,
3419,
198,
220,
220,
220,
4938,
62,
18596,
5857,
796,
27043,
58,
9688,
25,
11338,
1343,
352,
60,
198,
220,
220,
220,
1303,
7412,
318,
1036,
592,
38765,
611,
6518,
5400,
357,
49,
532,
402,
290,
402,
532,
347,
8,
198,
220,
220,
220,
1303,
389,
477,
6632,
13,
198,
220,
220,
220,
1441,
45941,
13,
439,
19836,
7,
37659,
13,
26069,
7,
12102,
62,
18596,
5857,
828,
657,
8,
628,
198,
4299,
299,
67,
18747,
62,
1462,
62,
79,
346,
7,
3258,
11,
5794,
62,
2536,
28,
14202,
2599,
198,
220,
220,
220,
37227,
43834,
281,
299,
67,
18747,
284,
257,
350,
4146,
2134,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
33973,
284,
7559,
12078,
1015,
15506,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
5240,
13,
358,
320,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
33705,
62,
292,
62,
549,
88,
660,
7,
3258,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4235,
796,
1391,
18,
25,
705,
36982,
3256,
604,
25,
705,
48192,
4339,
6,
92,
58,
3258,
13,
43358,
58,
17,
11907,
628,
220,
220,
220,
1288,
361,
5794,
62,
2536,
287,
37250,
11134,
3256,
705,
47,
10503,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
4235,
796,
705,
40,
26,
1433,
6,
198,
220,
220,
220,
220,
220,
220,
220,
4235,
62,
8692,
796,
705,
40,
6,
628,
220,
220,
220,
220,
220,
220,
220,
611,
5240,
13,
67,
4906,
13,
11031,
6624,
705,
69,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
33705,
62,
292,
62,
28611,
7,
3258,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
5240,
13,
9806,
3419,
1279,
17759,
290,
5240,
13,
1084,
3419,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
5240,
13,
459,
2981,
7,
37659,
13,
28611,
23,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4235,
796,
4235,
62,
8692,
796,
705,
43,
6,
628,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
33705,
62,
292,
62,
28611,
7,
3258,
8,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
33705,
62,
292,
62,
549,
88,
660,
7,
3258,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4235,
796,
705,
43,
6,
198,
220,
220,
220,
220,
220,
220,
220,
4235,
62,
8692,
796,
705,
43,
6,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
62,
22252,
796,
5240,
13,
83,
26730,
4879,
3419,
198,
220,
220,
220,
2845,
3460,
4163,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7177,
62,
22252,
796,
5240,
13,
83,
455,
1806,
3419,
220,
1303,
399,
32152,
1279,
352,
13,
24,
628,
220,
220,
220,
611,
5240,
13,
358,
320,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
545,
796,
7412,
13,
3605,
7,
14171,
62,
8692,
11,
5240,
13,
51,
13,
43358,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
545,
13,
6738,
33661,
7,
18747,
62,
22252,
11,
705,
1831,
3256,
4235,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
3460,
4163,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
545,
13,
6738,
8841,
7,
18747,
62,
22252,
11,
705,
1831,
3256,
4235,
8,
220,
1303,
350,
4146,
352,
13,
16,
13,
22,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2939,
62,
43358,
796,
357,
3258,
13,
43358,
58,
16,
4357,
5240,
13,
43358,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
545,
796,
7412,
13,
6738,
33661,
7,
14171,
11,
2939,
62,
43358,
11,
7177,
62,
22252,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
3460,
4163,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
545,
796,
7412,
13,
6738,
8841,
7,
14171,
11,
2939,
62,
43358,
11,
7177,
62,
22252,
8,
220,
1303,
350,
4146,
352,
13,
16,
13,
22,
198,
220,
220,
220,
1441,
545,
628,
198,
4299,
545,
21928,
7,
69,
3672,
11,
5240,
11,
5794,
62,
2536,
28,
14202,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
37227,
16928,
281,
2939,
284,
11898,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
277,
3672,
1058,
965,
393,
2393,
12,
2339,
2134,
198,
220,
220,
220,
220,
220,
220,
220,
6530,
286,
10965,
2393,
13,
198,
220,
220,
220,
5240,
1058,
299,
67,
18747,
286,
20398,
23,
393,
12178,
198,
220,
220,
220,
220,
220,
220,
220,
15690,
357,
9060,
8,
284,
3613,
13,
220,
943,
20477,
286,
1366,
12,
4906,
20398,
23,
815,
423,
198,
220,
220,
220,
220,
220,
220,
220,
3815,
287,
685,
15,
11,
14280,
4357,
9472,
12462,
12,
4122,
26515,
1276,
307,
198,
220,
220,
220,
220,
220,
220,
220,
287,
685,
15,
11,
352,
4083,
198,
220,
220,
220,
5794,
62,
2536,
25,
965,
198,
220,
220,
220,
220,
220,
220,
220,
18980,
284,
3613,
355,
11,
428,
318,
4277,
276,
284,
36182,
611,
1262,
257,
2393,
12,
2339,
198,
220,
220,
220,
220,
220,
220,
220,
2134,
26,
428,
481,
307,
10944,
422,
262,
7552,
611,
277,
3672,
318,
257,
4731,
198,
220,
220,
220,
479,
86,
22046,
25,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
7383,
4775,
7159,
284,
262,
19770,
322,
3613,
2163,
357,
273,
256,
361,
487,
576,
3613,
198,
220,
220,
220,
220,
220,
220,
220,
2163,
11,
329,
35775,
3696,
737,
2312,
389,
5794,
10795,
13,
1114,
1672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
19770,
322,
338,
48561,
3613,
2163,
6971,
281,
18253,
7559,
13237,
15506,
4578,
198,
220,
220,
220,
220,
220,
220,
220,
351,
3815,
287,
685,
16,
11,
6957,
4357,
981,
309,
5064,
5777,
576,
6971,
257,
7559,
5589,
601,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
18253,
4578,
351,
3815,
287,
685,
15,
11,
860,
4083,
628,
220,
220,
220,
11822,
198,
220,
220,
220,
37404,
198,
220,
220,
220,
5765,
262,
11361,
48656,
10074,
13,
198,
220,
220,
220,
4091,
350,
4146,
34165,
685,
16,
60,
62,
329,
257,
1351,
286,
584,
4855,
17519,
13,
198,
220,
220,
220,
1439,
4263,
13769,
2060,
6518,
36182,
82,
389,
11513,
1262,
4600,
9600,
62,
292,
62,
28611,
23,
44646,
198,
220,
220,
220,
14206,
11102,
36182,
82,
423,
262,
1708,
4069,
25,
198,
220,
220,
220,
532,
34142,
3815,
287,
685,
15,
11,
14280,
60,
290,
41146,
3858,
4613,
33705,
62,
292,
62,
28611,
23,
198,
220,
220,
220,
532,
49768,
966,
290,
584,
37014,
4613,
33705,
62,
292,
62,
28611,
1433,
628,
220,
220,
220,
31458,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
11485,
685,
16,
60,
2638,
1378,
27215,
322,
13,
961,
83,
704,
420,
82,
13,
2398,
14,
268,
14,
42861,
14,
4993,
2070,
14,
9060,
12,
7753,
12,
687,
1381,
13,
6494,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
4277,
284,
36182,
611,
2393,
12,
2339,
2134,
198,
220,
220,
220,
611,
407,
318,
39098,
7,
69,
3672,
11,
965,
8,
290,
5794,
62,
2536,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5794,
62,
2536,
796,
366,
47,
10503,
1,
198,
220,
220,
220,
1303,
6822,
329,
279,
782,
287,
29472,
198,
220,
220,
220,
611,
357,
271,
39098,
7,
69,
3672,
11,
965,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
290,
277,
3672,
13,
21037,
22446,
437,
2032,
342,
7,
1911,
11134,
4943,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5794,
62,
2536,
796,
366,
47,
10503,
1,
628,
220,
220,
220,
5240,
796,
45941,
13,
292,
1092,
18747,
7,
3258,
8,
628,
220,
220,
220,
611,
5240,
13,
67,
4906,
13,
11031,
6624,
705,
65,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
5240,
796,
5240,
13,
459,
2981,
7,
37659,
13,
28611,
23,
8,
628,
220,
220,
220,
611,
5240,
13,
358,
320,
407,
287,
357,
17,
11,
513,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
44651,
5485,
329,
2939,
7177,
25,
4064,
82,
1,
4064,
357,
3258,
13,
43358,
11,
15306,
628,
220,
220,
220,
611,
5240,
13,
358,
320,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
5240,
13,
43358,
58,
17,
60,
407,
287,
357,
18,
11,
604,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
44651,
1271,
286,
9619,
287,
2939,
7177,
19570,
628,
220,
220,
220,
33705,
796,
299,
67,
18747,
62,
1462,
62,
79,
346,
7,
3258,
11,
5794,
62,
2536,
28,
18982,
62,
2536,
8,
198,
220,
220,
220,
33705,
13,
21928,
7,
69,
3672,
11,
5794,
28,
18982,
62,
2536,
11,
12429,
46265,
22046,
8,
198
] | 2.218286 | 3,500 |
# -*- coding: utf-8 -*-
"""
Linear chain of reactions.
"""
from __future__ import print_function, division
import tellurium as te
model = '''
model feedback()
// Reactions:
J0: $X0 -> S1; (VM1 * (X0 - S1/Keq1))/(1 + X0 + S1 + S4^h);
J1: S1 -> S2; (10 * S1 - 2 * S2) / (1 + S1 + S2);
J2: S2 -> S3; (10 * S2 - 2 * S3) / (1 + S2 + S3);
J3: S3 -> S4; (10 * S3 - 2 * S4) / (1 + S3 + S4);
J4: S4 -> $X1; (V4 * S4) / (KS4 + S4);
// Species initializations:
S1 = 0; S2 = 0; S3 = 0;
S4 = 0; X0 = 10; X1 = 0;
// Variable initialization:
VM1 = 10; Keq1 = 10; h = 10; V4 = 2.5; KS4 = 0.5;
end'''
r = te.loada(model)
result = r.simulate(0, 40, 500)
r.plotWithLegend(result)
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
14993,
451,
6333,
286,
12737,
13,
198,
37811,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
11,
7297,
198,
11748,
1560,
333,
1505,
355,
573,
198,
198,
19849,
796,
705,
7061,
198,
19849,
7538,
3419,
198,
220,
220,
3373,
797,
4658,
25,
198,
220,
220,
449,
15,
25,
720,
55,
15,
4613,
311,
16,
26,
357,
15996,
16,
1635,
357,
55,
15,
532,
311,
16,
14,
8896,
80,
16,
4008,
29006,
16,
1343,
1395,
15,
1343,
311,
16,
1343,
220,
220,
311,
19,
61,
71,
1776,
198,
220,
220,
449,
16,
25,
311,
16,
4613,
311,
17,
26,
357,
940,
1635,
311,
16,
532,
362,
1635,
311,
17,
8,
1220,
357,
16,
1343,
311,
16,
1343,
311,
17,
1776,
198,
220,
220,
449,
17,
25,
311,
17,
4613,
311,
18,
26,
357,
940,
1635,
311,
17,
532,
362,
1635,
311,
18,
8,
1220,
357,
16,
1343,
311,
17,
1343,
311,
18,
1776,
198,
220,
220,
449,
18,
25,
311,
18,
4613,
311,
19,
26,
357,
940,
1635,
311,
18,
532,
362,
1635,
311,
19,
8,
1220,
357,
16,
1343,
311,
18,
1343,
311,
19,
1776,
198,
220,
220,
449,
19,
25,
311,
19,
4613,
720,
55,
16,
26,
357,
53,
19,
1635,
311,
19,
8,
1220,
357,
27015,
19,
1343,
311,
19,
1776,
628,
220,
3373,
28540,
4238,
4582,
25,
198,
220,
311,
16,
796,
657,
26,
311,
17,
796,
657,
26,
311,
18,
796,
657,
26,
198,
220,
311,
19,
796,
657,
26,
1395,
15,
796,
838,
26,
1395,
16,
796,
657,
26,
628,
220,
3373,
35748,
37588,
25,
198,
220,
16990,
16,
796,
838,
26,
3873,
80,
16,
796,
838,
26,
289,
796,
838,
26,
569,
19,
796,
362,
13,
20,
26,
34172,
19,
796,
657,
13,
20,
26,
198,
437,
7061,
6,
198,
198,
81,
796,
573,
13,
2220,
64,
7,
19849,
8,
198,
20274,
796,
374,
13,
14323,
5039,
7,
15,
11,
2319,
11,
5323,
8,
198,
81,
13,
29487,
3152,
21351,
7,
20274,
8,
198
] | 2.002882 | 347 |
from .users import User, UserCreate, UserUpdate
from .transactions import Transaction, TransactionCreate, TransactionUpdate
from .accounts import Account, AccountList, AccountSingle, AccountCreate, AccountUpdate
from .categories import Category, CategoryCreate, CategoryUpdate | [
6738,
764,
18417,
1330,
11787,
11,
11787,
16447,
11,
11787,
10260,
198,
6738,
764,
7645,
4658,
1330,
45389,
11,
45389,
16447,
11,
45389,
10260,
198,
6738,
764,
23317,
82,
1330,
10781,
11,
10781,
8053,
11,
10781,
28008,
11,
10781,
16447,
11,
10781,
10260,
198,
6738,
764,
66,
26129,
1330,
21743,
11,
21743,
16447,
11,
21743,
10260
] | 4.928571 | 56 |
def method_accepting_cls(cls, self):
# Using plain `super()` is not valid here, since there's no `__class__` cell found
# (Exact exception would be 'RuntimeError: super(): __class__ cell not found')
# Instead, we expect to *not* see a warning about `super-with-arguments`.
# Explicitly passing `cls`, and `self` to `super()` is what's required.
super(cls, self).__init__()
| [
628,
628,
628,
198,
4299,
2446,
62,
13635,
278,
62,
565,
82,
7,
565,
82,
11,
2116,
2599,
198,
220,
220,
220,
1303,
8554,
8631,
4600,
16668,
3419,
63,
318,
407,
4938,
994,
11,
1201,
612,
338,
645,
4600,
834,
4871,
834,
63,
2685,
1043,
198,
220,
220,
220,
1303,
357,
3109,
529,
6631,
561,
307,
705,
41006,
12331,
25,
2208,
33529,
11593,
4871,
834,
2685,
407,
1043,
11537,
198,
220,
220,
220,
1303,
5455,
11,
356,
1607,
284,
1635,
1662,
9,
766,
257,
6509,
546,
4600,
16668,
12,
4480,
12,
853,
2886,
44646,
198,
220,
220,
220,
1303,
11884,
306,
6427,
4600,
565,
82,
47671,
290,
4600,
944,
63,
284,
4600,
16668,
3419,
63,
318,
644,
338,
2672,
13,
198,
220,
220,
220,
2208,
7,
565,
82,
11,
2116,
737,
834,
15003,
834,
3419,
198
] | 2.941176 | 136 |
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
from flask import flash
import numpy as np
| [
11748,
19798,
292,
355,
279,
67,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
384,
397,
1211,
355,
3013,
82,
198,
6738,
1341,
35720,
13,
19849,
62,
49283,
1330,
4512,
62,
9288,
62,
35312,
198,
6738,
1341,
35720,
13,
3866,
36948,
1330,
36052,
27195,
12342,
198,
6738,
1341,
35720,
13,
1072,
11306,
1330,
14534,
34605,
9487,
7483,
198,
6738,
1341,
35720,
13,
4164,
10466,
1330,
9922,
62,
26675,
198,
6738,
42903,
1330,
7644,
198,
11748,
299,
32152,
355,
45941,
628,
628
] | 3.662791 | 86 |
# This version of the bitcoin experiment imports data preprocessed in Matlab, and uses the GCN baseline
# The point of this script is to do link prediction
# Imports and aliases
import pickle
import torch as t
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import torchvision.datasets as datasets
import numpy as np
import matplotlib.pyplot as plt
import cProfile
import pandas as pd
import datetime
from scipy.sparse import csr_matrix
import os.path
import embedding_help_functions as ehf
import scipy.io as sio
unsq = t.unsqueeze
sq = t.squeeze
# Settings
alpha_vec = [.75, .76, .77, .78, .79, .80, .81, .82, .83, .84, .85, .86, .87, .88, .89, .90, .91, .92, .93, .94, .95]
no_layers = 1
dataset = "OTC" # OTC or Alpha
no_epochs = 1000
mat_f_name = "saved_content_bitcoin_otc.mat"
no_trials = 1
beta1 = 19
beta2 = 19
cutoff = 95
eval_type = "MAP-MRR" # "MAP-MRR" or "F1"
data_loc = "data/Bitcoin_" + dataset + "/"
S_train, S_val, S_test = 95, 20, 20
lr = 0.01
momentum = 0.9
# Load and return relevant data
A, A_labels, C_train, C_val, C_test, N = ehf.load_data(data_loc, mat_f_name, S_train, S_val, S_test, transformed=False)
# Create features for the nodes
X_train, X_val, X_test = ehf.create_node_features(A, S_train, S_val, S_test, same_block_size=False)
# Extract edges and labels from A_labels, and augment with nonexisting edges
# edges, beta
edges = A_labels._indices()
edges_aug, labels = ehf.augment_edges(edges, N, beta1, beta2, cutoff)
# Divide adjacency matrices and labels into training, validation and testing sets
edges_train, target_train, e_train, edges_val, target_val, e_val, edges_test, target_test, e_test = ehf.split_data(edges_aug, labels, S_train, S_val, S_test, same_block_size = False)
if no_trials > 1:
ep_acc_loss_vec = []
for tr in range(no_trials):
for alpha in alpha_vec:
class_weights = t.tensor([alpha, 1.0-alpha])
save_res_fname = "results_BASELINE_layers" + str(no_layers) + "_w" + str(round(float(class_weights[0])*100)) + "_" + dataset + "_link_prediction"
# Create gcn for training
if no_layers == 2:
gcn = ehf.EmbeddingKWGCN(C_train[:-1], X_train[:-1], e_train, [6,6,2], nonlin2="selu")
elif no_layers == 1:
gcn = ehf.EmbeddingKWGCN(C_train[:-1], X_train[:-1], e_train, [6,2])
# Train
optimizer = t.optim.SGD(gcn.parameters(), lr=lr, momentum=momentum)
criterion = nn.CrossEntropyLoss(weight=class_weights) # Takes arguments (output, target)
if eval_type == "F1":
ep_acc_loss = np.zeros((no_epochs,12)) # (precision_train, recall_train, f1_train, loss_train, precision_val, recall_val, f1_val, loss_val, precision_test, recall_test, f1_test, loss_test)
elif eval_type == "MAP-MRR":
ep_acc_loss = np.zeros((no_epochs,9)) # (MAP_train, MRR_train, loss_train, MAP_val, MRR_val, loss_val, MAP_test, MRR_test, loss_test)
for ep in range(no_epochs):
# Compute loss and take step
optimizer.zero_grad()
output_train = gcn()
loss_train = criterion(output_train, target_train[edges_train[0]!=0])
loss_train.backward()
optimizer.step()
# Things that don't require gradient
with t.no_grad():
if ep % 100 == 0:
# Compute stats for training data; no point in doing more often than this
guess_train = t.argmax(output_train, dim=1)
if eval_type == "F1":
precision_train, recall_train, f1_train = ehf.compute_f1(guess_train, target_train[edges_train[0]!=0])
elif eval_type == "MAP-MRR":
MAP_train, MRR_train = ehf.compute_MAP_MRR(output_train, target_train[edges_train[0]!=0], edges_train[:, edges_train[0]!=0])
# Compute stats for validation data
output_val = gcn(C_val[:-1], X_val[:-1], e_val)
guess_val = t.argmax(output_val, dim=1)
if eval_type == "F1":
precision_val, recall_val, f1_val = ehf.compute_f1(guess_val, target_val[edges_val[0]!=0])
elif eval_type == "MAP-MRR":
MAP_val, MRR_val = ehf.compute_MAP_MRR(output_val, target_val[edges_val[0]!=0], edges_val[:, edges_val[0]!=0])
loss_val = criterion(output_val, target_val[edges_val[0]!=0])
# Compute stats for test data
output_test = gcn(C_test[:-1], X_test[:-1], e_test)
guess_test = t.argmax(output_test, dim=1)
if eval_type == "F1":
precision_test, recall_test, f1_test = ehf.compute_f1(guess_test, target_test[edges_test[0]!=0])
elif eval_type == "MAP-MRR":
MAP_test, MRR_test = ehf.compute_MAP_MRR(output_test, target_test[edges_test[0]!=0], edges_test[:, edges_test[0]!=0])
loss_test = criterion(output_test, target_test[edges_test[0]!=0])
# Print
if eval_type == "F1":
ehf.print_f1(precision_train, recall_train, f1_train, loss_train, precision_val, recall_val, f1_val, loss_val, precision_test, recall_test, f1_test, loss_test, alpha, tr, ep)
elif eval_type == "MAP-MRR":
print("alpha/Tr/Ep %.2f/%d/%d. Train MAP/MRR %.16f/%.16f. Train loss %.16f." % (alpha, tr, ep, MAP_train, MRR_train, loss_train))
print("alpha/Tr/Ep %.2f/%d/%d. Val MAP/MRR %.16f/%.16f. Val loss %.16f." % (alpha, tr, ep, MAP_val, MRR_val, loss_val))
print("alpha/Tr/Ep %.2f/%d/%d. Test MAP/MRR %.16f/%.16f. Test loss %.16f.\n" % (alpha, tr, ep, MAP_test, MRR_test, loss_test))
# Store values with results
if eval_type == "F1":
ep_acc_loss[ep] = [precision_train, recall_train, f1_train, loss_train, precision_val, recall_val, f1_val, loss_val, precision_test, recall_test, f1_test, loss_test]
elif eval_type == "MAP-MRR":
ep_acc_loss[ep] = [MAP_train, MRR_train, loss_train, MAP_val, MRR_val, loss_val, MAP_test, MRR_test, loss_test]
if eval_type == "F1":
ehf.print_f1(precision_train, recall_train, f1_train, loss_train, precision_val, recall_val, f1_val, loss_val, precision_test, recall_test, f1_test, loss_test, is_final=True)
elif eval_type == "MAP-MRR":
print("FINAL: Train MAP/MRR %.16f/%.16f. Train loss %.16f." % (MAP_train, MRR_train, loss_train))
print("FINAL: Val MAP/MRR %.16f/%.16f. Val loss %.16f." % (MAP_val, MRR_val, loss_val))
print("FINAL: Test MAP/MRR %.16f/%.16f. Test loss %.16f.\n" % (MAP_test, MRR_test, loss_test))
if no_trials == 1:
pickle.dump(ep_acc_loss, open(save_res_fname, "wb"))
print("Results saved for single trial")
else:
ep_acc_loss_vec.append(ep_acc_loss)
if no_trials > 1:
pickle.dump(ep_acc_loss_vec, open(save_res_fname + "_no_trials" + str(no_trials), "wb"))
print("Results saved for all trials") | [
2,
770,
2196,
286,
262,
8550,
6306,
17944,
1366,
662,
14681,
276,
287,
6550,
23912,
11,
290,
3544,
262,
20145,
45,
14805,
198,
2,
383,
966,
286,
428,
4226,
318,
284,
466,
2792,
17724,
198,
198,
2,
1846,
3742,
290,
47217,
198,
11748,
2298,
293,
198,
11748,
28034,
355,
256,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
198,
11748,
28034,
10178,
198,
11748,
28034,
10178,
13,
19608,
292,
1039,
355,
40522,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
269,
37046,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
4818,
8079,
198,
6738,
629,
541,
88,
13,
82,
29572,
1330,
269,
27891,
62,
6759,
8609,
198,
11748,
28686,
13,
6978,
198,
11748,
11525,
12083,
62,
16794,
62,
12543,
2733,
355,
32622,
69,
198,
11748,
629,
541,
88,
13,
952,
355,
264,
952,
198,
13271,
80,
796,
256,
13,
13271,
421,
1453,
2736,
198,
31166,
796,
256,
13,
16485,
1453,
2736,
198,
198,
2,
16163,
198,
26591,
62,
35138,
796,
685,
13,
2425,
11,
764,
4304,
11,
764,
3324,
11,
764,
3695,
11,
764,
3720,
11,
764,
1795,
11,
764,
6659,
11,
764,
6469,
11,
764,
5999,
11,
764,
5705,
11,
764,
5332,
11,
764,
4521,
11,
764,
5774,
11,
764,
3459,
11,
764,
4531,
11,
764,
3829,
11,
764,
6420,
11,
764,
5892,
11,
764,
6052,
11,
764,
5824,
11,
764,
3865,
60,
198,
3919,
62,
75,
6962,
796,
352,
198,
19608,
292,
316,
796,
366,
2394,
34,
1,
1303,
440,
4825,
393,
12995,
198,
3919,
62,
538,
5374,
82,
796,
8576,
198,
6759,
62,
69,
62,
3672,
796,
366,
82,
9586,
62,
11299,
62,
35395,
62,
313,
66,
13,
6759,
1,
198,
3919,
62,
28461,
874,
796,
352,
198,
31361,
16,
796,
678,
198,
31361,
17,
796,
678,
198,
8968,
2364,
796,
6957,
198,
18206,
62,
4906,
796,
366,
33767,
12,
13599,
49,
1,
1303,
366,
33767,
12,
13599,
49,
1,
393,
366,
37,
16,
1,
198,
198,
7890,
62,
17946,
796,
366,
7890,
14,
22614,
62,
1,
1343,
27039,
1343,
12813,
1,
198,
50,
62,
27432,
11,
311,
62,
2100,
11,
311,
62,
9288,
796,
6957,
11,
1160,
11,
1160,
198,
14050,
796,
657,
13,
486,
198,
32542,
298,
388,
796,
657,
13,
24,
198,
198,
2,
8778,
290,
1441,
5981,
1366,
198,
32,
11,
317,
62,
23912,
1424,
11,
327,
62,
27432,
11,
327,
62,
2100,
11,
327,
62,
9288,
11,
399,
796,
32622,
69,
13,
2220,
62,
7890,
7,
7890,
62,
17946,
11,
2603,
62,
69,
62,
3672,
11,
311,
62,
27432,
11,
311,
62,
2100,
11,
311,
62,
9288,
11,
14434,
28,
25101,
8,
198,
198,
2,
13610,
3033,
329,
262,
13760,
198,
55,
62,
27432,
11,
1395,
62,
2100,
11,
1395,
62,
9288,
796,
32622,
69,
13,
17953,
62,
17440,
62,
40890,
7,
32,
11,
311,
62,
27432,
11,
311,
62,
2100,
11,
311,
62,
9288,
11,
976,
62,
9967,
62,
7857,
28,
25101,
8,
198,
198,
2,
29677,
13015,
290,
14722,
422,
317,
62,
23912,
1424,
11,
290,
35016,
351,
36196,
9665,
13015,
198,
2,
13015,
11,
12159,
198,
276,
3212,
796,
317,
62,
23912,
1424,
13557,
521,
1063,
3419,
198,
276,
3212,
62,
7493,
11,
14722,
796,
32622,
69,
13,
559,
5154,
62,
276,
3212,
7,
276,
3212,
11,
399,
11,
12159,
16,
11,
12159,
17,
11,
45616,
8,
198,
198,
2,
46894,
9224,
330,
1387,
2603,
45977,
290,
14722,
656,
3047,
11,
21201,
290,
4856,
5621,
198,
276,
3212,
62,
27432,
11,
2496,
62,
27432,
11,
304,
62,
27432,
11,
13015,
62,
2100,
11,
2496,
62,
2100,
11,
304,
62,
2100,
11,
13015,
62,
9288,
11,
2496,
62,
9288,
11,
304,
62,
9288,
796,
32622,
69,
13,
35312,
62,
7890,
7,
276,
3212,
62,
7493,
11,
14722,
11,
311,
62,
27432,
11,
311,
62,
2100,
11,
311,
62,
9288,
11,
976,
62,
9967,
62,
7857,
796,
10352,
8,
198,
198,
361,
645,
62,
28461,
874,
1875,
352,
25,
198,
197,
538,
62,
4134,
62,
22462,
62,
35138,
796,
17635,
198,
198,
1640,
491,
287,
2837,
7,
3919,
62,
28461,
874,
2599,
198,
197,
1640,
17130,
287,
17130,
62,
35138,
25,
198,
197,
197,
4871,
62,
43775,
796,
256,
13,
83,
22854,
26933,
26591,
11,
352,
13,
15,
12,
26591,
12962,
198,
197,
197,
21928,
62,
411,
62,
69,
3672,
796,
366,
43420,
62,
33,
1921,
3698,
8881,
62,
75,
6962,
1,
1343,
965,
7,
3919,
62,
75,
6962,
8,
1343,
45434,
86,
1,
1343,
965,
7,
744,
7,
22468,
7,
4871,
62,
43775,
58,
15,
12962,
9,
3064,
4008,
1343,
45434,
1,
1343,
27039,
1343,
45434,
8726,
62,
28764,
2867,
1,
628,
197,
197,
2,
13610,
308,
31522,
329,
3047,
198,
197,
197,
361,
645,
62,
75,
6962,
6624,
362,
25,
198,
197,
197,
197,
70,
31522,
796,
32622,
69,
13,
31567,
6048,
278,
42,
54,
15916,
45,
7,
34,
62,
27432,
58,
21912,
16,
4357,
1395,
62,
27432,
58,
21912,
16,
4357,
304,
62,
27432,
11,
685,
21,
11,
21,
11,
17,
4357,
1729,
2815,
17,
2625,
741,
84,
4943,
198,
197,
197,
417,
361,
645,
62,
75,
6962,
6624,
352,
25,
198,
197,
197,
197,
70,
31522,
796,
32622,
69,
13,
31567,
6048,
278,
42,
54,
15916,
45,
7,
34,
62,
27432,
58,
21912,
16,
4357,
1395,
62,
27432,
58,
21912,
16,
4357,
304,
62,
27432,
11,
685,
21,
11,
17,
12962,
628,
197,
197,
2,
16835,
198,
197,
197,
40085,
7509,
796,
256,
13,
40085,
13,
38475,
35,
7,
70,
31522,
13,
17143,
7307,
22784,
300,
81,
28,
14050,
11,
12858,
28,
32542,
298,
388,
8,
198,
197,
197,
22213,
28019,
796,
299,
77,
13,
21544,
14539,
28338,
43,
793,
7,
6551,
28,
4871,
62,
43775,
8,
1303,
33687,
7159,
357,
22915,
11,
2496,
8,
198,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
538,
62,
4134,
62,
22462,
796,
45941,
13,
9107,
418,
19510,
3919,
62,
538,
5374,
82,
11,
1065,
4008,
1303,
357,
3866,
16005,
62,
27432,
11,
10014,
62,
27432,
11,
277,
16,
62,
27432,
11,
2994,
62,
27432,
11,
15440,
62,
2100,
11,
10014,
62,
2100,
11,
277,
16,
62,
2100,
11,
2994,
62,
2100,
11,
15440,
62,
9288,
11,
10014,
62,
9288,
11,
277,
16,
62,
9288,
11,
2994,
62,
9288,
8,
198,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
538,
62,
4134,
62,
22462,
796,
45941,
13,
9107,
418,
19510,
3919,
62,
538,
5374,
82,
11,
24,
4008,
1303,
357,
33767,
62,
27432,
11,
17242,
49,
62,
27432,
11,
2994,
62,
27432,
11,
34645,
62,
2100,
11,
17242,
49,
62,
2100,
11,
2994,
62,
2100,
11,
34645,
62,
9288,
11,
17242,
49,
62,
9288,
11,
2994,
62,
9288,
8,
628,
197,
197,
1640,
2462,
287,
2837,
7,
3919,
62,
538,
5374,
82,
2599,
198,
197,
197,
197,
2,
3082,
1133,
2994,
290,
1011,
2239,
198,
197,
197,
197,
40085,
7509,
13,
22570,
62,
9744,
3419,
198,
197,
197,
197,
22915,
62,
27432,
796,
308,
31522,
3419,
198,
197,
197,
197,
22462,
62,
27432,
796,
34054,
7,
22915,
62,
27432,
11,
2496,
62,
27432,
58,
276,
3212,
62,
27432,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
22462,
62,
27432,
13,
1891,
904,
3419,
198,
197,
197,
197,
40085,
7509,
13,
9662,
3419,
628,
197,
197,
197,
2,
11597,
326,
836,
470,
2421,
31312,
198,
197,
197,
197,
4480,
256,
13,
3919,
62,
9744,
33529,
198,
197,
197,
197,
197,
361,
2462,
4064,
1802,
6624,
657,
25,
198,
197,
197,
197,
197,
197,
2,
3082,
1133,
9756,
329,
3047,
1366,
26,
645,
966,
287,
1804,
517,
1690,
621,
428,
198,
197,
197,
197,
197,
197,
5162,
408,
62,
27432,
796,
256,
13,
853,
9806,
7,
22915,
62,
27432,
11,
5391,
28,
16,
8,
198,
197,
197,
197,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
197,
197,
197,
3866,
16005,
62,
27432,
11,
10014,
62,
27432,
11,
277,
16,
62,
27432,
796,
32622,
69,
13,
5589,
1133,
62,
69,
16,
7,
5162,
408,
62,
27432,
11,
2496,
62,
27432,
58,
276,
3212,
62,
27432,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
197,
197,
197,
33767,
62,
27432,
11,
17242,
49,
62,
27432,
796,
32622,
69,
13,
5589,
1133,
62,
33767,
62,
13599,
49,
7,
22915,
62,
27432,
11,
2496,
62,
27432,
58,
276,
3212,
62,
27432,
58,
15,
60,
0,
28,
15,
4357,
13015,
62,
27432,
58,
45299,
13015,
62,
27432,
58,
15,
60,
0,
28,
15,
12962,
628,
197,
197,
197,
197,
197,
2,
3082,
1133,
9756,
329,
21201,
1366,
198,
197,
197,
197,
197,
197,
22915,
62,
2100,
796,
308,
31522,
7,
34,
62,
2100,
58,
21912,
16,
4357,
1395,
62,
2100,
58,
21912,
16,
4357,
304,
62,
2100,
8,
198,
197,
197,
197,
197,
197,
5162,
408,
62,
2100,
796,
256,
13,
853,
9806,
7,
22915,
62,
2100,
11,
5391,
28,
16,
8,
198,
197,
197,
197,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
197,
197,
197,
3866,
16005,
62,
2100,
11,
10014,
62,
2100,
11,
277,
16,
62,
2100,
796,
32622,
69,
13,
5589,
1133,
62,
69,
16,
7,
5162,
408,
62,
2100,
11,
2496,
62,
2100,
58,
276,
3212,
62,
2100,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
197,
197,
197,
33767,
62,
2100,
11,
17242,
49,
62,
2100,
796,
32622,
69,
13,
5589,
1133,
62,
33767,
62,
13599,
49,
7,
22915,
62,
2100,
11,
2496,
62,
2100,
58,
276,
3212,
62,
2100,
58,
15,
60,
0,
28,
15,
4357,
13015,
62,
2100,
58,
45299,
13015,
62,
2100,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
22462,
62,
2100,
796,
34054,
7,
22915,
62,
2100,
11,
2496,
62,
2100,
58,
276,
3212,
62,
2100,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
198,
197,
197,
197,
197,
197,
2,
3082,
1133,
9756,
329,
1332,
1366,
198,
197,
197,
197,
197,
197,
22915,
62,
9288,
796,
308,
31522,
7,
34,
62,
9288,
58,
21912,
16,
4357,
1395,
62,
9288,
58,
21912,
16,
4357,
304,
62,
9288,
8,
198,
197,
197,
197,
197,
197,
5162,
408,
62,
9288,
796,
256,
13,
853,
9806,
7,
22915,
62,
9288,
11,
5391,
28,
16,
8,
198,
197,
197,
197,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
197,
197,
197,
3866,
16005,
62,
9288,
11,
10014,
62,
9288,
11,
277,
16,
62,
9288,
796,
32622,
69,
13,
5589,
1133,
62,
69,
16,
7,
5162,
408,
62,
9288,
11,
2496,
62,
9288,
58,
276,
3212,
62,
9288,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
197,
197,
197,
33767,
62,
9288,
11,
17242,
49,
62,
9288,
796,
32622,
69,
13,
5589,
1133,
62,
33767,
62,
13599,
49,
7,
22915,
62,
9288,
11,
2496,
62,
9288,
58,
276,
3212,
62,
9288,
58,
15,
60,
0,
28,
15,
4357,
13015,
62,
9288,
58,
45299,
13015,
62,
9288,
58,
15,
60,
0,
28,
15,
12962,
198,
197,
197,
197,
197,
197,
22462,
62,
9288,
796,
34054,
7,
22915,
62,
9288,
11,
2496,
62,
9288,
58,
276,
3212,
62,
9288,
58,
15,
60,
0,
28,
15,
12962,
628,
197,
197,
197,
197,
197,
2,
12578,
198,
197,
197,
197,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
197,
197,
197,
17231,
69,
13,
4798,
62,
69,
16,
7,
3866,
16005,
62,
27432,
11,
10014,
62,
27432,
11,
277,
16,
62,
27432,
11,
2994,
62,
27432,
11,
15440,
62,
2100,
11,
10014,
62,
2100,
11,
277,
16,
62,
2100,
11,
2994,
62,
2100,
11,
15440,
62,
9288,
11,
10014,
62,
9288,
11,
277,
16,
62,
9288,
11,
2994,
62,
9288,
11,
17130,
11,
491,
11,
2462,
8,
198,
197,
197,
197,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
197,
197,
197,
4798,
7203,
26591,
14,
2898,
14,
13807,
4064,
13,
17,
69,
14,
4,
67,
14,
4,
67,
13,
16835,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
16835,
2994,
4064,
13,
1433,
69,
526,
4064,
357,
26591,
11,
491,
11,
2462,
11,
34645,
62,
27432,
11,
17242,
49,
62,
27432,
11,
2994,
62,
27432,
4008,
198,
197,
197,
197,
197,
197,
197,
4798,
7203,
26591,
14,
2898,
14,
13807,
4064,
13,
17,
69,
14,
4,
67,
14,
4,
67,
13,
3254,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
3254,
2994,
4064,
13,
1433,
69,
526,
4064,
357,
26591,
11,
491,
11,
2462,
11,
34645,
62,
2100,
11,
17242,
49,
62,
2100,
11,
2994,
62,
2100,
4008,
198,
197,
197,
197,
197,
197,
197,
4798,
7203,
26591,
14,
2898,
14,
13807,
4064,
13,
17,
69,
14,
4,
67,
14,
4,
67,
13,
6208,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
6208,
2994,
4064,
13,
1433,
69,
13,
59,
77,
1,
4064,
357,
26591,
11,
491,
11,
2462,
11,
34645,
62,
9288,
11,
17242,
49,
62,
9288,
11,
2994,
62,
9288,
4008,
628,
197,
197,
197,
197,
2,
9363,
3815,
351,
2482,
198,
197,
197,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
197,
197,
197,
197,
197,
197,
197,
198,
197,
197,
197,
197,
197,
538,
62,
4134,
62,
22462,
58,
538,
60,
796,
685,
3866,
16005,
62,
27432,
11,
10014,
62,
27432,
11,
277,
16,
62,
27432,
11,
2994,
62,
27432,
11,
15440,
62,
2100,
11,
10014,
62,
2100,
11,
277,
16,
62,
2100,
11,
2994,
62,
2100,
11,
15440,
62,
9288,
11,
10014,
62,
9288,
11,
277,
16,
62,
9288,
11,
2994,
62,
9288,
60,
198,
197,
197,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
197,
197,
538,
62,
4134,
62,
22462,
58,
538,
60,
796,
685,
33767,
62,
27432,
11,
17242,
49,
62,
27432,
11,
2994,
62,
27432,
11,
34645,
62,
2100,
11,
17242,
49,
62,
2100,
11,
2994,
62,
2100,
11,
34645,
62,
9288,
11,
17242,
49,
62,
9288,
11,
2994,
62,
9288,
60,
628,
197,
197,
361,
5418,
62,
4906,
6624,
366,
37,
16,
1298,
198,
197,
197,
197,
17231,
69,
13,
4798,
62,
69,
16,
7,
3866,
16005,
62,
27432,
11,
10014,
62,
27432,
11,
277,
16,
62,
27432,
11,
2994,
62,
27432,
11,
15440,
62,
2100,
11,
10014,
62,
2100,
11,
277,
16,
62,
2100,
11,
2994,
62,
2100,
11,
15440,
62,
9288,
11,
10014,
62,
9288,
11,
277,
16,
62,
9288,
11,
2994,
62,
9288,
11,
318,
62,
20311,
28,
17821,
8,
198,
197,
197,
417,
361,
5418,
62,
4906,
6624,
366,
33767,
12,
13599,
49,
1298,
198,
197,
197,
197,
4798,
7203,
37,
17961,
25,
16835,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
16835,
2994,
4064,
13,
1433,
69,
526,
4064,
357,
33767,
62,
27432,
11,
17242,
49,
62,
27432,
11,
2994,
62,
27432,
4008,
198,
197,
197,
197,
4798,
7203,
37,
17961,
25,
3254,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
3254,
2994,
4064,
13,
1433,
69,
526,
4064,
357,
33767,
62,
2100,
11,
17242,
49,
62,
2100,
11,
2994,
62,
2100,
4008,
198,
197,
197,
197,
4798,
7203,
37,
17961,
25,
6208,
34645,
14,
13599,
49,
4064,
13,
1433,
69,
14,
7225,
1433,
69,
13,
6208,
2994,
4064,
13,
1433,
69,
13,
59,
77,
1,
4064,
357,
33767,
62,
9288,
11,
17242,
49,
62,
9288,
11,
2994,
62,
9288,
4008,
628,
197,
197,
361,
645,
62,
28461,
874,
6624,
352,
25,
198,
197,
197,
197,
27729,
293,
13,
39455,
7,
538,
62,
4134,
62,
22462,
11,
1280,
7,
21928,
62,
411,
62,
69,
3672,
11,
366,
39346,
48774,
198,
197,
197,
197,
4798,
7203,
25468,
7448,
329,
2060,
4473,
4943,
198,
197,
197,
17772,
25,
198,
197,
197,
197,
538,
62,
4134,
62,
22462,
62,
35138,
13,
33295,
7,
538,
62,
4134,
62,
22462,
8,
198,
198,
361,
645,
62,
28461,
874,
1875,
352,
25,
198,
197,
27729,
293,
13,
39455,
7,
538,
62,
4134,
62,
22462,
62,
35138,
11,
1280,
7,
21928,
62,
411,
62,
69,
3672,
1343,
45434,
3919,
62,
28461,
874,
1,
1343,
965,
7,
3919,
62,
28461,
874,
828,
366,
39346,
48774,
198,
197,
4798,
7203,
25468,
7448,
329,
477,
9867,
4943
] | 2.290851 | 2,809 |
import cPickle
import numpy as np
from elm import ELMClassifier
from sklearn import linear_model
if __name__ == '__main__':
# Load data sets
train_x, train_y, val_x, val_y, test_x, test_y = get_datasets(load_mnist())
# Build ELM
cls = ELMClassifier(n_hidden=7000,
alpha=0.93,
activation_func='multiquadric',
regressor=linear_model.Ridge(),
random_state=21398023)
cls.fit(train_x, train_y)
# Evaluate model
print 'Validation error:', cls.score(val_x, val_y)
print 'Test error:', cls.score(test_x, test_y)
| [
11748,
269,
31686,
293,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
1288,
76,
1330,
17852,
44,
9487,
7483,
198,
6738,
1341,
35720,
1330,
14174,
62,
19849,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1303,
8778,
1366,
5621,
198,
220,
220,
220,
4512,
62,
87,
11,
4512,
62,
88,
11,
1188,
62,
87,
11,
1188,
62,
88,
11,
1332,
62,
87,
11,
1332,
62,
88,
796,
651,
62,
19608,
292,
1039,
7,
2220,
62,
10295,
396,
28955,
198,
220,
220,
220,
1303,
10934,
17852,
44,
198,
220,
220,
220,
537,
82,
796,
17852,
44,
9487,
7483,
7,
77,
62,
30342,
28,
22,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17130,
28,
15,
13,
6052,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14916,
62,
20786,
11639,
16680,
1557,
324,
1173,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
842,
44292,
28,
29127,
62,
19849,
13,
49,
3130,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4738,
62,
5219,
28,
17,
20219,
1795,
1954,
8,
198,
220,
220,
220,
537,
82,
13,
11147,
7,
27432,
62,
87,
11,
4512,
62,
88,
8,
198,
220,
220,
220,
1303,
26439,
4985,
2746,
198,
220,
220,
220,
3601,
705,
7762,
24765,
4049,
25,
3256,
537,
82,
13,
26675,
7,
2100,
62,
87,
11,
1188,
62,
88,
8,
198,
220,
220,
220,
3601,
705,
14402,
4049,
25,
3256,
537,
82,
13,
26675,
7,
9288,
62,
87,
11,
1332,
62,
88,
8,
198
] | 2.006309 | 317 |
# -*- coding: utf-8 -*-
#!/usr/bin/env python3
from PKC_Classes import NetworkUser, KDC
from DES import DES
from RSA_Class import RSA
import socket
import os
import sys
import threading
import time
if sys.version_info[0] < 3:
raise Exception("Must be using Python 3")
bob = NetworkUser('Alice', DES(), RSA(9973, 97), 200)
print('bob:', bob.uid)
# socket communication
kdc_host, kdc_port = 'localhost', 9999
bob_host, bob_port = 'localhost', 9200
# talk to kdc for sess key
try:
sock_with_kdc = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock_with_kdc.connect((kdc_host, kdc_port))
print(sock_with_kdc.recv(1024))
# send cipher_key
bob_cipher_key_packet = bob.send_cipher_key()
sock_with_kdc.send(bob_cipher_key_packet.encode())
kdc_bob_cipher_key_packet = sock_with_kdc.recv(1024).decode()
print(kdc_bob_cipher_key_packet)
bob.process_packet(kdc_bob_cipher_key_packet)
except socket.error as msg:
print(msg);
sys.exit(1)
# sock_with_kdc.shutdown(socket.SHUT_WR)
# talk to bob
try:
sock_self = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock_self.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
sock_self.bind((bob_host, bob_port))
sock_self.listen(10)
except socket.error as msg:
print(msg);
sys.exit(1)
while 1:
conn, addr = sock_self.accept()
thread = threading.Thread(target=reply_conn, args=(conn, addr))
thread.start()
# sock_self.close()
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
6738,
29673,
34,
62,
9487,
274,
1330,
7311,
12982,
11,
509,
9697,
198,
6738,
22196,
1330,
22196,
198,
6738,
42319,
62,
9487,
1330,
42319,
198,
198,
11748,
17802,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
4704,
278,
198,
11748,
640,
198,
198,
361,
25064,
13,
9641,
62,
10951,
58,
15,
60,
1279,
513,
25,
198,
220,
220,
220,
5298,
35528,
7203,
34320,
307,
1262,
11361,
513,
4943,
198,
198,
65,
672,
796,
7311,
12982,
10786,
44484,
3256,
22196,
22784,
42319,
7,
2079,
4790,
11,
10111,
828,
939,
8,
198,
4798,
10786,
65,
672,
25,
3256,
29202,
13,
27112,
8,
198,
2,
17802,
6946,
198,
74,
17896,
62,
4774,
11,
479,
17896,
62,
634,
796,
705,
36750,
3256,
860,
17032,
198,
65,
672,
62,
4774,
11,
29202,
62,
634,
796,
705,
36750,
3256,
860,
2167,
198,
2,
1561,
284,
479,
17896,
329,
264,
408,
1994,
198,
28311,
25,
198,
220,
220,
220,
32263,
62,
4480,
62,
74,
17896,
796,
17802,
13,
44971,
7,
44971,
13,
8579,
62,
1268,
2767,
11,
17802,
13,
50,
11290,
62,
2257,
32235,
8,
198,
220,
220,
220,
32263,
62,
4480,
62,
74,
17896,
13,
8443,
19510,
74,
17896,
62,
4774,
11,
479,
17896,
62,
634,
4008,
198,
220,
220,
220,
3601,
7,
82,
735,
62,
4480,
62,
74,
17896,
13,
8344,
85,
7,
35500,
4008,
198,
220,
220,
220,
1303,
3758,
38012,
62,
2539,
198,
220,
220,
220,
29202,
62,
66,
10803,
62,
2539,
62,
8002,
316,
796,
29202,
13,
21280,
62,
66,
10803,
62,
2539,
3419,
198,
220,
220,
220,
32263,
62,
4480,
62,
74,
17896,
13,
21280,
7,
65,
672,
62,
66,
10803,
62,
2539,
62,
8002,
316,
13,
268,
8189,
28955,
628,
220,
220,
220,
479,
17896,
62,
65,
672,
62,
66,
10803,
62,
2539,
62,
8002,
316,
796,
32263,
62,
4480,
62,
74,
17896,
13,
8344,
85,
7,
35500,
737,
12501,
1098,
3419,
198,
220,
220,
220,
3601,
7,
74,
17896,
62,
65,
672,
62,
66,
10803,
62,
2539,
62,
8002,
316,
8,
198,
220,
220,
220,
29202,
13,
14681,
62,
8002,
316,
7,
74,
17896,
62,
65,
672,
62,
66,
10803,
62,
2539,
62,
8002,
316,
8,
198,
198,
16341,
17802,
13,
18224,
355,
31456,
25,
198,
220,
220,
220,
3601,
7,
19662,
1776,
198,
220,
220,
220,
25064,
13,
37023,
7,
16,
8,
198,
198,
2,
32263,
62,
4480,
62,
74,
17896,
13,
49625,
2902,
7,
44971,
13,
9693,
3843,
62,
18564,
8,
198,
198,
2,
1561,
284,
29202,
198,
28311,
25,
198,
220,
220,
220,
32263,
62,
944,
796,
17802,
13,
44971,
7,
44971,
13,
8579,
62,
1268,
2767,
11,
17802,
13,
50,
11290,
62,
2257,
32235,
8,
198,
220,
220,
220,
32263,
62,
944,
13,
28709,
735,
8738,
7,
44971,
13,
50,
3535,
62,
50,
11290,
2767,
11,
17802,
13,
15821,
62,
2200,
19108,
2885,
7707,
11,
352,
8,
198,
220,
220,
220,
32263,
62,
944,
13,
21653,
19510,
65,
672,
62,
4774,
11,
29202,
62,
634,
4008,
198,
220,
220,
220,
32263,
62,
944,
13,
4868,
268,
7,
940,
8,
198,
198,
16341,
17802,
13,
18224,
355,
31456,
25,
198,
220,
220,
220,
3601,
7,
19662,
1776,
198,
220,
220,
220,
25064,
13,
37023,
7,
16,
8,
198,
198,
4514,
352,
25,
198,
220,
220,
220,
48260,
11,
37817,
796,
32263,
62,
944,
13,
13635,
3419,
198,
220,
220,
220,
4704,
796,
4704,
278,
13,
16818,
7,
16793,
28,
47768,
62,
37043,
11,
26498,
16193,
37043,
11,
37817,
4008,
198,
220,
220,
220,
4704,
13,
9688,
3419,
198,
198,
2,
32263,
62,
944,
13,
19836,
3419,
198
] | 2.368506 | 616 |
from __future__ import print_function
import argparse
import itertools
import os
import pickle
import sys
from datetime import datetime
import matplotlib
import numpy as np
import torch
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import proj.archs as archs
from proj.utils.cluster.general import config_to_str, get_opt, update_lr
from proj.utils.cluster.baselines.triplets import make_triplets_data, \
triplets_eval, triplets_loss
"""
Triplets.
Makes output distribution same as that of attractor, and different to that
of repeller.
Greyscale version (no sobel).
"""
# Options ----------------------------------------------------------------------
parser = argparse.ArgumentParser()
parser.add_argument("--model_ind", type=int, required=True)
parser.add_argument("--arch", type=str, required=True)
parser.add_argument("--opt", type=str, default="Adam")
parser.add_argument("--dataset", type=str, required=True)
parser.add_argument("--dataset_root", type=str, required=True)
parser.add_argument("--gt_k", type=int, required=True)
parser.add_argument("--output_k", type=int, required=True)
parser.add_argument("--lr", type=float, default=0.01)
parser.add_argument("--lr_schedule", type=int, nargs="+", default=[])
parser.add_argument("--lr_mult", type=float, default=0.1)
parser.add_argument("--num_epochs", type=int, default=1000)
parser.add_argument("--batch_sz", type=int, required=True) # num pairs
parser.add_argument("--out_root", type=str,
default="/scratch/shared/slow/xuji/iid_private")
parser.add_argument("--restart", dest="restart", default=False,
action="store_true")
parser.add_argument("--test_code", dest="test_code", default=False,
action="store_true")
parser.add_argument("--save_freq", type=int, default=10)
parser.add_argument("--kmeans_on_features", default=False,
action="store_true")
# transforms
# used for "positive" sample
parser.add_argument("--demean", dest="demean", default=False,
action="store_true")
parser.add_argument("--per_img_demean", dest="per_img_demean", default=False,
action="store_true")
parser.add_argument("--data_mean", type=float, nargs="+",
default=[0.5, 0.5, 0.5])
parser.add_argument("--data_std", type=float, nargs="+",
default=[0.5, 0.5, 0.5])
parser.add_argument("--crop_orig", dest="crop_orig", default=False,
action="store_true")
parser.add_argument("--crop_other", dest="crop_other", default=False,
action="store_true")
parser.add_argument("--tf1_crop", type=str, default="random") # type name
parser.add_argument("--tf2_crop", type=str, default="random")
parser.add_argument("--tf1_crop_sz", type=int, default=84)
parser.add_argument("--tf2_crop_szs", type=int, nargs="+",
default=[84]) # allow diff crop for imgs_tf
parser.add_argument("--tf3_crop_diff", dest="tf3_crop_diff", default=False,
action="store_true")
parser.add_argument("--tf3_crop_sz", type=int, default=0)
parser.add_argument("--input_sz", type=int, default=96)
parser.add_argument("--rot_val", type=float, default=0.)
parser.add_argument("--always_rot", dest="always_rot", default=False,
action="store_true")
parser.add_argument("--no_jitter", dest="no_jitter", default=False,
action="store_true")
parser.add_argument("--no_flip", dest="no_flip", default=False,
action="store_true")
config = parser.parse_args()
# Fixed settings and checks ----------------------------------------------------
config.in_channels = 1
if config.output_k != config.gt_k:
assert (config.output_k > config.gt_k)
assert (config.kmeans_on_features)
config.out_dir = os.path.join(config.out_root, str(config.model_ind))
config.dataloader_batch_sz = config.batch_sz
config.num_dataloaders = 1
if not os.path.exists(config.out_dir):
os.makedirs(config.out_dir)
if config.restart:
given_config = config
reloaded_config_path = os.path.join(given_config.out_dir, "config.pickle")
print("Loading restarting config from: %s" % reloaded_config_path)
with open(reloaded_config_path, "rb") as config_f:
config = pickle.load(config_f)
assert (config.model_ind == given_config.model_ind)
config.restart = True
# copy over new num_epochs and lr schedule
config.num_epochs = given_config.num_epochs
config.lr_schedule = given_config.lr_schedule
if not hasattr(config, "kmeans_on_features"):
config.kmeans_on_features = False
else:
print("Config: %s" % config_to_str(config))
# Data, nets, optimisers -------------------------------------------------------
dataloader_original, dataloader_positive, dataloader_negative, \
dataloader_test = make_triplets_data(config)
train_dataloaders = [dataloader_original, dataloader_positive,
dataloader_negative]
net = archs.__dict__[config.arch](config)
if config.restart:
model_path = os.path.join(config.out_dir, "latest_net.pytorch")
taking_best = not os.path.exists(model_path)
if taking_best:
print("using best instead of latest")
model_path = os.path.join(config.out_dir, "best_net.pytorch")
net.load_state_dict(
torch.load(model_path, map_location=lambda storage, loc: storage))
net.cuda()
net = torch.nn.DataParallel(net)
net.train()
optimiser = get_opt(config.opt)(net.module.parameters(), lr=config.lr)
if config.restart:
opt_path = os.path.join(config.out_dir, "latest_optimiser.pytorch")
if taking_best:
opt_path = os.path.join(config.out_dir, "best_optimiser.pytorch")
optimiser.load_state_dict(torch.load(opt_path))
# Results storage --------------------------------------------------------------
if config.restart:
if not taking_best:
next_epoch = config.last_epoch + 1 # corresponds to last saved model
else:
next_epoch = np.argmax(np.array(config.epoch_acc)) + 1
print("starting from epoch %d" % next_epoch)
config.epoch_acc = config.epoch_acc[:next_epoch] # in case we overshot
config.epoch_loss = config.epoch_loss[:next_epoch]
config.masses = config.masses[:next_epoch, :]
config.per_class_acc = config.per_class_acc[:next_epoch, :]
else:
config.epoch_acc = []
config.epoch_loss = []
config.masses = None
config.per_class_acc = None
_ = triplets_eval(config, net,
dataloader_test=dataloader_test,
sobel=False)
print("Pre: time %s: \n %s" % (datetime.now(), config.epoch_acc[-1]))
sys.stdout.flush()
next_epoch = 1
fig, axarr = plt.subplots(4, sharex=False, figsize=(20, 20))
# Train ------------------------------------------------------------------------
for e_i in xrange(next_epoch, config.num_epochs):
print("Starting e_i: %d" % (e_i))
if e_i in config.lr_schedule:
optimiser = update_lr(optimiser, lr_mult=config.lr_mult)
avg_loss = 0. # over heads and head_epochs (and sub_heads)
avg_loss_count = 0
sys.stdout.flush()
iterators = (d for d in train_dataloaders)
b_i = 0
for tup in itertools.izip(*iterators):
net.module.zero_grad()
imgs_orig = tup[0][0].cuda()
imgs_pos = tup[1][0].cuda()
imgs_neg = tup[2][0].cuda()
outs_orig = net(imgs_orig)
outs_pos = net(imgs_pos)
outs_neg = net(imgs_neg)
curr_loss = triplets_loss(outs_orig, outs_pos, outs_neg)
if ((b_i % 100) == 0) or (e_i == next_epoch and b_i < 10):
print("Model ind %d epoch %d batch %d "
"loss %f time %s" % \
(config.model_ind, e_i, b_i, curr_loss.item(), datetime.now()))
sys.stdout.flush()
if not np.isfinite(float(curr_loss.item())):
print("Loss is not finite... %s:" % str(curr_loss.item()))
exit(1)
avg_loss += curr_loss.item()
avg_loss_count += 1
curr_loss.backward()
optimiser.step()
b_i += 1
if b_i == 2 and config.test_code:
break
avg_loss = float(avg_loss / avg_loss_count)
config.epoch_loss.append(avg_loss)
# Eval and storage -----------------------------------------------------------
# when epoch over both heads is finished
is_best = triplets_eval(config, net,
dataloader_test=dataloader_test,
sobel=False)
print("Time %s, acc %s" % (datetime.now(), config.epoch_acc[-1]))
sys.stdout.flush()
axarr[0].clear()
axarr[0].plot(config.epoch_acc)
axarr[0].set_title("acc, top: %f" % max(config.epoch_acc))
axarr[1].clear()
axarr[1].plot(config.epoch_loss)
axarr[1].set_title("Loss")
axarr[2].clear()
for c in xrange(config.gt_k):
axarr[2].plot(config.masses[:, c])
axarr[2].set_title("masses")
axarr[3].clear()
for c in xrange(config.gt_k):
axarr[3].plot(config.per_class_acc[:, c])
axarr[3].set_title("per_class_acc")
fig.tight_layout()
fig.canvas.draw_idle()
fig.savefig(os.path.join(config.out_dir, "plots.png"))
if is_best or (e_i % config.save_freq == 0):
net.module.cpu()
if is_best:
torch.save(net.module.state_dict(),
os.path.join(config.out_dir, "best_net.pytorch"))
torch.save(optimiser.state_dict(),
os.path.join(config.out_dir, "best_optimiser.pytorch"))
if e_i % config.save_freq == 0:
torch.save(net.module.state_dict(),
os.path.join(config.out_dir, "latest_net.pytorch"))
torch.save(optimiser.state_dict(),
os.path.join(config.out_dir, "latest_optimiser.pytorch"))
config.last_epoch = e_i # for last saved version
net.module.cuda()
with open(os.path.join(config.out_dir, "config.pickle"),
'wb') as outfile:
pickle.dump(config, outfile)
with open(os.path.join(config.out_dir, "config.txt"),
"w") as text_file:
text_file.write("%s" % config)
if config.test_code:
exit(0)
| [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
1822,
29572,
198,
11748,
340,
861,
10141,
198,
11748,
28686,
198,
11748,
2298,
293,
198,
11748,
25064,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
11748,
2603,
29487,
8019,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
198,
6759,
29487,
8019,
13,
1904,
10786,
46384,
11537,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
198,
11748,
386,
73,
13,
34592,
355,
3934,
82,
198,
6738,
386,
73,
13,
26791,
13,
565,
5819,
13,
24622,
1330,
4566,
62,
1462,
62,
2536,
11,
651,
62,
8738,
11,
4296,
62,
14050,
198,
6738,
386,
73,
13,
26791,
13,
565,
5819,
13,
12093,
20655,
13,
28461,
46916,
1330,
787,
62,
28461,
46916,
62,
7890,
11,
3467,
198,
220,
220,
220,
15055,
912,
62,
18206,
11,
15055,
912,
62,
22462,
198,
198,
37811,
198,
220,
19817,
912,
13,
198,
220,
27433,
5072,
6082,
976,
355,
326,
286,
4729,
273,
11,
290,
1180,
284,
326,
220,
198,
220,
286,
3172,
6051,
13,
198,
220,
11955,
28349,
1000,
2196,
357,
3919,
523,
6667,
737,
198,
37811,
198,
198,
2,
18634,
16529,
23031,
198,
198,
48610,
796,
1822,
29572,
13,
28100,
1713,
46677,
3419,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
19849,
62,
521,
1600,
2099,
28,
600,
11,
2672,
28,
17821,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
998,
1600,
2099,
28,
2536,
11,
2672,
28,
17821,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
8738,
1600,
2099,
28,
2536,
11,
4277,
2625,
23159,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
19608,
292,
316,
1600,
2099,
28,
2536,
11,
2672,
28,
17821,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
19608,
292,
316,
62,
15763,
1600,
2099,
28,
2536,
11,
2672,
28,
17821,
8,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
13655,
62,
74,
1600,
2099,
28,
600,
11,
2672,
28,
17821,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
22915,
62,
74,
1600,
2099,
28,
600,
11,
2672,
28,
17821,
8,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
14050,
1600,
2099,
28,
22468,
11,
4277,
28,
15,
13,
486,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
14050,
62,
15952,
5950,
1600,
2099,
28,
600,
11,
299,
22046,
2625,
10,
1600,
4277,
41888,
12962,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
14050,
62,
16680,
1600,
2099,
28,
22468,
11,
4277,
28,
15,
13,
16,
8,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
22510,
62,
538,
5374,
82,
1600,
2099,
28,
600,
11,
4277,
28,
12825,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
43501,
62,
82,
89,
1600,
2099,
28,
600,
11,
2672,
28,
17821,
8,
220,
1303,
997,
14729,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
448,
62,
15763,
1600,
2099,
28,
2536,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
35922,
1416,
36722,
14,
28710,
14,
38246,
14,
87,
84,
7285,
14,
72,
312,
62,
19734,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
2118,
433,
1600,
2244,
2625,
2118,
433,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
9288,
62,
8189,
1600,
2244,
2625,
9288,
62,
8189,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
21928,
62,
19503,
80,
1600,
2099,
28,
600,
11,
4277,
28,
940,
8,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
74,
1326,
504,
62,
261,
62,
40890,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
198,
2,
31408,
198,
2,
973,
329,
366,
24561,
1,
6291,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
9536,
11025,
1600,
2244,
2625,
9536,
11025,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
525,
62,
9600,
62,
9536,
11025,
1600,
2244,
2625,
525,
62,
9600,
62,
9536,
11025,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
7890,
62,
32604,
1600,
2099,
28,
22468,
11,
299,
22046,
2625,
10,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
41888,
15,
13,
20,
11,
657,
13,
20,
11,
657,
13,
20,
12962,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
7890,
62,
19282,
1600,
2099,
28,
22468,
11,
299,
22046,
2625,
10,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
41888,
15,
13,
20,
11,
657,
13,
20,
11,
657,
13,
20,
12962,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
31476,
62,
11612,
1600,
2244,
2625,
31476,
62,
11612,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
31476,
62,
847,
1600,
2244,
2625,
31476,
62,
847,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
16,
62,
31476,
1600,
2099,
28,
2536,
11,
4277,
2625,
25120,
4943,
220,
1303,
2099,
1438,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
17,
62,
31476,
1600,
2099,
28,
2536,
11,
4277,
2625,
25120,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
16,
62,
31476,
62,
82,
89,
1600,
2099,
28,
600,
11,
4277,
28,
5705,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
17,
62,
31476,
62,
82,
89,
82,
1600,
2099,
28,
600,
11,
299,
22046,
2625,
10,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4277,
41888,
5705,
12962,
220,
1303,
1249,
814,
13833,
329,
545,
14542,
62,
27110,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
18,
62,
31476,
62,
26069,
1600,
2244,
2625,
27110,
18,
62,
31476,
62,
26069,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
27110,
18,
62,
31476,
62,
82,
89,
1600,
2099,
28,
600,
11,
4277,
28,
15,
8,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
15414,
62,
82,
89,
1600,
2099,
28,
600,
11,
4277,
28,
4846,
8,
198,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
10599,
62,
2100,
1600,
2099,
28,
22468,
11,
4277,
28,
15,
2014,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
33770,
62,
10599,
1600,
2244,
2625,
33770,
62,
10599,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
3919,
62,
73,
1967,
1600,
2244,
2625,
3919,
62,
73,
1967,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
48610,
13,
2860,
62,
49140,
7203,
438,
3919,
62,
2704,
541,
1600,
2244,
2625,
3919,
62,
2704,
541,
1600,
4277,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
8095,
62,
7942,
4943,
198,
198,
11250,
796,
30751,
13,
29572,
62,
22046,
3419,
198,
198,
2,
10832,
6460,
290,
8794,
20368,
19351,
198,
198,
11250,
13,
259,
62,
354,
8961,
796,
352,
198,
198,
361,
4566,
13,
22915,
62,
74,
14512,
4566,
13,
13655,
62,
74,
25,
198,
220,
220,
220,
6818,
357,
11250,
13,
22915,
62,
74,
1875,
4566,
13,
13655,
62,
74,
8,
198,
220,
220,
220,
6818,
357,
11250,
13,
74,
1326,
504,
62,
261,
62,
40890,
8,
198,
198,
11250,
13,
448,
62,
15908,
796,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15763,
11,
965,
7,
11250,
13,
19849,
62,
521,
4008,
198,
11250,
13,
67,
10254,
1170,
263,
62,
43501,
62,
82,
89,
796,
4566,
13,
43501,
62,
82,
89,
198,
11250,
13,
22510,
62,
67,
10254,
1170,
364,
796,
352,
198,
198,
361,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
11250,
13,
448,
62,
15908,
2599,
198,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
11250,
13,
448,
62,
15908,
8,
198,
198,
361,
4566,
13,
2118,
433,
25,
198,
220,
220,
220,
1813,
62,
11250,
796,
4566,
198,
220,
220,
220,
18126,
276,
62,
11250,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
35569,
62,
11250,
13,
448,
62,
15908,
11,
366,
11250,
13,
27729,
293,
4943,
198,
220,
220,
220,
3601,
7203,
19031,
15765,
278,
4566,
422,
25,
4064,
82,
1,
4064,
18126,
276,
62,
11250,
62,
6978,
8,
198,
220,
220,
220,
351,
1280,
7,
260,
14578,
62,
11250,
62,
6978,
11,
366,
26145,
4943,
355,
4566,
62,
69,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4566,
796,
2298,
293,
13,
2220,
7,
11250,
62,
69,
8,
198,
220,
220,
220,
6818,
357,
11250,
13,
19849,
62,
521,
6624,
1813,
62,
11250,
13,
19849,
62,
521,
8,
198,
220,
220,
220,
4566,
13,
2118,
433,
796,
6407,
628,
220,
220,
220,
1303,
4866,
625,
649,
997,
62,
538,
5374,
82,
290,
300,
81,
7269,
198,
220,
220,
220,
4566,
13,
22510,
62,
538,
5374,
82,
796,
1813,
62,
11250,
13,
22510,
62,
538,
5374,
82,
198,
220,
220,
220,
4566,
13,
14050,
62,
15952,
5950,
796,
1813,
62,
11250,
13,
14050,
62,
15952,
5950,
628,
220,
220,
220,
611,
407,
468,
35226,
7,
11250,
11,
366,
74,
1326,
504,
62,
261,
62,
40890,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
4566,
13,
74,
1326,
504,
62,
261,
62,
40890,
796,
10352,
198,
198,
17772,
25,
198,
220,
220,
220,
3601,
7203,
16934,
25,
4064,
82,
1,
4064,
4566,
62,
1462,
62,
2536,
7,
11250,
4008,
198,
198,
2,
6060,
11,
31720,
11,
6436,
21572,
20368,
19351,
6329,
198,
198,
67,
10254,
1170,
263,
62,
14986,
11,
4818,
282,
1170,
263,
62,
24561,
11,
4818,
282,
1170,
263,
62,
31591,
11,
3467,
198,
67,
10254,
1170,
263,
62,
9288,
796,
787,
62,
28461,
46916,
62,
7890,
7,
11250,
8,
198,
198,
27432,
62,
67,
10254,
1170,
364,
796,
685,
67,
10254,
1170,
263,
62,
14986,
11,
4818,
282,
1170,
263,
62,
24561,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
282,
1170,
263,
62,
31591,
60,
198,
198,
3262,
796,
3934,
82,
13,
834,
11600,
834,
58,
11250,
13,
998,
16151,
11250,
8,
198,
361,
4566,
13,
2118,
433,
25,
198,
220,
220,
220,
2746,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
42861,
62,
3262,
13,
9078,
13165,
354,
4943,
198,
220,
220,
220,
2263,
62,
13466,
796,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
19849,
62,
6978,
8,
198,
220,
220,
220,
611,
2263,
62,
13466,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
3500,
1266,
2427,
286,
3452,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
2746,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
13466,
62,
3262,
13,
9078,
13165,
354,
4943,
628,
220,
220,
220,
2010,
13,
2220,
62,
5219,
62,
11600,
7,
198,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
2220,
7,
19849,
62,
6978,
11,
3975,
62,
24886,
28,
50033,
6143,
11,
1179,
25,
6143,
4008,
198,
3262,
13,
66,
15339,
3419,
198,
3262,
796,
28034,
13,
20471,
13,
6601,
10044,
29363,
7,
3262,
8,
198,
3262,
13,
27432,
3419,
198,
198,
40085,
5847,
796,
651,
62,
8738,
7,
11250,
13,
8738,
5769,
3262,
13,
21412,
13,
17143,
7307,
22784,
300,
81,
28,
11250,
13,
14050,
8,
198,
361,
4566,
13,
2118,
433,
25,
198,
220,
220,
220,
2172,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
42861,
62,
40085,
5847,
13,
9078,
13165,
354,
4943,
198,
220,
220,
220,
611,
2263,
62,
13466,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2172,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
13466,
62,
40085,
5847,
13,
9078,
13165,
354,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
5847,
13,
2220,
62,
5219,
62,
11600,
7,
13165,
354,
13,
2220,
7,
8738,
62,
6978,
4008,
198,
198,
2,
15691,
6143,
20368,
1783,
26171,
198,
198,
361,
4566,
13,
2118,
433,
25,
198,
220,
220,
220,
611,
407,
2263,
62,
13466,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1306,
62,
538,
5374,
796,
4566,
13,
12957,
62,
538,
5374,
1343,
352,
220,
1303,
24866,
284,
938,
7448,
2746,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1306,
62,
538,
5374,
796,
45941,
13,
853,
9806,
7,
37659,
13,
18747,
7,
11250,
13,
538,
5374,
62,
4134,
4008,
1343,
352,
198,
220,
220,
220,
3601,
7203,
38690,
422,
36835,
4064,
67,
1,
4064,
1306,
62,
538,
5374,
8,
628,
220,
220,
220,
4566,
13,
538,
5374,
62,
4134,
796,
4566,
13,
538,
5374,
62,
4134,
58,
25,
19545,
62,
538,
5374,
60,
220,
1303,
287,
1339,
356,
625,
9442,
198,
220,
220,
220,
4566,
13,
538,
5374,
62,
22462,
796,
4566,
13,
538,
5374,
62,
22462,
58,
25,
19545,
62,
538,
5374,
60,
198,
220,
220,
220,
4566,
13,
76,
13978,
796,
4566,
13,
76,
13978,
58,
25,
19545,
62,
538,
5374,
11,
1058,
60,
198,
220,
220,
220,
4566,
13,
525,
62,
4871,
62,
4134,
796,
4566,
13,
525,
62,
4871,
62,
4134,
58,
25,
19545,
62,
538,
5374,
11,
1058,
60,
198,
17772,
25,
198,
220,
220,
220,
4566,
13,
538,
5374,
62,
4134,
796,
17635,
198,
220,
220,
220,
4566,
13,
538,
5374,
62,
22462,
796,
17635,
628,
220,
220,
220,
4566,
13,
76,
13978,
796,
6045,
198,
220,
220,
220,
4566,
13,
525,
62,
4871,
62,
4134,
796,
6045,
628,
220,
220,
220,
4808,
796,
15055,
912,
62,
18206,
7,
11250,
11,
2010,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
282,
1170,
263,
62,
9288,
28,
67,
10254,
1170,
263,
62,
9288,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
523,
6667,
28,
25101,
8,
628,
220,
220,
220,
3601,
7203,
6719,
25,
640,
4064,
82,
25,
3467,
77,
4064,
82,
1,
4064,
357,
19608,
8079,
13,
2197,
22784,
4566,
13,
538,
5374,
62,
4134,
58,
12,
16,
60,
4008,
198,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
198,
220,
220,
220,
1306,
62,
538,
5374,
796,
352,
198,
198,
5647,
11,
7877,
3258,
796,
458,
83,
13,
7266,
489,
1747,
7,
19,
11,
2648,
87,
28,
25101,
11,
2336,
7857,
16193,
1238,
11,
1160,
4008,
198,
198,
2,
16835,
16529,
982,
198,
198,
1640,
304,
62,
72,
287,
2124,
9521,
7,
19545,
62,
538,
5374,
11,
4566,
13,
22510,
62,
538,
5374,
82,
2599,
198,
220,
220,
220,
3601,
7203,
22851,
304,
62,
72,
25,
4064,
67,
1,
4064,
357,
68,
62,
72,
4008,
628,
220,
220,
220,
611,
304,
62,
72,
287,
4566,
13,
14050,
62,
15952,
5950,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
5847,
796,
4296,
62,
14050,
7,
40085,
5847,
11,
300,
81,
62,
16680,
28,
11250,
13,
14050,
62,
16680,
8,
628,
220,
220,
220,
42781,
62,
22462,
796,
657,
13,
220,
1303,
625,
6665,
290,
1182,
62,
538,
5374,
82,
357,
392,
850,
62,
16600,
8,
198,
220,
220,
220,
42781,
62,
22462,
62,
9127,
796,
657,
628,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
628,
220,
220,
220,
11629,
2024,
796,
357,
67,
329,
288,
287,
4512,
62,
67,
10254,
1170,
364,
8,
628,
220,
220,
220,
275,
62,
72,
796,
657,
198,
220,
220,
220,
329,
256,
929,
287,
340,
861,
10141,
13,
528,
541,
46491,
2676,
2024,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
2010,
13,
21412,
13,
22570,
62,
9744,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
545,
14542,
62,
11612,
796,
256,
929,
58,
15,
7131,
15,
4083,
66,
15339,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
545,
14542,
62,
1930,
796,
256,
929,
58,
16,
7131,
15,
4083,
66,
15339,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
545,
14542,
62,
12480,
796,
256,
929,
58,
17,
7131,
15,
4083,
66,
15339,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
12198,
62,
11612,
796,
2010,
7,
9600,
82,
62,
11612,
8,
198,
220,
220,
220,
220,
220,
220,
220,
12198,
62,
1930,
796,
2010,
7,
9600,
82,
62,
1930,
8,
198,
220,
220,
220,
220,
220,
220,
220,
12198,
62,
12480,
796,
2010,
7,
9600,
82,
62,
12480,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1090,
81,
62,
22462,
796,
15055,
912,
62,
22462,
7,
5269,
62,
11612,
11,
12198,
62,
1930,
11,
12198,
62,
12480,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
14808,
65,
62,
72,
4064,
1802,
8,
6624,
657,
8,
393,
357,
68,
62,
72,
6624,
1306,
62,
538,
5374,
290,
275,
62,
72,
1279,
838,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
17633,
773,
4064,
67,
36835,
4064,
67,
15458,
4064,
67,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
22462,
4064,
69,
640,
4064,
82,
1,
4064,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
11250,
13,
19849,
62,
521,
11,
304,
62,
72,
11,
275,
62,
72,
11,
1090,
81,
62,
22462,
13,
9186,
22784,
4818,
8079,
13,
2197,
3419,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
611,
407,
45941,
13,
4468,
9504,
7,
22468,
7,
22019,
81,
62,
22462,
13,
9186,
28955,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
43,
793,
318,
407,
27454,
986,
4064,
82,
11097,
4064,
965,
7,
22019,
81,
62,
22462,
13,
9186,
3419,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8420,
7,
16,
8,
628,
220,
220,
220,
220,
220,
220,
220,
42781,
62,
22462,
15853,
1090,
81,
62,
22462,
13,
9186,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
42781,
62,
22462,
62,
9127,
15853,
352,
628,
220,
220,
220,
220,
220,
220,
220,
1090,
81,
62,
22462,
13,
1891,
904,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6436,
5847,
13,
9662,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
275,
62,
72,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
611,
275,
62,
72,
6624,
362,
290,
4566,
13,
9288,
62,
8189,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
42781,
62,
22462,
796,
12178,
7,
615,
70,
62,
22462,
1220,
42781,
62,
22462,
62,
9127,
8,
628,
220,
220,
220,
4566,
13,
538,
5374,
62,
22462,
13,
33295,
7,
615,
70,
62,
22462,
8,
628,
220,
220,
220,
1303,
26439,
290,
6143,
20368,
22369,
6329,
628,
220,
220,
220,
1303,
618,
36835,
625,
1111,
6665,
318,
5201,
198,
220,
220,
220,
318,
62,
13466,
796,
15055,
912,
62,
18206,
7,
11250,
11,
2010,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
282,
1170,
263,
62,
9288,
28,
67,
10254,
1170,
263,
62,
9288,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
523,
6667,
28,
25101,
8,
628,
220,
220,
220,
3601,
7203,
7575,
4064,
82,
11,
697,
4064,
82,
1,
4064,
357,
19608,
8079,
13,
2197,
22784,
4566,
13,
538,
5374,
62,
4134,
58,
12,
16,
60,
4008,
198,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
628,
220,
220,
220,
7877,
3258,
58,
15,
4083,
20063,
3419,
198,
220,
220,
220,
7877,
3258,
58,
15,
4083,
29487,
7,
11250,
13,
538,
5374,
62,
4134,
8,
198,
220,
220,
220,
7877,
3258,
58,
15,
4083,
2617,
62,
7839,
7203,
4134,
11,
1353,
25,
4064,
69,
1,
4064,
3509,
7,
11250,
13,
538,
5374,
62,
4134,
4008,
628,
220,
220,
220,
7877,
3258,
58,
16,
4083,
20063,
3419,
198,
220,
220,
220,
7877,
3258,
58,
16,
4083,
29487,
7,
11250,
13,
538,
5374,
62,
22462,
8,
198,
220,
220,
220,
7877,
3258,
58,
16,
4083,
2617,
62,
7839,
7203,
43,
793,
4943,
628,
220,
220,
220,
7877,
3258,
58,
17,
4083,
20063,
3419,
198,
220,
220,
220,
329,
269,
287,
2124,
9521,
7,
11250,
13,
13655,
62,
74,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
7877,
3258,
58,
17,
4083,
29487,
7,
11250,
13,
76,
13978,
58,
45299,
269,
12962,
198,
220,
220,
220,
7877,
3258,
58,
17,
4083,
2617,
62,
7839,
7203,
76,
13978,
4943,
628,
220,
220,
220,
7877,
3258,
58,
18,
4083,
20063,
3419,
198,
220,
220,
220,
329,
269,
287,
2124,
9521,
7,
11250,
13,
13655,
62,
74,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
7877,
3258,
58,
18,
4083,
29487,
7,
11250,
13,
525,
62,
4871,
62,
4134,
58,
45299,
269,
12962,
198,
220,
220,
220,
7877,
3258,
58,
18,
4083,
2617,
62,
7839,
7203,
525,
62,
4871,
62,
4134,
4943,
628,
220,
220,
220,
2336,
13,
33464,
62,
39786,
3419,
198,
220,
220,
220,
2336,
13,
5171,
11017,
13,
19334,
62,
312,
293,
3419,
198,
220,
220,
220,
2336,
13,
21928,
5647,
7,
418,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
489,
1747,
13,
11134,
48774,
628,
220,
220,
220,
611,
318,
62,
13466,
393,
357,
68,
62,
72,
4064,
4566,
13,
21928,
62,
19503,
80,
6624,
657,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
2010,
13,
21412,
13,
36166,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
611,
318,
62,
13466,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
21928,
7,
3262,
13,
21412,
13,
5219,
62,
11600,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
13466,
62,
3262,
13,
9078,
13165,
354,
48774,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
21928,
7,
40085,
5847,
13,
5219,
62,
11600,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
13466,
62,
40085,
5847,
13,
9078,
13165,
354,
48774,
628,
220,
220,
220,
220,
220,
220,
220,
611,
304,
62,
72,
4064,
4566,
13,
21928,
62,
19503,
80,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
21928,
7,
3262,
13,
21412,
13,
5219,
62,
11600,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
42861,
62,
3262,
13,
9078,
13165,
354,
48774,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
21928,
7,
40085,
5847,
13,
5219,
62,
11600,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
42861,
62,
40085,
5847,
13,
9078,
13165,
354,
48774,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
13,
12957,
62,
538,
5374,
796,
304,
62,
72,
220,
1303,
329,
938,
7448,
2196,
628,
220,
220,
220,
220,
220,
220,
220,
2010,
13,
21412,
13,
66,
15339,
3419,
628,
220,
220,
220,
351,
1280,
7,
418,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
11250,
13,
27729,
293,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
39346,
11537,
355,
503,
7753,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2298,
293,
13,
39455,
7,
11250,
11,
503,
7753,
8,
628,
220,
220,
220,
351,
1280,
7,
418,
13,
6978,
13,
22179,
7,
11250,
13,
448,
62,
15908,
11,
366,
11250,
13,
14116,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
86,
4943,
355,
2420,
62,
7753,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2420,
62,
7753,
13,
13564,
7203,
4,
82,
1,
4064,
4566,
8,
628,
220,
220,
220,
611,
4566,
13,
9288,
62,
8189,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8420,
7,
15,
8,
198
] | 2.323216 | 4,415 |
"""empty message
Revision ID: 0084_add_job_stats
Revises: 0083_add_perm_types_and_svc_perm
Create Date: 2017-05-12 13:16:14.147368
"""
# revision identifiers, used by Alembic.
revision = "0084_add_job_stats"
down_revision = "0083_add_perm_types_and_svc_perm"
import sqlalchemy as sa
from alembic import op
from sqlalchemy.dialects import postgresql
| [
37811,
28920,
3275,
198,
198,
18009,
1166,
4522,
25,
3571,
5705,
62,
2860,
62,
21858,
62,
34242,
198,
18009,
2696,
25,
3571,
5999,
62,
2860,
62,
16321,
62,
19199,
62,
392,
62,
21370,
66,
62,
16321,
198,
16447,
7536,
25,
2177,
12,
2713,
12,
1065,
1511,
25,
1433,
25,
1415,
13,
20198,
27412,
198,
198,
37811,
198,
198,
2,
18440,
42814,
11,
973,
416,
9300,
2022,
291,
13,
198,
260,
10178,
796,
366,
405,
5705,
62,
2860,
62,
21858,
62,
34242,
1,
198,
2902,
62,
260,
10178,
796,
366,
405,
5999,
62,
2860,
62,
16321,
62,
19199,
62,
392,
62,
21370,
66,
62,
16321,
1,
198,
198,
11748,
44161,
282,
26599,
355,
473,
198,
6738,
31341,
2022,
291,
1330,
1034,
198,
6738,
44161,
282,
26599,
13,
38969,
478,
82,
1330,
1281,
34239,
13976,
628,
198
] | 2.62963 | 135 |
import unittest
from future.moves.urllib.parse import urlparse, urljoin, parse_qs
import pytest
from addons.twofactor.tests.utils import _valid_code
from nose.tools import (assert_equal, assert_false, assert_is_none,
assert_is_not_none, assert_true)
from osf_tests.factories import UserFactory
pytestmark = pytest.mark.django_db
| [
11748,
555,
715,
395,
198,
6738,
2003,
13,
76,
5241,
13,
333,
297,
571,
13,
29572,
1330,
19016,
29572,
11,
19016,
22179,
11,
21136,
62,
48382,
198,
198,
11748,
12972,
9288,
198,
6738,
751,
684,
13,
4246,
1659,
11218,
13,
41989,
13,
26791,
1330,
4808,
12102,
62,
8189,
198,
6738,
9686,
13,
31391,
1330,
357,
30493,
62,
40496,
11,
6818,
62,
9562,
11,
6818,
62,
271,
62,
23108,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6818,
62,
271,
62,
1662,
62,
23108,
11,
6818,
62,
7942,
8,
198,
6738,
267,
28202,
62,
41989,
13,
22584,
1749,
1330,
11787,
22810,
198,
198,
9078,
9288,
4102,
796,
12972,
9288,
13,
4102,
13,
28241,
14208,
62,
9945,
628,
198
] | 2.664179 | 134 |
import numpy as np
from torchvision import transforms
np.random.seed(1) | [
11748,
299,
32152,
355,
45941,
198,
6738,
28034,
10178,
1330,
31408,
198,
37659,
13,
25120,
13,
28826,
7,
16,
8
] | 3.55 | 20 |
import torch
import os
from torch import nn
import numpy as np
import torch.nn.functional
from termcolor import colored
from .logger import get_logger
| [
11748,
28034,
198,
11748,
28686,
198,
6738,
28034,
1330,
299,
77,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
13,
20471,
13,
45124,
198,
6738,
3381,
8043,
1330,
16396,
198,
6738,
764,
6404,
1362,
1330,
651,
62,
6404,
1362,
628,
198
] | 3.642857 | 42 |
from django.apps import AppConfig #pragma: no cover
| [
6738,
42625,
14208,
13,
18211,
1330,
2034,
16934,
1303,
1050,
363,
2611,
25,
645,
3002,
628
] | 3.3125 | 16 |
from __future__ import division
from timeit import default_timer as timer
import csv
import numpy as np
import itertools
from munkres import Munkres, print_matrix, make_cost_matrix
import sys
from classes import *
from functions import *
from math import sqrt
import Tkinter as tk
import tkFileDialog as filedialog
root = tk.Tk()
root.withdraw()
p_file = filedialog.askopenfilename(title='Please select the posting file')
c_file = filedialog.askopenfilename(title='Please select the candidate file')
"""for use with /users/java_jonathan/postings_lge.csv and
/Users/java_jonathan/candidates_lge.csv"""
# p_file = raw_input("Please enter the path for the postings file: ")
# p_file = p_file.strip()
# c_file = raw_input("Please enter the path for the candidate file: ")
# c_file = c_file.strip()
start = timer()
with open(p_file,'r') as f:
#with open('/Users/Jonathan/Google Drive/CPD/Python/postings.csv','r') as f:
reader = csv.reader(f)
postingsAll = list(reader)
with open(c_file,'r') as f:
reader = csv.reader(f)
candidatesAll = list(reader)
"""create empty lists to fill with lists of lists output by iterating function
below"""
names = []
totalMatrix = []
for list in candidatesAll:
candidate = Candidate(*list)
names.append(candidate.name)
n = 0
for list in postingsAll:
posting = Posting(*list)
totalMatrix.append(matchDept(posting,candidate) + matchAnchor(posting,candidate)
+matchLocation(posting,candidate) + matchCompetency(posting,candidate) +
matchSkill(posting,candidate)+matchCohort(posting,candidate))
n += 1
l = len(names)
names.extend([0] * (n-l))
totalMatrix.extend([0] * (n**2 - len(totalMatrix)))
totalMatrix = np.asarray(totalMatrix)
totalMatrix = np.reshape(totalMatrix,(n,-1))
#at this point the matrix is structured as candidates down and jobs across
totalMatrix = np.transpose(totalMatrix)
#now it's switched!
totalMatrix = np.subtract(np.amax(totalMatrix),totalMatrix)
totalMatrix = np.array(totalMatrix)
minSuitability = 18
check = []
result = []
m = Munkres()
indexes = m.compute(totalMatrix)
#print_matrix(totalMatrix, msg='Lowest cost through this matrix:')
total = 0.0
unhappy_candidates = 0
medium_candidates = 0
tenpc_candidates = 0
qs_candidates = 0
vs_candidates = 0
f = open('output.txt', 'w')
for row, column in indexes:
if column < l:
value = totalMatrix[row][column]
if value > minSuitability*0.9:
tenpc_candidates += 1
elif value > minSuitability*0.75:
medium_candidates += 1
elif value > minSuitability/2:
unhappy_candidates += 1
elif value > minSuitability*0.25:
qs_candidates += 1
elif value > minSuitability*0.1:
vs_candidates += 1
total += value
check.append(column+1)
result.append((row,column))
f.write('For candidate %s: \nOptimal position: %d (score %s)\n'
% (names[column], column+1, value))
else:
pass
globalSatisfaction = 100*(1-(total/(l*minSuitability)))
print('Global satisfaction: %.2f%%' % globalSatisfaction)
print('Candidates who are more than 90%% suitable: %d' % vs_candidates)
print('Candidates who are more than 75%% suitable: %d' % qs_candidates)
print('Candidates who are more than 50%% suitable: %d' % (l-unhappy_candidates))
print('Candidates who are more than 75%% unsuitable: %d' % medium_candidates)
print('Candidates who are more than 90%% unsuitable: %d' % tenpc_candidates)
#output from excel:
correct = [1,3,5,9,10,2,4,8,6,7]
#this function tests output above against Excel:
#test(correct,check)
topMatrix = topFive(names,totalMatrix)
#print(topMatrix)
np.savetxt('/Users/java_jonathan/test.csv',topMatrix, fmt='%s', delimiter=',',
newline='\n', header='', footer='', comments='# ')
np.savetxt('/Users/java_jonathan/test2.csv',totalMatrix, fmt='%s', delimiter=',',
newline='\n', header='', footer='', comments='# ')
end = timer()
print(end-start)
"""
#posting = [Posting(*postingsAll)]
#print(posting[0].anchor)
#print(posting)
#print(candidatesAll)
#print(postingsAll)
#print(postingsAll[0].name)
#print(preferences)
#print(postings)
#split up files into relative blocks
postCode = [lists[0] for lists in postings]
postDept = [lists[1] for lists in postings]
postAnchor = [lists[2] for lists in postings]
postSkills = [lists[3:5] for lists in postings]
postLocation = [lists[5] for lists in postings]
postCompetencies = [lists[7:10] for lists in postings]
postSecurity = [lists[10] for lists in postings]
#with open('/Users/Jonathan/Google Drive/CPD/Python/candidates.csv','r') as f:
#gives first column ie candidate a
a=totalMatrix[:,[0]]
#b = totalMatrix[:,[0]]
#print(a)
#converts 1D matrix to list for ease
a = np.array(a).tolist()
#print(a)
#creates list called output containing rank of score
output = [0] * len(a)
for i, x in enumerate(sorted(range(len(a)), key=lambda y: a[y])):
output[x] = i
print(output)
#creates tuples of rank, job and appends to list
jobRank = []
# for rank, b in zip(output, postCode):
# jobScore = (rank,b)
# list(jobScore)
# jobRank.append(jobScore)
# print(jobRank)
output = [0] * len(a)
for i, x in enumerate(sorted(range(len(a)), key=lambda y: a[y])):
output[x] = i
print(output)
# #print(a)
# jobRank = sorted(jobRank, reverse=False)
# print(jobRank)
# print('For candidate a, the best position is %s') % (jobRank[0][1])
# print(candidate[0].skills)
"""
| [
6738,
11593,
37443,
834,
1330,
7297,
198,
6738,
640,
270,
1330,
4277,
62,
45016,
355,
19781,
198,
11748,
269,
21370,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
340,
861,
10141,
198,
6738,
285,
2954,
411,
1330,
337,
2954,
411,
11,
3601,
62,
6759,
8609,
11,
787,
62,
15805,
62,
6759,
8609,
198,
11748,
25064,
198,
6738,
6097,
1330,
1635,
198,
6738,
5499,
1330,
1635,
198,
6738,
10688,
1330,
19862,
17034,
198,
11748,
309,
74,
3849,
355,
256,
74,
198,
11748,
256,
74,
8979,
44204,
355,
5717,
498,
519,
198,
198,
15763,
796,
256,
74,
13,
51,
74,
3419,
198,
15763,
13,
4480,
19334,
3419,
198,
79,
62,
7753,
796,
5717,
498,
519,
13,
2093,
9654,
34345,
7,
7839,
11639,
5492,
2922,
262,
10754,
2393,
11537,
198,
66,
62,
7753,
796,
5717,
498,
519,
13,
2093,
9654,
34345,
7,
7839,
11639,
5492,
2922,
262,
4540,
2393,
11537,
628,
198,
37811,
1640,
779,
351,
1220,
18417,
14,
12355,
62,
46286,
6696,
14,
7353,
654,
62,
75,
469,
13,
40664,
290,
198,
14,
14490,
14,
12355,
62,
46286,
6696,
14,
46188,
37051,
62,
75,
469,
13,
40664,
37811,
198,
198,
2,
279,
62,
7753,
796,
8246,
62,
15414,
7203,
5492,
3802,
262,
3108,
329,
262,
44656,
2393,
25,
366,
8,
198,
2,
279,
62,
7753,
796,
279,
62,
7753,
13,
36311,
3419,
198,
2,
269,
62,
7753,
796,
8246,
62,
15414,
7203,
5492,
3802,
262,
3108,
329,
262,
4540,
2393,
25,
366,
8,
198,
2,
269,
62,
7753,
796,
269,
62,
7753,
13,
36311,
3419,
198,
9688,
796,
19781,
3419,
198,
4480,
1280,
7,
79,
62,
7753,
4032,
81,
11537,
355,
277,
25,
198,
2,
4480,
1280,
10786,
14,
14490,
14,
30365,
14,
11708,
9974,
14,
34,
5760,
14,
37906,
14,
7353,
654,
13,
40664,
41707,
81,
11537,
355,
277,
25,
198,
220,
220,
220,
9173,
796,
269,
21370,
13,
46862,
7,
69,
8,
198,
220,
220,
220,
44656,
3237,
796,
1351,
7,
46862,
8,
198,
198,
4480,
1280,
7,
66,
62,
7753,
4032,
81,
11537,
355,
277,
25,
198,
220,
220,
220,
9173,
796,
269,
21370,
13,
46862,
7,
69,
8,
198,
220,
220,
220,
5871,
3237,
796,
1351,
7,
46862,
8,
628,
198,
37811,
17953,
6565,
8341,
284,
6070,
351,
8341,
286,
8341,
5072,
416,
11629,
803,
2163,
198,
35993,
37811,
198,
14933,
796,
17635,
198,
23350,
46912,
796,
17635,
198,
1640,
1351,
287,
5871,
3237,
25,
198,
220,
220,
220,
4540,
796,
40327,
46491,
4868,
8,
198,
220,
220,
220,
3891,
13,
33295,
7,
46188,
20540,
13,
3672,
8,
198,
220,
220,
220,
299,
796,
657,
198,
220,
220,
220,
329,
1351,
287,
44656,
3237,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10754,
796,
2947,
278,
46491,
4868,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2472,
46912,
13,
33295,
7,
15699,
5005,
457,
7,
7353,
278,
11,
46188,
20540,
8,
1343,
2872,
2025,
354,
273,
7,
7353,
278,
11,
46188,
20540,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1343,
15699,
14749,
7,
7353,
278,
11,
46188,
20540,
8,
1343,
2872,
7293,
316,
1387,
7,
7353,
278,
11,
46188,
20540,
8,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
2872,
35040,
7,
7353,
278,
11,
46188,
20540,
47762,
15699,
34,
1219,
419,
7,
7353,
278,
11,
46188,
20540,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
299,
15853,
352,
198,
75,
796,
18896,
7,
14933,
8,
198,
14933,
13,
2302,
437,
26933,
15,
60,
1635,
357,
77,
12,
75,
4008,
198,
198,
23350,
46912,
13,
2302,
437,
26933,
15,
60,
1635,
357,
77,
1174,
17,
532,
18896,
7,
23350,
46912,
22305,
198,
23350,
46912,
796,
45941,
13,
292,
18747,
7,
23350,
46912,
8,
198,
198,
23350,
46912,
796,
45941,
13,
3447,
1758,
7,
23350,
46912,
11,
7,
77,
12095,
16,
4008,
198,
2,
265,
428,
966,
262,
17593,
318,
20793,
355,
5871,
866,
290,
3946,
1973,
198,
23350,
46912,
796,
45941,
13,
7645,
3455,
7,
23350,
46912,
8,
198,
2,
2197,
340,
338,
15293,
0,
198,
23350,
46912,
796,
45941,
13,
7266,
83,
974,
7,
37659,
13,
321,
897,
7,
23350,
46912,
828,
23350,
46912,
8,
198,
23350,
46912,
796,
45941,
13,
18747,
7,
23350,
46912,
8,
198,
1084,
50,
5013,
1799,
796,
1248,
198,
9122,
796,
17635,
198,
20274,
796,
17635,
198,
76,
796,
337,
2954,
411,
3419,
198,
9630,
274,
796,
285,
13,
5589,
1133,
7,
23350,
46912,
8,
198,
2,
4798,
62,
6759,
8609,
7,
23350,
46912,
11,
31456,
11639,
20535,
395,
1575,
832,
428,
17593,
25,
11537,
198,
23350,
796,
657,
13,
15,
198,
403,
34191,
62,
46188,
37051,
796,
657,
198,
24132,
62,
46188,
37051,
796,
657,
198,
1452,
14751,
62,
46188,
37051,
796,
657,
198,
48382,
62,
46188,
37051,
796,
657,
198,
14259,
62,
46188,
37051,
796,
657,
198,
69,
796,
1280,
10786,
22915,
13,
14116,
3256,
705,
86,
11537,
198,
1640,
5752,
11,
5721,
287,
39199,
25,
198,
220,
220,
220,
611,
5721,
1279,
300,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
2472,
46912,
58,
808,
7131,
28665,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
1875,
949,
50,
5013,
1799,
9,
15,
13,
24,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3478,
14751,
62,
46188,
37051,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1988,
1875,
949,
50,
5013,
1799,
9,
15,
13,
2425,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7090,
62,
46188,
37051,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1988,
1875,
949,
50,
5013,
1799,
14,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19283,
62,
46188,
37051,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1988,
1875,
949,
50,
5013,
1799,
9,
15,
13,
1495,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
82,
62,
46188,
37051,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1988,
1875,
949,
50,
5013,
1799,
9,
15,
13,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3691,
62,
46188,
37051,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
2472,
15853,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
2198,
13,
33295,
7,
28665,
10,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
13,
33295,
19510,
808,
11,
28665,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
277,
13,
13564,
10786,
1890,
4540,
4064,
82,
25,
3467,
77,
27871,
4402,
2292,
25,
4064,
67,
357,
26675,
4064,
82,
19415,
77,
6,
198,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
14933,
58,
28665,
4357,
5721,
10,
16,
11,
1988,
4008,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
20541,
50,
17403,
2673,
796,
1802,
9,
7,
16,
30420,
23350,
29006,
75,
9,
1084,
50,
5013,
1799,
22305,
198,
4798,
10786,
22289,
14676,
25,
4064,
13,
17,
69,
16626,
6,
4064,
3298,
50,
17403,
2673,
8,
198,
4798,
10786,
41572,
37051,
508,
389,
517,
621,
4101,
16626,
11080,
25,
4064,
67,
6,
4064,
3691,
62,
46188,
37051,
8,
198,
4798,
10786,
41572,
37051,
508,
389,
517,
621,
5441,
16626,
11080,
25,
4064,
67,
6,
4064,
10662,
82,
62,
46188,
37051,
8,
198,
4798,
10786,
41572,
37051,
508,
389,
517,
621,
2026,
16626,
11080,
25,
4064,
67,
6,
4064,
357,
75,
12,
403,
34191,
62,
46188,
37051,
4008,
198,
4798,
10786,
41572,
37051,
508,
389,
517,
621,
5441,
16626,
48092,
4674,
25,
4064,
67,
6,
4064,
7090,
62,
46188,
37051,
8,
198,
4798,
10786,
41572,
37051,
508,
389,
517,
621,
4101,
16626,
48092,
4674,
25,
4064,
67,
6,
4064,
3478,
14751,
62,
46188,
37051,
8,
198,
198,
2,
22915,
422,
27336,
25,
198,
30283,
796,
685,
16,
11,
18,
11,
20,
11,
24,
11,
940,
11,
17,
11,
19,
11,
23,
11,
21,
11,
22,
60,
198,
198,
2,
5661,
2163,
5254,
5072,
2029,
1028,
24134,
25,
198,
2,
9288,
7,
30283,
11,
9122,
8,
198,
4852,
46912,
796,
1353,
20029,
7,
14933,
11,
23350,
46912,
8,
198,
2,
4798,
7,
4852,
46912,
8,
198,
198,
37659,
13,
21928,
14116,
10786,
14,
14490,
14,
12355,
62,
46286,
6696,
14,
9288,
13,
40664,
3256,
4852,
46912,
11,
46996,
11639,
4,
82,
3256,
46728,
2676,
28,
3256,
3256,
198,
3605,
1370,
11639,
59,
77,
3256,
13639,
11639,
3256,
2366,
263,
11639,
3256,
3651,
11639,
2,
705,
8,
198,
37659,
13,
21928,
14116,
10786,
14,
14490,
14,
12355,
62,
46286,
6696,
14,
9288,
17,
13,
40664,
3256,
23350,
46912,
11,
46996,
11639,
4,
82,
3256,
46728,
2676,
28,
3256,
3256,
198,
3605,
1370,
11639,
59,
77,
3256,
13639,
11639,
3256,
2366,
263,
11639,
3256,
3651,
11639,
2,
705,
8,
198,
437,
796,
19781,
3419,
198,
4798,
7,
437,
12,
9688,
8,
198,
198,
37811,
198,
2,
7353,
278,
796,
685,
6307,
278,
46491,
7353,
654,
3237,
15437,
198,
2,
4798,
7,
7353,
278,
58,
15,
4083,
3702,
273,
8,
198,
2,
4798,
7,
7353,
278,
8,
198,
2,
4798,
7,
46188,
37051,
3237,
8,
198,
2,
4798,
7,
7353,
654,
3237,
8,
198,
2,
4798,
7,
7353,
654,
3237,
58,
15,
4083,
3672,
8,
198,
220,
220,
220,
1303,
4798,
7,
3866,
69,
4972,
8,
198,
2,
4798,
7,
7353,
654,
8,
198,
2,
35312,
510,
3696,
656,
3585,
7021,
198,
198,
7353,
10669,
796,
685,
20713,
58,
15,
60,
329,
8341,
287,
44656,
60,
198,
7353,
5005,
457,
796,
685,
20713,
58,
16,
60,
329,
8341,
287,
44656,
60,
198,
7353,
2025,
354,
273,
796,
685,
20713,
58,
17,
60,
329,
8341,
287,
44656,
60,
198,
7353,
15739,
2171,
796,
685,
20713,
58,
18,
25,
20,
60,
329,
8341,
287,
44656,
60,
198,
7353,
14749,
796,
685,
20713,
58,
20,
60,
329,
8341,
287,
44656,
60,
198,
7353,
7293,
316,
3976,
796,
685,
20713,
58,
22,
25,
940,
60,
329,
8341,
287,
44656,
60,
198,
7353,
24074,
796,
685,
20713,
58,
940,
60,
329,
8341,
287,
44656,
60,
628,
198,
2,
4480,
1280,
10786,
14,
14490,
14,
30365,
14,
11708,
9974,
14,
34,
5760,
14,
37906,
14,
46188,
37051,
13,
40664,
41707,
81,
11537,
355,
277,
25,
628,
628,
198,
198,
2,
70,
1083,
717,
5721,
37941,
4540,
257,
198,
64,
28,
23350,
46912,
58,
25,
17414,
15,
11907,
198,
2,
65,
796,
2472,
46912,
58,
25,
17414,
15,
11907,
198,
2,
4798,
7,
64,
8,
198,
2,
1102,
24040,
352,
35,
17593,
284,
1351,
329,
10152,
198,
64,
796,
45941,
13,
18747,
7,
64,
737,
83,
349,
396,
3419,
198,
2,
4798,
7,
64,
8,
198,
2,
20123,
274,
1351,
1444,
5072,
7268,
4279,
286,
4776,
198,
22915,
796,
685,
15,
60,
1635,
18896,
7,
64,
8,
198,
1640,
1312,
11,
2124,
287,
27056,
378,
7,
82,
9741,
7,
9521,
7,
11925,
7,
64,
36911,
1994,
28,
50033,
331,
25,
257,
58,
88,
12962,
2599,
198,
220,
220,
220,
5072,
58,
87,
60,
796,
1312,
198,
4798,
7,
22915,
8,
198,
2,
20123,
274,
12777,
2374,
286,
4279,
11,
1693,
290,
598,
2412,
284,
1351,
198,
21858,
27520,
796,
17635,
198,
2,
329,
4279,
11,
275,
287,
19974,
7,
22915,
11,
1281,
10669,
2599,
198,
2,
220,
220,
220,
220,
1693,
26595,
796,
357,
43027,
11,
65,
8,
198,
2,
220,
220,
220,
220,
1351,
7,
21858,
26595,
8,
198,
2,
220,
220,
220,
220,
1693,
27520,
13,
33295,
7,
21858,
26595,
8,
198,
2,
3601,
7,
21858,
27520,
8,
628,
198,
22915,
796,
685,
15,
60,
1635,
18896,
7,
64,
8,
198,
1640,
1312,
11,
2124,
287,
27056,
378,
7,
82,
9741,
7,
9521,
7,
11925,
7,
64,
36911,
1994,
28,
50033,
331,
25,
257,
58,
88,
12962,
2599,
198,
220,
220,
220,
5072,
58,
87,
60,
796,
1312,
198,
4798,
7,
22915,
8,
198,
198,
2,
1303,
4798,
7,
64,
8,
198,
2,
1693,
27520,
796,
23243,
7,
21858,
27520,
11,
9575,
28,
25101,
8,
198,
2,
3601,
7,
21858,
27520,
8,
198,
2,
3601,
10786,
1890,
4540,
257,
11,
262,
1266,
2292,
318,
4064,
82,
11537,
4064,
357,
21858,
27520,
58,
15,
7131,
16,
12962,
198,
2,
3601,
7,
46188,
20540,
58,
15,
4083,
8135,
2171,
8,
198,
37811,
198
] | 2.662274 | 2,049 |
"""Setup script for PySyReNN.
Adapted from:
https://hynek.me/articles/sharing-your-labor-of-love-pypi-quick-and-dirty/
"""
import codecs
import os
import re
from setuptools import setup, find_packages
###################################################################
NAME = "pysyrenn"
PACKAGES = [
"syrenn_proto",
"pysyrenn",
"pysyrenn.frontend",
"pysyrenn.helpers",
]
META_PATH = "__metadata__.py"
KEYWORDS = ["class", "attribute", "boilerplate"]
CLASSIFIERS = [
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Natural Language :: English",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
"Programming Language :: Python",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy",
"Topic :: Software Development :: Libraries :: Python Modules",
]
INSTALL_REQUIRES = ["torch"]
with open("requirements.txt") as requirements:
reading = False
for line in requirements.readlines():
if line.startswith("# PYSYRENN"):
reading = True
elif line.startswith("# END"):
reading = False
elif line.startswith("#"):
pass
elif reading:
INSTALL_REQUIRES.append(line.strip().split("==")[0])
###################################################################
HERE = os.path.abspath(os.path.dirname(__file__))
def read(*parts):
"""
Build an absolute path from *parts* and and return the contents of the
resulting file. Assume UTF-8 encoding.
"""
with codecs.open(os.path.join(HERE, *parts), "rb", "utf-8") as f:
return f.read()
META_FILE = read(META_PATH)
def find_meta(meta):
"""Extract __*meta*__ from META_FILE.
"""
meta_match = re.search(
r"^__{meta}__ = ['\"]([^'\"]*)['\"]".format(meta=meta),
META_FILE, re.M
)
if meta_match:
return meta_match.group(1)
raise RuntimeError("Unable to find __{meta}__ string.".format(meta=meta))
if __name__ == "__main__":
setup(
name=NAME,
description=find_meta("description"),
license=find_meta("license"),
url=find_meta("uri"),
version=find_meta("version"),
author=find_meta("author"),
author_email=find_meta("email"),
maintainer=find_meta("author"),
maintainer_email=find_meta("email"),
keywords=KEYWORDS,
long_description=read("README.md"),
long_description_content_type="text/markdown",
packages=PACKAGES,
package_dir={"": "."},
package_data={"": ["pysyrenn/**/*.py"]},
zip_safe=False,
classifiers=CLASSIFIERS,
install_requires=INSTALL_REQUIRES,
)
| [
37811,
40786,
4226,
329,
9485,
13940,
3041,
6144,
13,
198,
198,
48003,
276,
422,
25,
198,
5450,
1378,
12114,
710,
74,
13,
1326,
14,
26845,
14,
21987,
12,
14108,
12,
75,
4820,
12,
1659,
12,
23205,
12,
79,
4464,
72,
12,
24209,
12,
392,
12,
49075,
14,
198,
37811,
198,
11748,
40481,
82,
198,
11748,
28686,
198,
11748,
302,
198,
198,
6738,
900,
37623,
10141,
1330,
9058,
11,
1064,
62,
43789,
198,
198,
29113,
29113,
21017,
198,
198,
20608,
796,
366,
79,
893,
88,
918,
77,
1,
198,
47,
8120,
25552,
796,
685,
198,
220,
220,
220,
366,
1837,
918,
77,
62,
1676,
1462,
1600,
198,
220,
220,
220,
366,
79,
893,
88,
918,
77,
1600,
198,
220,
220,
220,
366,
79,
893,
88,
918,
77,
13,
8534,
437,
1600,
198,
220,
220,
220,
366,
79,
893,
88,
918,
77,
13,
16794,
364,
1600,
198,
60,
198,
44,
20892,
62,
34219,
796,
366,
834,
38993,
834,
13,
9078,
1,
198,
20373,
45359,
5258,
796,
14631,
4871,
1600,
366,
42348,
1600,
366,
2127,
5329,
6816,
8973,
198,
31631,
5064,
40,
4877,
796,
685,
198,
220,
220,
220,
366,
41206,
12678,
7904,
642,
532,
19174,
14,
1273,
540,
1600,
198,
220,
220,
220,
366,
5317,
1631,
7591,
1240,
7904,
34152,
1600,
198,
220,
220,
220,
366,
35364,
15417,
7904,
3594,
1600,
198,
220,
220,
220,
366,
34156,
7904,
7294,
40,
20010,
1079,
7904,
17168,
13789,
1600,
198,
220,
220,
220,
366,
18843,
803,
4482,
7904,
7294,
13362,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
362,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
362,
13,
22,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
18,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
19,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
20,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
21,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
513,
13,
22,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
46333,
7904,
16932,
7535,
1600,
198,
220,
220,
220,
366,
15167,
2229,
15417,
7904,
11361,
7904,
46333,
7904,
9485,
20519,
1600,
198,
220,
220,
220,
366,
33221,
7904,
10442,
7712,
7904,
46267,
7904,
11361,
3401,
5028,
1600,
198,
60,
198,
38604,
7036,
62,
2200,
10917,
4663,
1546,
796,
14631,
13165,
354,
8973,
198,
4480,
1280,
7203,
8897,
18883,
13,
14116,
4943,
355,
5359,
25,
198,
220,
220,
220,
3555,
796,
10352,
198,
220,
220,
220,
329,
1627,
287,
5359,
13,
961,
6615,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1627,
13,
9688,
2032,
342,
7203,
2,
350,
16309,
38162,
34571,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3555,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1627,
13,
9688,
2032,
342,
7203,
2,
23578,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3555,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1627,
13,
9688,
2032,
342,
7203,
2,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
3555,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40589,
7036,
62,
2200,
10917,
4663,
1546,
13,
33295,
7,
1370,
13,
36311,
22446,
35312,
7203,
855,
4943,
58,
15,
12962,
198,
198,
29113,
29113,
21017,
198,
198,
39,
9338,
796,
28686,
13,
6978,
13,
397,
2777,
776,
7,
418,
13,
6978,
13,
15908,
3672,
7,
834,
7753,
834,
4008,
198,
198,
4299,
1100,
46491,
42632,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10934,
281,
4112,
3108,
422,
1635,
42632,
9,
290,
290,
1441,
262,
10154,
286,
262,
198,
220,
220,
220,
7186,
2393,
13,
220,
2195,
2454,
41002,
12,
23,
21004,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
351,
40481,
82,
13,
9654,
7,
418,
13,
6978,
13,
22179,
7,
39,
9338,
11,
1635,
42632,
828,
366,
26145,
1600,
366,
40477,
12,
23,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
277,
13,
961,
3419,
198,
198,
44,
20892,
62,
25664,
796,
1100,
7,
44,
20892,
62,
34219,
8,
198,
198,
4299,
1064,
62,
28961,
7,
28961,
2599,
198,
220,
220,
220,
37227,
11627,
974,
11593,
9,
28961,
9,
834,
422,
337,
20892,
62,
25664,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
13634,
62,
15699,
796,
302,
13,
12947,
7,
198,
220,
220,
220,
220,
220,
220,
220,
374,
1,
61,
834,
90,
28961,
92,
834,
796,
37250,
7879,
16151,
58,
61,
6,
7879,
60,
28104,
17816,
7879,
60,
1911,
18982,
7,
28961,
28,
28961,
828,
198,
220,
220,
220,
220,
220,
220,
220,
337,
20892,
62,
25664,
11,
302,
13,
44,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
611,
13634,
62,
15699,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
13634,
62,
15699,
13,
8094,
7,
16,
8,
198,
220,
220,
220,
5298,
43160,
12331,
7203,
3118,
540,
284,
1064,
11593,
90,
28961,
92,
834,
4731,
526,
13,
18982,
7,
28961,
28,
28961,
4008,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
9058,
7,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
20608,
11,
198,
220,
220,
220,
220,
220,
220,
220,
6764,
28,
19796,
62,
28961,
7203,
11213,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
5964,
28,
19796,
62,
28961,
7203,
43085,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
19016,
28,
19796,
62,
28961,
7203,
9900,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
2196,
28,
19796,
62,
28961,
7203,
9641,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1772,
28,
19796,
62,
28961,
7203,
9800,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1772,
62,
12888,
28,
19796,
62,
28961,
7203,
12888,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
5529,
263,
28,
19796,
62,
28961,
7203,
9800,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
5529,
263,
62,
12888,
28,
19796,
62,
28961,
7203,
12888,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
26286,
28,
20373,
45359,
5258,
11,
198,
220,
220,
220,
220,
220,
220,
220,
890,
62,
11213,
28,
961,
7203,
15675,
11682,
13,
9132,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
890,
62,
11213,
62,
11299,
62,
4906,
2625,
5239,
14,
4102,
2902,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
10392,
28,
47,
8120,
25552,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5301,
62,
15908,
28,
4895,
1298,
366,
526,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
5301,
62,
7890,
28,
4895,
1298,
14631,
79,
893,
88,
918,
77,
35343,
15211,
13,
9078,
8973,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
19974,
62,
21230,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
13350,
28,
31631,
5064,
40,
4877,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2721,
62,
47911,
28,
38604,
7036,
62,
2200,
10917,
4663,
1546,
11,
198,
220,
220,
220,
1267,
198
] | 2.533871 | 1,240 |
REST_PATH = u""
WS_PATH = u"/api/notifications/v1"
| [
49,
6465,
62,
34219,
796,
334,
15931,
198,
19416,
62,
34219,
796,
334,
1,
14,
15042,
14,
1662,
6637,
14,
85,
16,
1,
198
] | 2.125 | 24 |
__all__ = ["load"]
import imp
import importlib
def load(name, path):
"""Load and initialize a module implemented as a Python source file and return its module object"""
if hasattr(importlib, "machinery"):
loader = importlib.machinery.SourceFileLoader(name, path)
return loader.load_module()
return imp.load_source(name, path)
| [
834,
439,
834,
796,
14631,
2220,
8973,
628,
198,
11748,
848,
198,
11748,
1330,
8019,
628,
198,
4299,
3440,
7,
3672,
11,
3108,
2599,
198,
220,
220,
220,
37227,
8912,
290,
41216,
257,
8265,
9177,
355,
257,
11361,
2723,
2393,
290,
1441,
663,
8265,
2134,
37811,
198,
220,
220,
220,
611,
468,
35226,
7,
11748,
8019,
11,
366,
76,
620,
15451,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
40213,
796,
1330,
8019,
13,
76,
620,
15451,
13,
37226,
17401,
7,
3672,
11,
3108,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
40213,
13,
2220,
62,
21412,
3419,
198,
220,
220,
220,
1441,
848,
13,
2220,
62,
10459,
7,
3672,
11,
3108,
8,
198
] | 3.033898 | 118 |
import itertools
from pygears.common.sieve import sieve
from pygears.svgen.inst import SVGenInstPlugin
from pygears.svgen.svmod import SVModuleGen
from functools import partial
from pygears.svgen.svgen import SVGenPlugin
from pygears.svgen.util import svgen_visitor
from pygears.core.hier_node import HierVisitorBase
from pygears.svgen.inst import svgen_inst
from pygears.rtl.gear import RTLGearHierVisitor, is_gear_instance
class SVGenSievePlugin(SVGenInstPlugin, SVGenPlugin):
| [
11748,
340,
861,
10141,
198,
198,
6738,
12972,
70,
4127,
13,
11321,
13,
82,
12311,
1330,
264,
12311,
198,
6738,
12972,
70,
4127,
13,
21370,
5235,
13,
8625,
1330,
20546,
13746,
6310,
37233,
198,
6738,
12972,
70,
4127,
13,
21370,
5235,
13,
21370,
4666,
1330,
20546,
26796,
13746,
198,
6738,
1257,
310,
10141,
1330,
13027,
198,
6738,
12972,
70,
4127,
13,
21370,
5235,
13,
21370,
5235,
1330,
20546,
13746,
37233,
198,
6738,
12972,
70,
4127,
13,
21370,
5235,
13,
22602,
1330,
38487,
5235,
62,
4703,
2072,
198,
6738,
12972,
70,
4127,
13,
7295,
13,
71,
959,
62,
17440,
1330,
36496,
15854,
2072,
14881,
198,
6738,
12972,
70,
4127,
13,
21370,
5235,
13,
8625,
1330,
38487,
5235,
62,
8625,
198,
6738,
12972,
70,
4127,
13,
17034,
75,
13,
31763,
1330,
11923,
43,
38141,
39,
959,
15854,
2072,
11,
318,
62,
31763,
62,
39098,
628,
628,
628,
198,
4871,
20546,
13746,
50,
12311,
37233,
7,
50,
53,
13746,
6310,
37233,
11,
20546,
13746,
37233,
2599,
198
] | 2.963415 | 164 |
#encoding=utf-8
import qlib
import pandas as pd
import pickle
import xgboost as xgb
import numpy as np
import re
from qlib.constant import REG_US
from qlib.utils import exists_qlib_data, init_instance_by_config
from qlib.workflow import R
from qlib.workflow.record_temp import SignalRecord, PortAnaRecord
from qlib.utils import flatten_dict
from qlib.data import LocalExpressionProvider
from qlib.data.ops import Operators, OpsList
from qlib.data.base import Feature
from pyecharts import options as opts
from pyecharts.charts import Kline, Line, Grid
from my_data_handler import MyAlphaHandler
# model_file = r'.\mlruns\1\d6536b056ba84a74be6b33971f443cf6\artifacts\trained_model'
model_file = r'.\mlruns\1\148ef1cd7acd48deac3eadc339ad3008\artifacts\trained_model'
with open(model_file, 'rb') as fi:
model = pickle.load(fi)
exprs, columns = MyAlphaHandler.get_custom_config()
raw_data = pd.read_csv('../stock_data/TSLA.csv', parse_dates=['time'])
raw_data['data_time'] = raw_data['time'].dt.strftime("%Y-%m-%d %H:%M:00")
raw_data.set_index('time', inplace=True)
raw_data["vwap"] = np.nan
raw_data.sort_index(inplace=True)
# print(raw_data)
Operators.register(OpsList + [MyFeature])
obj = dict()
for field in exprs:
expression = eval(my_parse_field(field))
series = expression.load('TSLA', "2022-01-02", "2022-02-28", "1min")
series = series.astype(np.float32)
obj[field] = series
data = pd.DataFrame(obj)
data.columns = columns
view_time_start = '2022-02-11'
view_time_end = '2022-02-12'
pre_data = raw_data.loc[view_time_start:view_time_end].copy()
pred=model.model.predict(xgb.DMatrix(data.loc[view_time_start:view_time_end]))
pre_data['pred_score'] = pred
records = pre_data.to_dict("records")
cash = 50000
position = {}
hold_thresh = 5
score_thresh = 0.001
x_axises, y_axises, mark_points, money = [], [], [], []
for record in records:
x_axises.append(record['data_time'])
y_axises.append([
record['open'], record['close'], record['low'], record['high']
])
if 'hold_cnt' in position:
position['hold_cnt'] += 1
if position and (record['open'] >= position['close'] * 1.01 or record['open'] < position['close'] * 0.995 or record['pred_score'] < -score_thresh or position['hold_cnt'] >= hold_thresh):
cash += position['amount'] * record['open']
position = {}
#print("sell")
mark_points.append(opts.MarkPointItem(
coord=[record['data_time'], record['high']],
symbol='triangle', symbol_size=7,
itemstyle_opts=opts.ItemStyleOpts(color="green")
))
elif record['pred_score'] > score_thresh and not position:
position = dict(record)
position['amount'] = int(cash / position['open'])
cash -= position['amount'] * position['open']
# buy
#print("buy")
position['hold_cnt'] = 0
mark_points.append(opts.MarkPointItem(
coord=[record['data_time'], record['high']],
symbol='arrow', symbol_size=7,
itemstyle_opts=opts.ItemStyleOpts(color="yellow")
))
cur_money = cash
if position:
cur_money += position['amount'] * record['close']
money.append(cur_money)
if position:
cash += position['amount'] * records[-1]['close']
print("cash:", cash)
kline_graph = (
Kline()
.add_xaxis(x_axises)
.add_yaxis(
"kline",
y_axises,
markpoint_opts=opts.MarkPointOpts(
data=mark_points
),
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
),
title_opts=opts.TitleOpts(title="%s_%s" % (view_time_start, view_time_end)),
datazoom_opts=[opts.DataZoomOpts(type_="inside", xaxis_index=[0, 1],)],
)
)
kline_line = (
Line()
.add_xaxis(xaxis_data=x_axises)
.add_yaxis(
series_name="cur_money",
y_axis=money,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(opacity=0.5),
label_opts=opts.LabelOpts(is_show=False),
markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(y=50000)]
),
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=2,
axislabel_opts=opts.LabelOpts(is_show=False),
),
yaxis_opts=opts.AxisOpts(
min_='dataMin'
)
)
)
grid_chart = Grid(init_opts=opts.InitOpts(width='2000px', height='900px'))
grid_chart.add(
kline_graph,
grid_opts=opts.GridOpts(pos_left="3%", pos_right="10%", height="50%"),
)
grid_chart.add(
kline_line,
grid_opts=opts.GridOpts(
pos_left="3%", pos_right="10%", pos_top="60%", height="30%"
),
)
grid_chart.render("kline_markline.html") | [
2,
12685,
7656,
28,
40477,
12,
23,
198,
11748,
10662,
8019,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
2298,
293,
198,
11748,
2124,
70,
39521,
355,
2124,
22296,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
302,
198,
6738,
10662,
8019,
13,
9979,
415,
1330,
23337,
62,
2937,
198,
6738,
10662,
8019,
13,
26791,
1330,
7160,
62,
80,
8019,
62,
7890,
11,
2315,
62,
39098,
62,
1525,
62,
11250,
198,
6738,
10662,
8019,
13,
1818,
11125,
1330,
371,
198,
6738,
10662,
8019,
13,
1818,
11125,
13,
22105,
62,
29510,
1330,
26484,
23739,
11,
4347,
2025,
64,
23739,
198,
6738,
10662,
8019,
13,
26791,
1330,
27172,
268,
62,
11600,
198,
6738,
10662,
8019,
13,
7890,
1330,
10714,
16870,
2234,
29495,
198,
6738,
10662,
8019,
13,
7890,
13,
2840,
1330,
6564,
2024,
11,
26123,
8053,
198,
6738,
10662,
8019,
13,
7890,
13,
8692,
1330,
27018,
198,
6738,
12972,
3055,
5889,
1330,
3689,
355,
2172,
82,
198,
6738,
12972,
3055,
5889,
13,
354,
5889,
1330,
509,
1370,
11,
6910,
11,
24846,
198,
6738,
616,
62,
7890,
62,
30281,
1330,
2011,
38077,
25060,
198,
198,
2,
2746,
62,
7753,
796,
374,
4458,
59,
4029,
48381,
59,
16,
59,
67,
2996,
2623,
65,
2713,
21,
7012,
5705,
64,
4524,
1350,
21,
65,
29626,
4869,
69,
34938,
12993,
21,
59,
50179,
59,
35311,
62,
19849,
6,
198,
19849,
62,
7753,
796,
374,
4458,
59,
4029,
48381,
59,
16,
59,
18294,
891,
16,
10210,
22,
330,
67,
2780,
2934,
330,
18,
1329,
66,
29626,
324,
6200,
23,
59,
50179,
59,
35311,
62,
19849,
6,
198,
4480,
1280,
7,
19849,
62,
7753,
11,
705,
26145,
11537,
355,
25912,
25,
198,
220,
220,
220,
2746,
796,
2298,
293,
13,
2220,
7,
12463,
8,
198,
198,
31937,
82,
11,
15180,
796,
2011,
38077,
25060,
13,
1136,
62,
23144,
62,
11250,
3419,
628,
198,
1831,
62,
7890,
796,
279,
67,
13,
961,
62,
40664,
10786,
40720,
13578,
62,
7890,
14,
4694,
13534,
13,
40664,
3256,
21136,
62,
19581,
28,
17816,
2435,
6,
12962,
198,
1831,
62,
7890,
17816,
7890,
62,
2435,
20520,
796,
8246,
62,
7890,
17816,
2435,
6,
4083,
28664,
13,
2536,
31387,
7203,
4,
56,
12,
4,
76,
12,
4,
67,
4064,
39,
25,
4,
44,
25,
405,
4943,
198,
1831,
62,
7890,
13,
2617,
62,
9630,
10786,
2435,
3256,
287,
5372,
28,
17821,
8,
198,
1831,
62,
7890,
14692,
85,
86,
499,
8973,
796,
45941,
13,
12647,
198,
1831,
62,
7890,
13,
30619,
62,
9630,
7,
259,
5372,
28,
17821,
8,
198,
2,
3601,
7,
1831,
62,
7890,
8,
198,
18843,
2024,
13,
30238,
7,
41472,
8053,
1343,
685,
3666,
38816,
12962,
198,
198,
26801,
796,
8633,
3419,
198,
1640,
2214,
287,
1033,
3808,
25,
198,
220,
220,
220,
5408,
796,
5418,
7,
1820,
62,
29572,
62,
3245,
7,
3245,
4008,
198,
220,
220,
220,
2168,
796,
5408,
13,
2220,
10786,
4694,
13534,
3256,
366,
1238,
1828,
12,
486,
12,
2999,
1600,
366,
1238,
1828,
12,
2999,
12,
2078,
1600,
366,
16,
1084,
4943,
198,
220,
220,
220,
2168,
796,
2168,
13,
459,
2981,
7,
37659,
13,
22468,
2624,
8,
198,
220,
220,
220,
26181,
58,
3245,
60,
796,
2168,
198,
7890,
796,
279,
67,
13,
6601,
19778,
7,
26801,
8,
198,
7890,
13,
28665,
82,
796,
15180,
198,
198,
1177,
62,
2435,
62,
9688,
796,
705,
1238,
1828,
12,
2999,
12,
1157,
6,
198,
1177,
62,
2435,
62,
437,
796,
705,
1238,
1828,
12,
2999,
12,
1065,
6,
198,
198,
3866,
62,
7890,
796,
8246,
62,
7890,
13,
17946,
58,
1177,
62,
2435,
62,
9688,
25,
1177,
62,
2435,
62,
437,
4083,
30073,
3419,
198,
28764,
28,
19849,
13,
19849,
13,
79,
17407,
7,
87,
22296,
13,
35,
46912,
7,
7890,
13,
17946,
58,
1177,
62,
2435,
62,
9688,
25,
1177,
62,
2435,
62,
437,
60,
4008,
198,
3866,
62,
7890,
17816,
28764,
62,
26675,
20520,
796,
2747,
198,
8344,
3669,
796,
662,
62,
7890,
13,
1462,
62,
11600,
7203,
8344,
3669,
4943,
198,
198,
30350,
796,
642,
2388,
198,
9150,
796,
23884,
198,
2946,
62,
400,
3447,
796,
642,
198,
26675,
62,
400,
3447,
796,
657,
13,
8298,
198,
87,
62,
897,
2696,
11,
331,
62,
897,
2696,
11,
1317,
62,
13033,
11,
1637,
796,
685,
4357,
685,
4357,
685,
4357,
17635,
198,
1640,
1700,
287,
4406,
25,
198,
220,
220,
220,
2124,
62,
897,
2696,
13,
33295,
7,
22105,
17816,
7890,
62,
2435,
6,
12962,
198,
220,
220,
220,
331,
62,
897,
2696,
13,
33295,
26933,
198,
220,
220,
220,
220,
220,
220,
220,
1700,
17816,
9654,
6,
4357,
1700,
17816,
19836,
6,
4357,
1700,
17816,
9319,
6,
4357,
1700,
17816,
8929,
20520,
198,
220,
220,
220,
33761,
198,
220,
220,
220,
611,
705,
2946,
62,
66,
429,
6,
287,
2292,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
17816,
2946,
62,
66,
429,
20520,
15853,
352,
198,
220,
220,
220,
611,
2292,
290,
357,
22105,
17816,
9654,
20520,
18189,
2292,
17816,
19836,
20520,
1635,
352,
13,
486,
393,
1700,
17816,
9654,
20520,
1279,
2292,
17816,
19836,
20520,
1635,
657,
13,
33438,
393,
1700,
17816,
28764,
62,
26675,
20520,
1279,
532,
26675,
62,
400,
3447,
393,
2292,
17816,
2946,
62,
66,
429,
20520,
18189,
1745,
62,
400,
3447,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5003,
15853,
2292,
17816,
17287,
20520,
1635,
1700,
17816,
9654,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4798,
7203,
7255,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
1317,
62,
13033,
13,
33295,
7,
404,
912,
13,
9704,
12727,
7449,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6349,
41888,
22105,
17816,
7890,
62,
2435,
6,
4357,
1700,
17816,
8929,
20520,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6194,
11639,
28461,
9248,
3256,
6194,
62,
7857,
28,
22,
11,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2378,
7635,
62,
404,
912,
28,
404,
912,
13,
7449,
21466,
27871,
82,
7,
8043,
2625,
14809,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
15306,
198,
220,
220,
220,
1288,
361,
1700,
17816,
28764,
62,
26675,
20520,
1875,
4776,
62,
400,
3447,
290,
407,
2292,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
796,
8633,
7,
22105,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
17816,
17287,
20520,
796,
493,
7,
30350,
1220,
2292,
17816,
9654,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
5003,
48185,
2292,
17816,
17287,
20520,
1635,
2292,
17816,
9654,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2822,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4798,
7203,
17846,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
2292,
17816,
2946,
62,
66,
429,
20520,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1317,
62,
13033,
13,
33295,
7,
404,
912,
13,
9704,
12727,
7449,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6349,
41888,
22105,
17816,
7890,
62,
2435,
6,
4357,
1700,
17816,
8929,
20520,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6194,
11639,
6018,
3256,
6194,
62,
7857,
28,
22,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2378,
7635,
62,
404,
912,
28,
404,
912,
13,
7449,
21466,
27871,
82,
7,
8043,
2625,
36022,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
15306,
198,
220,
220,
220,
1090,
62,
26316,
796,
5003,
198,
220,
220,
220,
611,
2292,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1090,
62,
26316,
15853,
2292,
17816,
17287,
20520,
1635,
1700,
17816,
19836,
20520,
198,
220,
220,
220,
1637,
13,
33295,
7,
22019,
62,
26316,
8,
198,
361,
2292,
25,
198,
220,
220,
220,
5003,
15853,
2292,
17816,
17287,
20520,
1635,
4406,
58,
12,
16,
7131,
6,
19836,
20520,
198,
4798,
7203,
30350,
25,
1600,
5003,
8,
198,
198,
74,
1370,
62,
34960,
796,
357,
198,
220,
220,
220,
509,
1370,
3419,
198,
220,
220,
220,
764,
2860,
62,
87,
22704,
7,
87,
62,
897,
2696,
8,
198,
220,
220,
220,
764,
2860,
62,
88,
22704,
7,
198,
220,
220,
220,
220,
220,
220,
220,
366,
74,
1370,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
331,
62,
897,
2696,
11,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1317,
4122,
62,
404,
912,
28,
404,
912,
13,
9704,
12727,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
28,
4102,
62,
13033,
198,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
764,
2617,
62,
20541,
62,
404,
912,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
22704,
62,
404,
912,
28,
404,
912,
13,
31554,
271,
27871,
82,
7,
271,
62,
9888,
28,
17821,
828,
198,
220,
220,
220,
220,
220,
220,
220,
331,
22704,
62,
404,
912,
28,
404,
912,
13,
31554,
271,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
9888,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6626,
20337,
62,
404,
912,
28,
404,
912,
13,
41205,
30547,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
12860,
28,
17821,
11,
389,
459,
2349,
62,
404,
912,
28,
404,
912,
13,
30547,
21466,
27871,
82,
7,
404,
4355,
28,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
220,
220,
220,
220,
3670,
62,
404,
912,
28,
404,
912,
13,
19160,
27871,
82,
7,
7839,
2625,
4,
82,
62,
4,
82,
1,
4064,
357,
1177,
62,
2435,
62,
9688,
11,
1570,
62,
2435,
62,
437,
36911,
198,
220,
220,
220,
220,
220,
220,
220,
4818,
1031,
4207,
62,
404,
912,
41888,
404,
912,
13,
6601,
57,
4207,
27871,
82,
7,
4906,
62,
2625,
48787,
1600,
2124,
22704,
62,
9630,
41888,
15,
11,
352,
4357,
8,
4357,
198,
220,
220,
220,
1267,
198,
8,
198,
198,
74,
1370,
62,
1370,
796,
357,
198,
220,
220,
220,
6910,
3419,
198,
220,
220,
220,
764,
2860,
62,
87,
22704,
7,
87,
22704,
62,
7890,
28,
87,
62,
897,
2696,
8,
198,
220,
220,
220,
764,
2860,
62,
88,
22704,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2168,
62,
3672,
2625,
22019,
62,
26316,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
331,
62,
22704,
28,
26316,
11,
198,
220,
220,
220,
220,
220,
220,
220,
318,
62,
5796,
5226,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
9493,
10992,
62,
404,
912,
28,
404,
912,
13,
13949,
21466,
27871,
82,
7,
404,
4355,
28,
15,
13,
20,
828,
198,
220,
220,
220,
220,
220,
220,
220,
6167,
62,
404,
912,
28,
404,
912,
13,
33986,
27871,
82,
7,
271,
62,
12860,
28,
25101,
828,
198,
220,
220,
220,
220,
220,
220,
220,
1317,
1370,
62,
404,
912,
28,
404,
912,
13,
9704,
13949,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
41888,
404,
912,
13,
9704,
13949,
7449,
7,
88,
28,
20,
2388,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
764,
2617,
62,
20541,
62,
404,
912,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
22704,
62,
404,
912,
28,
404,
912,
13,
31554,
271,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
62,
2625,
22872,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
9630,
28,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7877,
3044,
9608,
62,
404,
912,
28,
404,
912,
13,
33986,
27871,
82,
7,
271,
62,
12860,
28,
25101,
828,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
220,
220,
220,
220,
331,
22704,
62,
404,
912,
28,
404,
912,
13,
31554,
271,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
62,
11639,
7890,
9452,
6,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
1267,
198,
8,
198,
198,
25928,
62,
40926,
796,
24846,
7,
15003,
62,
404,
912,
28,
404,
912,
13,
31768,
27871,
82,
7,
10394,
11639,
11024,
8416,
3256,
6001,
11639,
12865,
8416,
6,
4008,
198,
25928,
62,
40926,
13,
2860,
7,
198,
220,
220,
220,
479,
1370,
62,
34960,
11,
198,
220,
220,
220,
10706,
62,
404,
912,
28,
404,
912,
13,
41339,
27871,
82,
7,
1930,
62,
9464,
2625,
18,
4,
1600,
1426,
62,
3506,
2625,
940,
4,
1600,
6001,
2625,
1120,
4,
12340,
198,
8,
198,
25928,
62,
40926,
13,
2860,
7,
198,
220,
220,
220,
479,
1370,
62,
1370,
11,
198,
220,
220,
220,
10706,
62,
404,
912,
28,
404,
912,
13,
41339,
27871,
82,
7,
198,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
9464,
2625,
18,
4,
1600,
1426,
62,
3506,
2625,
940,
4,
1600,
1426,
62,
4852,
2625,
1899,
4,
1600,
6001,
2625,
1270,
39658,
198,
220,
220,
220,
10612,
198,
8,
198,
25928,
62,
40926,
13,
13287,
7203,
74,
1370,
62,
4102,
1370,
13,
6494,
4943
] | 2.186313 | 2,265 |
from fastapi import APIRouter
router = APIRouter()
| [
6738,
3049,
15042,
1330,
3486,
4663,
39605,
198,
198,
472,
353,
796,
3486,
4663,
39605,
3419,
628
] | 3.117647 | 17 |
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import networkx as nx
import time
from embed_methods.dgi.models import DGI, LogReg
from embed_methods.dgi.utils import process
| [
11748,
299,
32152,
355,
45941,
198,
11748,
629,
541,
88,
13,
82,
29572,
355,
599,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
3127,
87,
355,
299,
87,
198,
11748,
640,
198,
198,
6738,
11525,
62,
24396,
82,
13,
67,
12397,
13,
27530,
1330,
360,
18878,
11,
5972,
8081,
198,
6738,
11525,
62,
24396,
82,
13,
67,
12397,
13,
26791,
1330,
1429,
198
] | 3.058824 | 68 |
"""Deploys binaries to a GitHub release given the specified tag name."""
import argparse
import os
import time
from github import Github
THIS_FILE_DIRECTORY = os.path.dirname(os.path.realpath(__file__))
GH_REPO_IDENT = "ETCLabs/RDMnet"
GH_USERNAME = "svc-etclabs"
GH_API_TOKEN = os.getenv("SVC_ETCLABS_REPO_TOKEN")
def deploy_binaries(version: str):
"""Deploys staged binaries to a new GitHub Release."""
g = Github(login_or_token=GH_USERNAME, password=GH_API_TOKEN)
repo = g.get_repo(GH_REPO_IDENT)
print(f"Waiting for the correct GitHub tag v{version} to become available...")
keep_trying = True
while keep_trying:
for tag in repo.get_tags():
if tag.name == f"v{version}":
keep_trying = False # Tag now exists
break
if keep_trying:
time.sleep(5)
print(f"Tag v{version} available. Creating release...")
new_release = repo.create_git_release(
tag=f"v{version}",
name=f"RDMnet v{version}",
message=f"Automated release of RDMnet for v{version}",
)
new_release.upload_asset("RDMnetSetup_x86.msi")
new_release.upload_asset("RDMnetSetup_x64.msi")
new_release.upload_asset("RDMnet.pkg")
if __name__ == "__main__":
main()
| [
37811,
49322,
82,
38640,
284,
257,
21722,
2650,
1813,
262,
7368,
7621,
1438,
526,
15931,
198,
11748,
1822,
29572,
198,
11748,
28686,
198,
11748,
640,
198,
198,
6738,
33084,
1330,
38994,
198,
198,
43559,
62,
25664,
62,
17931,
23988,
15513,
796,
28686,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
5305,
6978,
7,
834,
7753,
834,
4008,
198,
17511,
62,
2200,
16402,
62,
25256,
796,
366,
2767,
5097,
8937,
14,
49,
23127,
3262,
1,
198,
17511,
62,
29904,
20608,
796,
366,
21370,
66,
12,
316,
565,
8937,
1,
198,
17511,
62,
17614,
62,
10468,
43959,
796,
28686,
13,
1136,
24330,
7203,
50,
15922,
62,
2767,
16827,
4462,
62,
2200,
16402,
62,
10468,
43959,
4943,
198,
198,
4299,
6061,
62,
8800,
3166,
7,
9641,
25,
965,
2599,
198,
220,
220,
220,
37227,
49322,
82,
23393,
38640,
284,
257,
649,
21722,
13868,
526,
15931,
198,
220,
220,
220,
308,
796,
38994,
7,
38235,
62,
273,
62,
30001,
28,
17511,
62,
29904,
20608,
11,
9206,
28,
17511,
62,
17614,
62,
10468,
43959,
8,
198,
220,
220,
220,
29924,
796,
308,
13,
1136,
62,
260,
7501,
7,
17511,
62,
2200,
16402,
62,
25256,
8,
628,
220,
220,
220,
3601,
7,
69,
1,
33484,
1780,
329,
262,
3376,
21722,
7621,
410,
90,
9641,
92,
284,
1716,
1695,
9313,
8,
628,
220,
220,
220,
1394,
62,
83,
14992,
796,
6407,
198,
220,
220,
220,
981,
1394,
62,
83,
14992,
25,
198,
220,
220,
220,
220,
220,
220,
220,
329,
7621,
287,
29924,
13,
1136,
62,
31499,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
7621,
13,
3672,
6624,
277,
1,
85,
90,
9641,
92,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1394,
62,
83,
14992,
796,
10352,
220,
1303,
17467,
783,
7160,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1394,
62,
83,
14992,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
20,
8,
628,
220,
220,
220,
3601,
7,
69,
1,
24835,
410,
90,
9641,
92,
1695,
13,
30481,
2650,
9313,
8,
198,
220,
220,
220,
649,
62,
20979,
796,
29924,
13,
17953,
62,
18300,
62,
20979,
7,
198,
220,
220,
220,
220,
220,
220,
220,
7621,
28,
69,
1,
85,
90,
9641,
92,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
69,
1,
49,
23127,
3262,
410,
90,
9641,
92,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
3275,
28,
69,
1,
38062,
515,
2650,
286,
371,
23127,
3262,
329,
410,
90,
9641,
92,
1600,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
649,
62,
20979,
13,
25850,
62,
562,
316,
7203,
49,
23127,
3262,
40786,
62,
87,
4521,
13,
907,
72,
4943,
198,
220,
220,
220,
649,
62,
20979,
13,
25850,
62,
562,
316,
7203,
49,
23127,
3262,
40786,
62,
87,
2414,
13,
907,
72,
4943,
198,
220,
220,
220,
649,
62,
20979,
13,
25850,
62,
562,
316,
7203,
49,
23127,
3262,
13,
35339,
4943,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.350554 | 542 |
import logging
import numpy
from ..Fragments import Fragments
from ..typing import SpectrumType
logger = logging.getLogger("matchms")
def add_losses(spectrum_in: SpectrumType, loss_mz_from=0.0, loss_mz_to=1000.0) -> SpectrumType:
"""Derive losses based on precursor mass.
Parameters
----------
spectrum_in:
Input spectrum.
loss_mz_from:
Minimum allowed m/z value for losses. Default is 0.0.
loss_mz_to:
Maximum allowed m/z value for losses. Default is 1000.0.
"""
if spectrum_in is None:
return None
spectrum = spectrum_in.clone()
precursor_mz = spectrum.get("precursor_mz", None)
if precursor_mz:
assert isinstance(precursor_mz, (float, int)), ("Expected 'precursor_mz' to be a scalar number.",
"Consider applying 'add_precursor_mz' filter first.")
peaks_mz, peaks_intensities = spectrum.peaks.mz, spectrum.peaks.intensities
losses_mz = (precursor_mz - peaks_mz)[::-1]
losses_intensities = peaks_intensities[::-1]
# Add losses which are within given boundaries
mask = numpy.where((losses_mz >= loss_mz_from)
& (losses_mz <= loss_mz_to))
spectrum.losses = Fragments(mz=losses_mz[mask],
intensities=losses_intensities[mask])
else:
logger.warning("No precursor_mz found. Consider applying 'add_precursor_mz' filter first.")
return spectrum
| [
11748,
18931,
198,
11748,
299,
32152,
198,
6738,
11485,
42974,
902,
1330,
24229,
902,
198,
6738,
11485,
774,
13886,
1330,
27217,
6030,
628,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7203,
15699,
907,
4943,
628,
198,
4299,
751,
62,
22462,
274,
7,
4443,
6582,
62,
259,
25,
27217,
6030,
11,
2994,
62,
76,
89,
62,
6738,
28,
15,
13,
15,
11,
2994,
62,
76,
89,
62,
1462,
28,
12825,
13,
15,
8,
4613,
27217,
6030,
25,
198,
220,
220,
220,
37227,
28532,
425,
9089,
1912,
319,
34826,
2347,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
10958,
62,
259,
25,
198,
220,
220,
220,
220,
220,
220,
220,
23412,
10958,
13,
198,
220,
220,
220,
2994,
62,
76,
89,
62,
6738,
25,
198,
220,
220,
220,
220,
220,
220,
220,
26265,
3142,
285,
14,
89,
1988,
329,
9089,
13,
15161,
318,
657,
13,
15,
13,
198,
220,
220,
220,
2994,
62,
76,
89,
62,
1462,
25,
198,
220,
220,
220,
220,
220,
220,
220,
22246,
3142,
285,
14,
89,
1988,
329,
9089,
13,
15161,
318,
8576,
13,
15,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
10958,
62,
259,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
628,
220,
220,
220,
10958,
796,
10958,
62,
259,
13,
21018,
3419,
628,
220,
220,
220,
34826,
62,
76,
89,
796,
10958,
13,
1136,
7203,
3866,
66,
21471,
62,
76,
89,
1600,
6045,
8,
198,
220,
220,
220,
611,
34826,
62,
76,
89,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
318,
39098,
7,
3866,
66,
21471,
62,
76,
89,
11,
357,
22468,
11,
493,
36911,
5855,
3109,
7254,
705,
3866,
66,
21471,
62,
76,
89,
6,
284,
307,
257,
16578,
283,
1271,
33283,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
19626,
11524,
705,
2860,
62,
3866,
66,
21471,
62,
76,
89,
6,
8106,
717,
19570,
198,
220,
220,
220,
220,
220,
220,
220,
25740,
62,
76,
89,
11,
25740,
62,
600,
641,
871,
796,
10958,
13,
431,
4730,
13,
76,
89,
11,
10958,
13,
431,
4730,
13,
600,
641,
871,
198,
220,
220,
220,
220,
220,
220,
220,
9089,
62,
76,
89,
796,
357,
3866,
66,
21471,
62,
76,
89,
532,
25740,
62,
76,
89,
38381,
3712,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
9089,
62,
600,
641,
871,
796,
25740,
62,
600,
641,
871,
58,
3712,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
9089,
543,
389,
1626,
1813,
13215,
198,
220,
220,
220,
220,
220,
220,
220,
9335,
796,
299,
32152,
13,
3003,
19510,
22462,
274,
62,
76,
89,
18189,
2994,
62,
76,
89,
62,
6738,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1222,
357,
22462,
274,
62,
76,
89,
19841,
2994,
62,
76,
89,
62,
1462,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
10958,
13,
22462,
274,
796,
24229,
902,
7,
76,
89,
28,
22462,
274,
62,
76,
89,
58,
27932,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17509,
871,
28,
22462,
274,
62,
600,
641,
871,
58,
27932,
12962,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
49706,
13,
43917,
7203,
2949,
34826,
62,
76,
89,
1043,
13,
12642,
11524,
705,
2860,
62,
3866,
66,
21471,
62,
76,
89,
6,
8106,
717,
19570,
628,
220,
220,
220,
1441,
10958,
198
] | 2.258209 | 670 |
import re
from .dict_functions import gen_schema, ParameterSchema, sort_dict
from cornflow_client.constants import JSON_TYPES, DATASCHEMA
| [
11748,
302,
198,
6738,
764,
11600,
62,
12543,
2733,
1330,
2429,
62,
15952,
2611,
11,
25139,
2357,
27054,
2611,
11,
3297,
62,
11600,
198,
6738,
11676,
11125,
62,
16366,
13,
9979,
1187,
1330,
19449,
62,
9936,
47,
1546,
11,
360,
1404,
1921,
3398,
27630,
628
] | 3.088889 | 45 |
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import platform
import unittest
import rspub.util.resourcefilter as rf
| [
2,
0,
1220,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
28686,
198,
11748,
3859,
198,
11748,
555,
715,
395,
198,
198,
11748,
374,
2777,
549,
13,
22602,
13,
31092,
24455,
355,
374,
69,
628,
628,
628,
628,
628,
198
] | 2.545455 | 55 |
import os
import testinfra.utils.ansible_runner
testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner(
os.environ['MOLECULE_INVENTORY_FILE']).get_hosts('all')
def test_package(host):
""" check if packages are installed
"""
assert host.package('grafana').is_installed
def test_service(host):
""" Testing whether the service is running and enabled
"""
assert host.service('grafana-server').is_enabled
assert host.service('grafana-server').is_running
| [
11748,
28686,
198,
198,
11748,
1332,
10745,
430,
13,
26791,
13,
504,
856,
62,
16737,
198,
198,
9288,
10745,
430,
62,
4774,
82,
796,
1332,
10745,
430,
13,
26791,
13,
504,
856,
62,
16737,
13,
2025,
82,
856,
49493,
7,
198,
220,
220,
220,
28686,
13,
268,
2268,
17816,
11770,
2538,
34,
24212,
62,
1268,
53,
3525,
15513,
62,
25664,
20520,
737,
1136,
62,
4774,
82,
10786,
439,
11537,
628,
198,
4299,
1332,
62,
26495,
7,
4774,
2599,
198,
220,
220,
220,
37227,
2198,
611,
10392,
389,
6589,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6818,
2583,
13,
26495,
10786,
70,
32188,
2271,
27691,
271,
62,
37050,
628,
198,
4299,
1332,
62,
15271,
7,
4774,
2599,
198,
220,
220,
220,
37227,
23983,
1771,
262,
2139,
318,
2491,
290,
9343,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6818,
2583,
13,
15271,
10786,
70,
32188,
2271,
12,
15388,
27691,
271,
62,
25616,
198,
220,
220,
220,
6818,
2583,
13,
15271,
10786,
70,
32188,
2271,
12,
15388,
27691,
271,
62,
20270,
198
] | 2.861272 | 173 |
"""Class representations of heatsinks."""
import math
from scipy import constants as const
from materials import Aluminium_6063 as aluminium
| [
37811,
9487,
24612,
286,
37876,
2973,
526,
15931,
198,
198,
11748,
10688,
198,
6738,
629,
541,
88,
1330,
38491,
355,
1500,
198,
198,
6738,
5696,
1330,
978,
35241,
62,
1899,
5066,
355,
40412,
628,
198
] | 4.142857 | 35 |
import inspect
foo() | [
11748,
10104,
220,
198,
220,
198,
21943,
3419
] | 2.875 | 8 |
import base58
from plenum.common.signer_did import DidSigner
from plenum.common.verifier import DidVerifier
from plenum.common.eventually import eventually
from plenum.test.helper import assertEquality
from sovrin.common.identity import Identity
MsgForSigning = {'sender': 'Mario', 'msg': 'Lorem ipsum'}
| [
11748,
2779,
3365,
198,
6738,
458,
44709,
13,
11321,
13,
12683,
263,
62,
20839,
1330,
7731,
11712,
263,
198,
6738,
458,
44709,
13,
11321,
13,
332,
7483,
1330,
7731,
13414,
7483,
198,
6738,
458,
44709,
13,
11321,
13,
15596,
935,
1330,
4191,
198,
6738,
458,
44709,
13,
9288,
13,
2978,
525,
1330,
6818,
36,
13237,
198,
198,
6738,
523,
85,
12769,
13,
11321,
13,
738,
414,
1330,
27207,
198,
198,
50108,
1890,
11712,
278,
796,
1391,
6,
82,
2194,
10354,
705,
42315,
3256,
705,
19662,
10354,
705,
43,
29625,
220,
2419,
388,
6,
92,
628,
628,
628,
628,
628
] | 3.181818 | 99 |
import astropy
import datetime
import numpy as np
from edibles.utils.edibles_spectrum import EdiblesSpectrum
if __name__ == "__main__":
filename = "HD170740_w860_redl_20140915_O12.fits"
testEdiblesSpectrum(filename=filename)
| [
11748,
6468,
28338,
198,
11748,
4818,
8079,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
1225,
18764,
13,
26791,
13,
276,
18764,
62,
4443,
6582,
1330,
1717,
18764,
49738,
6582,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
628,
220,
220,
220,
29472,
796,
366,
10227,
1558,
2998,
1821,
62,
86,
45039,
62,
445,
75,
62,
1264,
29416,
1314,
62,
46,
1065,
13,
21013,
1,
198,
220,
220,
220,
1332,
7407,
18764,
49738,
6582,
7,
34345,
28,
34345,
8,
198
] | 2.788235 | 85 |
# Copyright (c) 2010-2013 OpenStack, LLC.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Methods & Attributes for shared 'on-disk' data layouts."""
import os
import sys
import errno
from hashlib import md5
from random import shuffle
from ConfigParser import ConfigParser, NoSectionError, NoOptionError
from swift import gettext_ as _
from swift.common.utils import listdir, quote
# Used by hash_path to offer a bit more security when generating hashes for
# paths. It simply appends this value to all paths; guessing the hash a path
# will end up with would also require knowing this suffix.
_hash_conf = ConfigParser()
HASH_PATH_SUFFIX = ''
HASH_PATH_PREFIX = ''
if _hash_conf.read('/etc/swift/swift.conf'):
try:
HASH_PATH_SUFFIX = _hash_conf.get('swift-hash',
'swift_hash_path_suffix')
except (NoSectionError, NoOptionError):
pass
try:
HASH_PATH_PREFIX = _hash_conf.get('swift-hash',
'swift_hash_path_prefix')
except (NoSectionError, NoOptionError):
pass
def hash_path(account, container=None, object=None, raw_digest=False):
"""
Get the canonical hash for an account/container/object
:param account: Account
:param container: Container
:param object: Object
:param raw_digest: If True, return the raw version rather than a hex digest
:returns: hash string
"""
if object and not container:
raise ValueError('container is required if object is provided')
paths = [account]
if container:
paths.append(container)
if object:
paths.append(object)
if raw_digest:
return md5(HASH_PATH_PREFIX + '/' + '/'.join(paths)
+ HASH_PATH_SUFFIX).digest()
else:
return md5(HASH_PATH_PREFIX + '/' + '/'.join(paths)
+ HASH_PATH_SUFFIX).hexdigest()
def normalize_timestamp(timestamp):
"""
Format a timestamp (string or numeric) into a standardized
xxxxxxxxxx.xxxxx (10.5) format.
Note that timestamps using values greater than or equal to November 20th,
2286 at 17:46 UTC will use 11 digits to represent the number of
seconds.
:param timestamp: unix timestamp
:returns: normalized timestamp as a string
"""
return "%016.05f" % (float(timestamp))
def validate_device_partition(device, partition):
"""
Validate that a device and a partition are valid and won't lead to
directory traversal when used.
:param device: device to validate
:param partition: partition to validate
:raises: ValueError if given an invalid device or partition
"""
invalid_device = False
invalid_partition = False
if not device or '/' in device or device in ['.', '..']:
invalid_device = True
if not partition or '/' in partition or partition in ['.', '..']:
invalid_partition = True
if invalid_device:
raise ValueError('Invalid device: %s' % quote(device or ''))
elif invalid_partition:
raise ValueError('Invalid partition: %s' % quote(partition or ''))
def storage_directory(datadir, partition, name_hash):
"""
Get the storage directory
:param datadir: Base data directory
:param partition: Partition
:param name_hash: Account, container or object name hash
:returns: Storage directory
"""
return os.path.join(datadir, str(partition), name_hash[-3:], name_hash)
| [
2,
15069,
357,
66,
8,
3050,
12,
6390,
4946,
25896,
11,
11419,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
198,
2,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
37811,
46202,
1222,
49213,
329,
4888,
705,
261,
12,
39531,
6,
1366,
38489,
526,
15931,
198,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
11454,
3919,
198,
198,
6738,
12234,
8019,
1330,
45243,
20,
198,
6738,
4738,
1330,
36273,
198,
6738,
17056,
46677,
1330,
17056,
46677,
11,
1400,
16375,
12331,
11,
1400,
19722,
12331,
198,
198,
6738,
14622,
1330,
651,
5239,
62,
355,
4808,
198,
6738,
14622,
13,
11321,
13,
26791,
1330,
1351,
15908,
11,
9577,
198,
198,
2,
16718,
416,
12234,
62,
6978,
284,
2897,
257,
1643,
517,
2324,
618,
15453,
46621,
329,
198,
2,
13532,
13,
632,
2391,
598,
2412,
428,
1988,
284,
477,
13532,
26,
25260,
262,
12234,
257,
3108,
198,
2,
481,
886,
510,
351,
561,
635,
2421,
6970,
428,
35488,
13,
198,
62,
17831,
62,
10414,
796,
17056,
46677,
3419,
198,
39,
11211,
62,
34219,
62,
12564,
5777,
10426,
796,
10148,
198,
39,
11211,
62,
34219,
62,
47,
31688,
10426,
796,
10148,
198,
361,
4808,
17831,
62,
10414,
13,
961,
10786,
14,
14784,
14,
2032,
2135,
14,
2032,
2135,
13,
10414,
6,
2599,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
367,
11211,
62,
34219,
62,
12564,
5777,
10426,
796,
4808,
17831,
62,
10414,
13,
1136,
10786,
2032,
2135,
12,
17831,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2032,
2135,
62,
17831,
62,
6978,
62,
37333,
844,
11537,
198,
220,
220,
220,
2845,
357,
2949,
16375,
12331,
11,
1400,
19722,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
367,
11211,
62,
34219,
62,
47,
31688,
10426,
796,
4808,
17831,
62,
10414,
13,
1136,
10786,
2032,
2135,
12,
17831,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2032,
2135,
62,
17831,
62,
6978,
62,
40290,
11537,
198,
220,
220,
220,
2845,
357,
2949,
16375,
12331,
11,
1400,
19722,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
628,
198,
198,
4299,
12234,
62,
6978,
7,
23317,
11,
9290,
28,
14202,
11,
2134,
28,
14202,
11,
8246,
62,
12894,
395,
28,
25101,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3497,
262,
40091,
12234,
329,
281,
1848,
14,
34924,
14,
15252,
628,
220,
220,
220,
1058,
17143,
1848,
25,
10781,
198,
220,
220,
220,
1058,
17143,
9290,
25,
43101,
198,
220,
220,
220,
1058,
17143,
2134,
25,
9515,
198,
220,
220,
220,
1058,
17143,
8246,
62,
12894,
395,
25,
1002,
6407,
11,
1441,
262,
8246,
2196,
2138,
621,
257,
17910,
16274,
198,
220,
220,
220,
1058,
7783,
82,
25,
12234,
4731,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
2134,
290,
407,
9290,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
10786,
34924,
318,
2672,
611,
2134,
318,
2810,
11537,
198,
220,
220,
220,
13532,
796,
685,
23317,
60,
198,
220,
220,
220,
611,
9290,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13532,
13,
33295,
7,
34924,
8,
198,
220,
220,
220,
611,
2134,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13532,
13,
33295,
7,
15252,
8,
198,
220,
220,
220,
611,
8246,
62,
12894,
395,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
45243,
20,
7,
39,
11211,
62,
34219,
62,
47,
31688,
10426,
1343,
31051,
6,
1343,
31051,
4458,
22179,
7,
6978,
82,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1343,
367,
11211,
62,
34219,
62,
12564,
5777,
10426,
737,
12894,
395,
3419,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
45243,
20,
7,
39,
11211,
62,
34219,
62,
47,
31688,
10426,
1343,
31051,
6,
1343,
31051,
4458,
22179,
7,
6978,
82,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1343,
367,
11211,
62,
34219,
62,
12564,
5777,
10426,
737,
33095,
12894,
395,
3419,
628,
198,
4299,
3487,
1096,
62,
16514,
27823,
7,
16514,
27823,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
18980,
257,
41033,
357,
8841,
393,
35575,
8,
656,
257,
25713,
198,
220,
220,
220,
2124,
24223,
87,
13,
12343,
87,
357,
940,
13,
20,
8,
5794,
13,
628,
220,
220,
220,
5740,
326,
4628,
395,
9430,
1262,
3815,
3744,
621,
393,
4961,
284,
3389,
1160,
400,
11,
198,
220,
220,
220,
362,
27033,
379,
1596,
25,
3510,
18119,
481,
779,
1367,
19561,
284,
2380,
262,
1271,
286,
198,
220,
220,
220,
4201,
13,
628,
220,
220,
220,
1058,
17143,
41033,
25,
555,
844,
41033,
198,
220,
220,
220,
1058,
7783,
82,
25,
39279,
41033,
355,
257,
4731,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
36521,
27037,
13,
2713,
69,
1,
4064,
357,
22468,
7,
16514,
27823,
4008,
628,
198,
4299,
26571,
62,
25202,
62,
3911,
653,
7,
25202,
11,
18398,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3254,
20540,
326,
257,
3335,
290,
257,
18398,
389,
4938,
290,
1839,
470,
1085,
284,
198,
220,
220,
220,
8619,
33038,
282,
618,
973,
13,
628,
220,
220,
220,
1058,
17143,
3335,
25,
3335,
284,
26571,
198,
220,
220,
220,
1058,
17143,
18398,
25,
18398,
284,
26571,
198,
220,
220,
220,
1058,
430,
2696,
25,
11052,
12331,
611,
1813,
281,
12515,
3335,
393,
18398,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
12515,
62,
25202,
796,
10352,
198,
220,
220,
220,
12515,
62,
3911,
653,
796,
10352,
198,
220,
220,
220,
611,
407,
3335,
393,
31051,
6,
287,
3335,
393,
3335,
287,
37250,
2637,
11,
705,
492,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
12515,
62,
25202,
796,
6407,
198,
220,
220,
220,
611,
407,
18398,
393,
31051,
6,
287,
18398,
393,
18398,
287,
37250,
2637,
11,
705,
492,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
12515,
62,
3911,
653,
796,
6407,
628,
220,
220,
220,
611,
12515,
62,
25202,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
10786,
44651,
3335,
25,
4064,
82,
6,
4064,
9577,
7,
25202,
393,
10148,
4008,
198,
220,
220,
220,
1288,
361,
12515,
62,
3911,
653,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
10786,
44651,
18398,
25,
4064,
82,
6,
4064,
9577,
7,
3911,
653,
393,
10148,
4008,
628,
198,
4299,
6143,
62,
34945,
7,
19608,
324,
343,
11,
18398,
11,
1438,
62,
17831,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3497,
262,
6143,
8619,
628,
220,
220,
220,
1058,
17143,
4818,
324,
343,
25,
7308,
1366,
8619,
198,
220,
220,
220,
1058,
17143,
18398,
25,
2142,
653,
198,
220,
220,
220,
1058,
17143,
1438,
62,
17831,
25,
10781,
11,
9290,
393,
2134,
1438,
12234,
198,
220,
220,
220,
1058,
7783,
82,
25,
20514,
8619,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
28686,
13,
6978,
13,
22179,
7,
19608,
324,
343,
11,
965,
7,
3911,
653,
828,
1438,
62,
17831,
58,
12,
18,
25,
4357,
1438,
62,
17831,
8,
628
] | 2.821937 | 1,404 |
# uncompyle6 version 2.11.3
# Python bytecode 2.7 (62211)
# Decompiled from: Python 2.7.10 (default, May 23 2015, 09:40:32) [MSC v.1500 32 bit (Intel)]
# Embedded file name: scripts/common/dossiers2/custom/cache.py
import nations
from items import vehicles
_g_cache = {} | [
2,
34318,
2349,
21,
2196,
362,
13,
1157,
13,
18,
198,
2,
11361,
18022,
8189,
362,
13,
22,
357,
21,
1828,
1157,
8,
198,
2,
4280,
3361,
3902,
422,
25,
11361,
362,
13,
22,
13,
940,
357,
12286,
11,
1737,
2242,
1853,
11,
7769,
25,
1821,
25,
2624,
8,
685,
5653,
34,
410,
13,
33698,
3933,
1643,
357,
24123,
15437,
198,
2,
13302,
47238,
2393,
1438,
25,
14750,
14,
11321,
14,
67,
793,
3183,
17,
14,
23144,
14,
23870,
13,
9078,
198,
11748,
7027,
198,
6738,
3709,
1330,
5672,
628,
198,
198,
62,
70,
62,
23870,
796,
23884
] | 2.785714 | 98 |
#!/usr/bin/python
from code import TreeNode
from code import ThreeAddressCode
from lexer import tokens
from random import *
from symbol_table import SymbolTable
from symbol_table import SymbolTableNode
import logging
import ply.lex as lex
import ply.yacc as yacc
import sys
from codegen import convert_tac
from code import Code
from codegen import generate_assembly
three_addr_code = ThreeAddressCode()
assembly_code = Code()
parsed = []
symbol_table = SymbolTable()
var_list = []
generated = {'temp': [], 'scope': ['scope_0'], 'label': [], 'str_list': []}
precedence = (
('left','IDENTIFIER'),
('right','ASSIGN_OP'),
('left','COMMA'),
('left','LSQUARE'),
('left','RSQUARE'),
('left','LCURLY'),
('left','RCURLY'),
('left','DDD'),
('left','DOT'),
('left','SEMICOLON'),
('left','COLON'),
('left','SINGLE_QUOTES'),
('left','DOUBLE_QUOTES'),
('left','DECIMAL_LIT'),
('left','OCTAL_LIT'),
('left','HEX_LIT'),
('left','FLOAT_LIT'),
('left','STRING_LIT'),
('left','NEWLINE'),
('left','BREAK'),
('left','CONTINUE'),
('left','RETURN'),
('left','RROUND'),
('left','LROUND'),
('left', 'OR_OR'),
('left', 'AMP_AMP'),
('left', 'EQ_EQ', 'NOT_EQ','LT','LT_EQ','GT','GT_EQ'),
('left', 'PLUS', 'MINUS','OR','CARET'),
('left', 'STAR', 'DIVIDE','MODULO','AMP','AND_OR','LS','RS'),
)
def p_SourceFile(p):
'''SourceFile : PACKAGE IDENTIFIER SEMICOLON ImportDeclList TopLevelDeclList
'''
parsed.append(p.slice)
# TODO: Ignoring package name and Imports for now
p[0] = p[5]
var_list = symbol_table.make_var_list()
three_addr_code = convert_tac(p[0].TAC)
symbol_table.fill_next_use(three_addr_code)
assembly_code = generate_assembly(three_addr_code,var_list,symbol_table)
# p[0].TAC.print_code()
# three_addr_code.print_code()
assembly_code.print_code()
# symbol_table.print_symbol_table()
return
def p_ImportDeclList(p):
'''ImportDeclList : ImportDecl SEMICOLON ImportDeclList
| empty
'''
parsed.append(p.slice)
# TODO: Ignoring Imports for now
return
def p_TopLevelDeclList(p):
'''TopLevelDeclList : TopLevelDecl SEMICOLON TopLevelDeclList
| empty
'''
parsed.append(p.slice)
if len(p) == 4:
if p[3] != None:
p[0] = TreeNode('TopLevelDeclList', 0, 'INT', 0, [p[1]] + p[3].children, p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
else:
p[0] = TreeNode('TopLevelDeclList', 0, 'INT', 0, [p[1]], p[1].TAC)
return
def p_TopLevelDecl(p):
'''TopLevelDecl : Declaration
| FunctionDecl
'''
parsed.append(p.slice)
p[0] = p[1]
return
def p_ImportDecl(p):
'''ImportDecl : IMPORT LROUND ImportSpecList RROUND
| IMPORT ImportSpec
'''
parsed.append(p.slice)
# TODO: Ignoring Imports for now
return
def p_ImportSpecList(p):
'''ImportSpecList : ImportSpec SEMICOLON ImportSpecList
| empty
'''
parsed.append(p.slice)
# TODO: Ignoring Imports for now
return
def p_ImportSpec(p):
'''ImportSpec : DOT string_lit
| IDENTIFIER string_lit
| empty string_lit
'''
parsed.append(p.slice)
# TODO: Ignoring Imports for now
return
def p_Block(p):
'''Block : LCURLY ScopeStart StatementList ScopeEnd RCURLY
'''
parsed.append(p.slice)
p[0] = p[3]
p[0].data = p[2].data
p[0].name = 'Block'
return
def p_ScopeStart(p):
'''ScopeStart : empty
'''
parsed.append(p.slice)
symbol_table.add_scope(gen('scope'))
p[0] = TreeNode('ScopeStart', symbol_table.current_scope, 'None')
return
def p_ScopeEnd(p):
'''ScopeEnd : empty
'''
parsed.append(p.slice)
symbol_table.end_scope()
return
def p_StatementList(p):
'''StatementList : Statement SEMICOLON StatementList
| empty
'''
parsed.append(p.slice)
if len(p) == 4:
p[0] = TreeNode('StatementList', 0, 'INT', 0, [p[1].data] + p[3].children, p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
else:
p[0] = TreeNode('StatementList', 0, 'INT')
return
def p_Statement(p):
'''Statement : Declaration
| SimpleStmt
| ReturnStmt
| Block
| IfStmt
| SwitchStmt
| ForStmt
| BreakStmt
| ContinueStmt
| GotoStmt
| PrintIntStmt
| PrintStrStmt
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'Statement'
return
def p_PrintIntStmt(p):
'''PrintIntStmt : PRINTLN LROUND IDENTIFIER RROUND
| PRINTLN LROUND int_lit RROUND
'''
if hasattr(p[3], 'name') and p[3].name == 'int_lit':
p[0] = p[3]
# p[0].isLvalue = 0
else:
p[0] = TreeNode('IDENTIFIER', p[3], 'INT', 1, [])
p[0].TAC.add_line(['print_int', check_variable(p[0]), '', ''])
p[0].name = 'PrintIntStmt'
return
def p_PrintStrStmt(p):
'''PrintStrStmt : PRINTLN LROUND string_lit RROUND
'''
p[0] = p[3]
name = symbol_table.current_scope + '_' + gen('str_list')
parametersNode = SymbolTableNode(p[3].data, p[3].input_type)
newNode = SymbolTableNode(name, p[3].input_type, parameters = [parametersNode])
symbol_table.add_var(newNode)
p[0].TAC.add_line(['print_str', name, '', ''])
p[0].name = 'PrintStrStmt'
return
def p_Declaration(p):
'''Declaration : ConstDecl
| TypeDecl
| VarDecl
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'Declaration'
return
def p_ConstDecl(p):
'''ConstDecl : CONST LROUND ConstSpecList RROUND
| CONST ConstSpec
'''
parsed.append(p.slice)
return
def p_ConstSpecList(p):
'''ConstSpecList : empty
| ConstSpecList ConstSpec SEMICOLON
'''
parsed.append(p.slice)
return
def p_ConstSpec(p):
'''ConstSpec : IDENTIFIER
| IdentifierList
| IDENTIFIER EQ Expression
| IdentifierList EQ ExpressionList
| IDENTIFIER Type EQ Expression
| IdentifierList Type EQ ExpressionList
'''
parsed.append(p.slice)
return
def p_IdentifierList(p):
'''IdentifierList : IDENTIFIER COMMA IdentifierBotList
'''
parsed.append(p.slice)
node = TreeNode('IDENTIFIER', p[1], 'INT', 1)
p[0] = TreeNode('IdentifierList', 0, 'None', 0, [node] + p[3].children, p[3].TAC)
return
def p_IdentifierBotList(p):
'''IdentifierBotList : IDENTIFIER COMMA IdentifierBotList
| IDENTIFIER
'''
parsed.append(p.slice)
if len(p) == 2:
node = TreeNode('IDENTIFIER', p[1], 'INT', 1)
p[0] = TreeNode('IdentifierBotList', 0, 'None', 0, [node])
elif len(p) == 4:
node = TreeNode('IDENTIFIER', p[1], 'INT', 1)
p[0] = TreeNode('IdentifierBotList', 0, 'None', 0, [node] + p[3].children, p[3].TAC)
return
def p_ExpressionList(p):
'''ExpressionList : Expression COMMA ExpressionBotList
'''
parsed.append(p.slice)
p[0] = TreeNode('ExpressionList', 0, 'INT', 0, [p[1]] + p[3].children, p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
return
def p_ExpressionBotList(p):
'''ExpressionBotList : Expression COMMA ExpressionBotList
| Expression
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = TreeNode('ExpressionBotList', 0, 'INT', 0, [p[1]], p[1].TAC)
elif len(p) == 4:
p[0] = TreeNode('ExpressionBotList', 0, 'INT', 0, [p[1]] + p[3].children, p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
return
def p_TypeDecl(p):
'''TypeDecl : TYPE TypeSpecTopList
'''
parsed.append(p.slice)
return
def p_TypeSpecTopList(p):
'''TypeSpecTopList : TypeSpec
| LROUND TypeSpecList RROUND
'''
parsed.append(p.slice)
return
def p_TypeSpecList(p):
'''TypeSpecList : empty
| TypeSpecList TypeSpec SEMICOLON
'''
parsed.append(p.slice)
return
def p_TypeSpec(p):
'''TypeSpec : AliasDecl
| TypeDef
'''
parsed.append(p.slice)
return
def p_AliasDecl(p):
'''AliasDecl : IDENTIFIER EQ Type
'''
parsed.append(p.slice)
return
def p_TypeDef(p):
'''TypeDef : IDENTIFIER Type
'''
parsed.append(p.slice)
return
def p_Type(p):
'''Type : TypeLit
| StandardTypes
| LROUND Type RROUND
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
else:
p[0] = p[2]
p[0].name = 'Type'
return
def p_StandardTypes(p):
'''StandardTypes : PREDEFINED_TYPES
'''
parsed.append(p.slice)
p[0] = TreeNode('StandardTypes', p[1], 'NONE')
return
def p_TypeLit(p):
'''TypeLit : ArrayType
| StructType
| FunctionType
| PointerType
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'TypeLit'
return
def p_PointerType(p):
'''PointerType : STAR Type
'''
parsed.append(p.slice)
return
def p_ArrayType(p):
'''ArrayType : LSQUARE ArrayLength RSQUARE Type
'''
parsed.append(p.slice)
p[0] = TreeNode('ArrayType', p[2].data, p[4].data)
return
def p_ArrayLength(p):
'''ArrayLength : Expression
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'ArrayLength'
return
def p_StructType(p):
'''StructType : STRUCT LCURLY FieldDeclList RCURLY
'''
parsed.append(p.slice)
return
def p_FieldDeclList(p):
'''FieldDeclList : empty
| FieldDeclList FieldDecl SEMICOLON
'''
parsed.append(p.slice)
return
def p_FieldDecl(p):
'''FieldDecl : IdentifierList Type TagTop
| IDENTIFIER Type TagTop
'''
parsed.append(p.slice)
return
def p_TagTop(p):
'''TagTop : empty
| Tag
'''
parsed.append(p.slice)
return
def p_Tag(p):
'''Tag : string_lit
'''
parsed.append(p.slice)
return
def p_FunctionType(p):
'''FunctionType : FUNC Signature
'''
parsed.append(p.slice)
return
def p_Signature(p):
'''Signature : Parameters
| Parameters Result
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'Signature'
s = 'scope_' + str(len(generated['scope']))
symbol_table.new_scope(s)
for child in p[1].children:
symbol_table.add_identifier(child, s)
newNode = SymbolTableNode(s + '_' + child.data, child.input_type)
symbol_table.add_var(newNode, s)
# symbol_table.print_symbol_table()
if len(p) == 2:
p[0].input_type = TreeNode('Result', 0, 'None')
else:
p[0].input_type = p[2]
return
def p_Result(p):
'''Result : Parameters
| Type
'''
parsed.append(p.slice)
if p[1].name == 'Type':
p[0] = TreeNode('Result', 1, 'None', 0, [p[1]])
else:
p[0] = p[1]
p[0].name = 'Result'
return
def p_Parameters(p):
'''Parameters : LROUND RROUND
| LROUND ParameterList RROUND
'''
parsed.append(p.slice)
if len(p) == 3:
p[0] = TreeNode('Parameters', 0, 'None')
else:
p[0] = p[2]
p[0].name = 'Parameters'
return
def p_ParameterList(p):
'''ParameterList : ParameterDecl
| ParameterList COMMA ParameterDecl
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
p[0].name = 'ParameterList'
elif len(p) == 4:
p[0] = TreeNode('ParameterList', p[1].data + p[3].data, 'None', 0, p[1].children + p[3].children, p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
return
def p_ParameterDecl(p):
'''ParameterDecl : IdentifierList Type
| IDENTIFIER Type
| Type
'''
parsed.append(p.slice)
p[0] = TreeNode('ParameterDecl', 0, 'None')
if len(p) == 3:
if hasattr(p[1], 'name') and p[1].name == 'IdentifierList':
for node in p[1].children:
p[0].data += 1
node.input_type = p[2].data
p[0].children += [node]
else:
node = TreeNode('IDENTIFIER', p[1], p[2].data, 1)
p[0].data += 1
p[0].children += [node]
else:
p[0].data += 1
p[0].children += [p[1]]
return
def p_VarDecl(p):
'''VarDecl : VAR VarSpecTopList
'''
parsed.append(p.slice)
p[0] = p[2]
p[0].name = 'VarDecl'
return
def p_VarSpecTopList(p):
'''VarSpecTopList : VarSpec
| LROUND VarSpecList RROUND
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
else:
p[0] = p[2]
p[0].name = 'VarSpecTopList'
return
def p_VarSpecList(p):
'''VarSpecList : empty
| VarSpecList VarSpec SEMICOLON
'''
return
def p_VarSpec(p):
'''VarSpec : IDENTIFIER Type
| IDENTIFIER EQ Expression
| IDENTIFIER Type EQ Expression
| IdentifierList Type
| IdentifierList EQ ExpressionList
| IdentifierList Type EQ ExpressionList
'''
# Insert into symbol table
p[0] = TreeNode('VarSpec', 0, 'NONE')
if hasattr(p[1], 'name') and p[1].name == 'IdentifierList':
zero_val = TreeNode('decimal_lit', 0, 'INT')
# l1 = len(p[1].children)
# if len(p) == 3:
# expr_list = TreeNode('Expr_List', 0, 'NONE', 0, [zero_val] * l1)
# elif len(p) == 4:
# expr_list = p[3]
# elif len(p) == 5:
# expr_list = p[4]
# l2 = len(expr_list.children)
# p[0].TAC.append_TAC(expr_list.TAC)
# p[0].TAC.append_TAC(p[1].TAC)
# if l1 == l2:
# for i in range(l1):
# p[0].TAC.add_line(['=', p[1].children[i], expr_list.children[i].data, ''])
# else:
# print_error("Variable Declaration mismatch: " + str(l1) + " identifier(s) but " + str(l2) + " value(s)")
else:
p[1] = TreeNode('IDENTIFIER',p[1],'INT',1)
if p[2].input_type != 'NONE':
# array case
# p[2].print_node()
if symbol_table.add_identifier(p[1], size = p[2].data) == False:
print_error("Unable to add to SymbolTable")
return
name = symbol_table.search_identifier(p[1].data)
newNode = SymbolTableNode(name, p[1].input_type,size = p[2].data)
symbol_table.add_var(newNode)
p[0] = TreeNode('VarSpec',p[1].data,'INT')
# expr = TreeNode('Expr', 0, 'NONE')
# if len(p) == 4:
# expr = p[3]
# p[0].TAC.append_TAC(p[3].TAC)
# p[0].TAC.add_line(['=', check_variable(p[1]), check_variable(expr), ''])
# elif len(p) == 5:
# expr = p[4]
# p[0].TAC.append_TAC(p[4].TAC)
# p[0].TAC.add_line(['=', check_variable(p[1]), check_variable(expr), ''])
return
def p_FunctionDecl(p):
'''FunctionDecl : FUNC FunctionName Signature
| FUNC FunctionName Signature FunctionBody
'''
parsed.append(p.slice)
# symbol_table.print_symbol_table()
p[0] = TreeNode('FunctionDecl', 0, 'INT')
# print symbol_table.current_scope
# p[4].TAC.print_code()
symbol_table.add_function(p[2].data, p[3].input_type, p[3].children)
if len(p) == 5:
noOfParams = 0
for f in symbol_table.symbol_table[symbol_table.current_scope]['functions']:
if f.name == p[2].data:
noOfParams = len(f.parameters)
p[0].TAC.add_line(['func', check_variable(p[2]), str(noOfParams), ''])
for child in reversed(p[3].children):
p[0].TAC.add_line(['getparam', p[4].data + '_' + child.data, '', ''])
p[0].TAC.add_line(['stack_push', '', '', ''])
p[0].TAC.append_TAC(p[4].TAC)
return
def p_FunctionName(p):
'''FunctionName : IDENTIFIER
'''
parsed.append(p.slice)
p[0] = TreeNode('FunctionName', p[1], 'INT', 1)
return
def p_FunctionBody(p):
'''FunctionBody : Block
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'FunctionBody'
return
def p_SimpleStmt(p):
'''SimpleStmt : Expression
| Assignment
| ShortVarDecl
| IncDecStmt
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'SimpleStmt'
return
def p_IncDecStmt(p):
'''IncDecStmt : Expression PLUS_PLUS
| Expression MINUS_MINUS
'''
parsed.append(p.slice)
one_val = TreeNode('IncDecStmt', '1', 'INT')
p[0] = p[1]
if p[1].isLvalue == 1:
if p[2] == '++':
p[0].TAC.add_line(['+', check_variable(p[1]), check_variable(p[1]), one_val.data])
else:
p[0].TAC.add_line(['-', check_variable(p[1]), check_variable(p[1]), one_val.data])
else:
print_error("Lvalue required")
p[0].name = 'IncDecStmt'
return
def p_ShortVarDecl(p):
'''ShortVarDecl : ExpressionList ASSIGN_OP ExpressionList
| Expression ASSIGN_OP Expression
'''
parsed.append(p.slice)
# TODO: Add in symbol table
p[0] = TreeNode('ShortVarDecl', 0, 'INT')
if p[1].name == 'ExpressionList':
l1 = len(p[1].children)
l2 = len(p[3].children)
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.append_TAC(p[1].TAC)
if l1 == l2:
for i in range(l1):
if p[1].children[i].isLvalue == 0:
print_error("Lvalue required")
return
else:
if symbol_table.add_identifier(p[1].children[i]) == False:
print_error("Unable to add to SymbolTable")
return
p[0].TAC.add_line([p[2], check_variable(p[1].children[i]), check_variable(p[3].children[i]), ''])
else:
print_error("Variable Declaration mismatch: " + str(l1) + " identifier(s) but " + str(l2) + " value(s)")
elif p[1].name == 'Expression':
if p[1].isLvalue == 0:
print_error("Lvalue required")
return
else:
if symbol_table.add_identifier(p[1]) == False:
print_error("Unable to add to SymbolTable")
return
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.append_TAC(p[1].TAC)
p[0].TAC.add_line([p[2], check_variable(p[1]), check_variable(p[3]), ''])
return
def p_Assignment(p):
'''Assignment : ExpressionList assign_op ExpressionList
| Expression assign_op Expression
'''
parsed.append(p.slice)
p[0] = TreeNode('Assignment', 0, 'INT')
if p[1].name == 'ExpressionList':
l1 = len(p[1].children)
l2 = len(p[3].children)
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.append_TAC(p[1].TAC)
if l1 == l2:
for i in range(l1):
if p[1].children[i].isLvalue == 0:
print_error("Lvalue required")
return
else:
if symbol_table.search_identifier(p[1].children[i].data) == False and p[1].children[i].data not in generated['temp']:
print_error("Variable " + p[1].children[i].data + " is undefined")
return
if p[3].children[i].isLvalue == 1 and symbol_table.search_identifier(p[3].children[i].data) == False and p[3].children[i].data not in generated['temp']:
print_error("Variable " + p[3].children[i].data + " is undefined")
return
p[0].TAC.add_line([p[2].data, check_variable(p[1].children[i]), check_variable(p[3].children[i]), ''])
else:
print_error("Variable Declaration mismatch: " + str(l1) + " identifier(s) but " + str(l2) + " value(s)")
elif p[1].name == 'Expression':
if p[1].isLvalue == 0:
print_error("Lvalue required")
return
else:
if symbol_table.search_identifier(p[1].data) == False and p[1].data not in generated['temp']:
print_error("Variable " + p[1].data + " is undefined")
return
if p[3].isLvalue == 1 and symbol_table.search_identifier(p[3].data) == False and p[3].data not in generated['temp']:
print_error("Variable " + p[3].data + " is undefined")
return
# print symbol_table.current_scope
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.append_TAC(p[1].TAC)
p[0].TAC.add_line([p[2].data, check_variable(p[1]), check_variable(p[3]), ''])
return
def p_assign_op(p):
'''assign_op : EQ
| PLUS_EQ
| MINUS_EQ
| OR_EQ
| CARET_EQ
| STAR_EQ
| DIVIDE_EQ
| MODULO_EQ
| LS_EQ
| RS_EQ
| AMP_EQ
| AND_OR_EQ
'''
parsed.append(p.slice)
p[0] = TreeNode('assign_op', p[1], 'OPERATOR')
return
def p_IfStmt(p):
'''IfStmt : IF Expression Block
| IF Expression Block ELSE elseTail
'''
parsed.append(p.slice)
if len(p) == 4:
l1 = gen('label')
p[0] = TreeNode('IfStmt', 0, 'INT')
p[0].TAC.append_TAC(p[2].TAC)
p[0].TAC.add_line(['ifgotoeq', check_variable(p[2]), '0', l1])
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.add_line(['label', l1, '', ''])
if len(p) == 6:
l1 = gen('label')
l2 = gen('label')
p[0] = TreeNode('IfStmt', 0, 'INT')
p[0].TAC.append_TAC(p[2].TAC)
p[0].TAC.add_line(['ifgotoeq', check_variable(p[2]), '0', l1])
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.add_line(['goto', l2, '', ''])
p[0].TAC.add_line(['label', l1, '', ''])
p[0].TAC.append_TAC(p[5].TAC)
p[0].TAC.add_line(['label', l2, '', ''])
return
def p_elseTail(p):
'''elseTail : IfStmt
| Block
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'elseTail'
return
def p_SwitchStmt(p):
'''SwitchStmt : ExprSwitchStmt
'''
parsed.append(p.slice)
p[0] = TreeNode('SwitchStmt', 0, 'INT', 0, [], p[1].TAC)
return
def p_ExprSwitchStmt(p):
'''ExprSwitchStmt : SWITCH SimpleStmt SEMICOLON LCURLY ScopeStart ExprCaseClauseList ScopeEnd RCURLY
| SWITCH SimpleStmt SEMICOLON Expression LCURLY ScopeStart ExprCaseClauseList ScopeEnd RCURLY
| SWITCH LCURLY ScopeStart ExprCaseClauseList ScopeEnd RCURLY
| SWITCH Expression LCURLY ScopeStart ExprCaseClauseList ScopeEnd RCURLY
'''
parsed.append(p.slice)
if len(p) == 8:
l1 = gen('label')
l2 = gen('label')
p[0] = TreeNode('ExprSwitchStmt', 0, 'INT')
p[0].TAC.append_TAC(p[2].TAC)
t1 = TreeNode('IDENTIFIER', gen('temp'), 'INT', 1)
p[0].TAC.add_line(['=', check_variable(t1) , check_variable(p[2]), ''])
p[0].TAC.append_TAC(p[5].data)
for i in range(len(p[5].children)):
p[0].TAC.add_line(['ifgotoeq', check_variable(t1), p[5].children[i][0], p[5].children[i][1]])
p[0].TAC.add_line(['goto', l2, '', ''])
for i in range(p[5].TAC.length()):
if i in p[5].TAC.leaders[1:]:
p[0].TAC.add_line(['goto', l2, '', ''])
p[0].TAC.add_line(p[5].TAC.code[i])
p[0].TAC.add_line(['label', l2, '', ''])
return
def p_ExprCaseClauseList(p):
'''ExprCaseClauseList : empty
| ExprCaseClauseList ExprCaseClause
'''
parsed.append(p.slice)
TAC1 = ThreeAddressCode()
TAC2 = ThreeAddressCode()
if len(p) == 3:
TAC1 = p[1].data
TAC2 = p[2].data
p[0] = TreeNode('ExprCaseClauseList', TAC1, 'INT', 0, p[1].children + p[2].children, p[1].TAC)
p[0].TAC.add_leader(p[0].TAC.length())
p[0].TAC.append_TAC(p[2].TAC)
p[0].data.append_TAC(TAC2)
else:
p[0] = TreeNode('ExprCaseClauseList', TAC1, 'INT')
return
def p_ExprCaseClause(p):
'''ExprCaseClause : ExprSwitchCase COLON StatementList
'''
parsed.append(p.slice)
l1 = gen('label')
p[0] = TreeNode('ExprCaseClause', 0, 'INT')
# p[0].TAC.append_TAC(p[1].TAC)
p[0].TAC.add_line(['label', l1, '', ''])
# p[0].TAC.add_line(['ifgotoneq', p[1].children, p[1].children, l1])
p[0].TAC.append_TAC(p[3].TAC)
p[0].children = [[p[1].data,l1]]
p[0].data = p[1].TAC
return
def p_ExprSwitchCase(p):
'''ExprSwitchCase : CASE ExpressionList
| DEFAULT
| CASE Expression
'''
parsed.append(p.slice)
p[0] = TreeNode('ExprSwitchCase', 0, 'INT')
if len(p) == 3:
p[0].data = p[2].data
p[0].TAC = p[2].TAC
return
def p_ForStmt(p):
'''ForStmt : FOR Expression Block
| FOR Block
'''
parsed.append(p.slice)
p[0] = TreeNode('ForStmt', 0, 'INT')
if len(p) == 4:
l1 = gen('label')
l2 = gen('label')
p[0].TAC.add_line(['label', l1, '', ''])
p[0].TAC.append_TAC(p[2].TAC)
p[0].TAC.add_line(['ifgotoeq',check_variable(p[2]), '0', l2])
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.add_line(['goto', l1, '', ''])
p[0].TAC.add_line(['label', l2, '', ''])
if len(p) == 3:
l1 = gen('label')
# l2 = gen('label')
p[0].TAC.add_line(['label', l1, '', ''])
p[0].TAC.append_TAC(p[2].TAC)
p[0].TAC.add_line(['goto', l1, '', ''])
# p[0].TAC.add_line([l2])
return
def p_ReturnStmt(p):
'''ReturnStmt : RETURN
| RETURN Expression
| RETURN ExpressionList
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = TreeNode('ReturnStmt', 0, 'None')
p[0].TAC.add_line(['return', '', '', ''])
if len(p) == 3:
if p[2].name == 'Expression':
p[0] = p[2]
p[0].name = 'ReturnStmt'
p[0].TAC.add_line(['return', check_variable(p[2]), '', ''])
return
def p_BreakStmt(p):
'''BreakStmt : BREAK IDENTIFIER
'''
parsed.append(p.slice)
return
def p_ContinueStmt(p):
'''ContinueStmt : CONTINUE IDENTIFIER
'''
parsed.append(p.slice)
return
def p_GotoStmt(p):
'''GotoStmt : GOTO IDENTIFIER
'''
parsed.append(p.slice)
return
def p_Expression(p):
'''Expression : UnaryExpr
| Expression OR_OR Expression
| Expression AMP_AMP Expression
| Expression EQ_EQ Expression
| Expression NOT_EQ Expression
| Expression LT Expression
| Expression LT_EQ Expression
| Expression GT Expression
| Expression GT_EQ Expression
| Expression PLUS Expression
| Expression MINUS Expression
| Expression OR Expression
| Expression CARET Expression
| Expression STAR Expression
| Expression DIVIDE Expression
| Expression MODULO Expression
| Expression LS Expression
| Expression RS Expression
| Expression AMP Expression
| Expression AND_OR Expression
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
elif len(p) == 4:
p[0] = TreeNode('IDENTIFIER', gen('temp'), 'INT', 1, [], p[1].TAC)
p[0].TAC.append_TAC(p[3].TAC)
p[0].TAC.add_line([p[2],check_variable(p[0]), check_variable(p[1]), check_variable(p[3])])
p[0].name = 'Expression'
return
def p_UnaryExpr(p):
'''UnaryExpr : PrimaryExpr
| unary_op UnaryExpr
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
elif len(p) == 3:
p[0] = TreeNode('IDENTIFIER', gen('temp'), 'INT', 1)
p[0].TAC.add_line([check_variable(p[1]), check_variable(p[0]), check_variable(p[2]), ''])
p[0].name = 'UnaryExpr'
return
def p_unary_op(p):
'''unary_op : PLUS
| MINUS
| NOT
| CARET
| STAR
| AMP
| LT_MINUS
'''
parsed.append(p.slice)
p[0] = TreeNode('unary_op', p[1], 'OPERATOR')
return
def p_PrimaryExpr(p):
'''PrimaryExpr : Operand
| IDENTIFIER
| PrimaryExpr Selector
| PrimaryExpr Index
| PrimaryExpr Arguments
'''
parsed.append(p.slice)
if len(p) == 2:
if p.slice[1].type == 'IDENTIFIER':
p[0] = TreeNode('IDENTIFIER', p[1], 'INT', 1)
elif p[1].name == 'Operand':
p[0] = p[1]
elif len(p) == 3:
if p[2].name == 'Index':
p[0] = TreeNode('IDENTIFIER', p[1].data, 'INT', 1, p[2].data)
elif p[2].name == 'Arguments':
p[0] = TreeNode('IDENTIFIER', gen('temp'), 'INT', 1)
p[0].TAC.append_TAC(p[1].TAC)
p[0].TAC.append_TAC(p[2].TAC)
# p[1].print_node()
func = check_variable(p[1]).split("_")
scope, funcName = "_".join(func[:2]), "_".join(func[2:])
temp = 0
for f in symbol_table.symbol_table[scope]['functions']:
if f.name == funcName:
temp = len(f.parameters)
# p[2].print_node()
for child in p[2].children:
p[0].TAC.add_line(['putparam', check_variable(child), '', ''])
if temp != p[2].data:
print_error('Function ' + funcName + ' requires ' + str(temp) + ' parameters but ' + str(p[2].data) + ' supplied')
p[0].TAC.add_line(['call', check_variable(p[1]), str(p[2].data), ''])
p[0].TAC.add_line(['return_value', check_variable(p[0]), '', ''])
p[0].name = 'PrimaryExpr'
return
def p_Operand(p):
'''Operand : Literal
| LROUND Expression RROUND
'''
parsed.append(p.slice)
if len(p) == 2:
p[0] = p[1]
else:
p[0] = p[2]
p[0].name = 'Operand'
return
def p_Literal(p):
'''Literal : BasicLit
| FunctionLit
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'Literal'
return
def p_BasicLit(p):
'''BasicLit : int_lit
| float_lit
| string_lit
| rune_lit
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'BasicLit'
return
def p_int_lit(p):
'''int_lit : decimal_lit
| octal_lit
| hex_lit
'''
parsed.append(p.slice)
p[0] = p[1]
p[0].name = 'int_lit'
return
def p_decimal_lit(p):
'''decimal_lit : DECIMAL_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('decimal_lit', p[1], 'INT')
return
def p_octal_lit(p):
'''octal_lit : OCTAL_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('octal_lit', p[1], 'OCT')
return
def p_hex_lit(p):
'''hex_lit : HEX_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('hex_lit', p[1], 'HEX')
return
def p_float_lit(p):
'''float_lit : FLOAT_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('float_lit', p[1], 'FLOAT')
return
def p_FunctionLit(p):
'''FunctionLit : FUNC Signature FunctionBody
'''
parsed.append(p.slice)
# Anonymous Function
# Not implemented yet
return
def p_Selector(p):
'''Selector : DOT IDENTIFIER
'''
parsed.append(p.slice)
return
def p_Index(p):
'''Index : LSQUARE Expression RSQUARE
'''
parsed.append(p.slice)
p[0] = p[2]
p[0].name = 'Index'
return
def p_Arguments(p):
'''Arguments : LROUND RROUND
| LROUND ExpressionList RROUND
| LROUND Expression RROUND
| LROUND Type RROUND
| LROUND Type COMMA ExpressionList RROUND
| LROUND Type COMMA Expression RROUND
'''
# print p.slice
parsed.append(p.slice)
if len(p) == 3:
p[0] = TreeNode('Arguments', 0, 'None')
if len(p) == 4:
if p[2].name == 'Expression':
p[0] = TreeNode('Arguments', 1, 'None', 0, [p[2]], p[2].TAC)
if p[2].name == 'ExpressionList':
p[0] = p[2]
p[0].name = 'Arguments'
p[0].data = len(p[2].children)
return
def p_string_lit(p):
'''string_lit : STRING_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('string_lit', p[1], 'STRING')
return
def p_rune_lit(p):
'''rune_lit : RUNE_LIT
'''
parsed.append(p.slice)
p[0] = TreeNode('rune_lit', p[1], 'RUNE')
return
def p_empty(p):
'empty :'
pass
# Standard Logger
logging.basicConfig(
level = logging.DEBUG,
filename = "parselog.txt",
filemode = "w",
format = "%(filename)10s:%(lineno)4d:%(message)s"
)
log = logging.getLogger()
yacc.yacc(debug=True, debuglog=log)
input_file = sys.argv[1]
import os
if os.path.isfile(input_file) is False:
print('Input file ' + input_file + ' does not exist')
sys.exit(1)
input_code = open(input_file, 'r').read()
if input_code[len(input_code)-1] != '\n':
input_code += '\n'
yacc.parse(input_code, debug=log, tracking=True)
| [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
198,
6738,
2438,
1330,
12200,
19667,
198,
6738,
2438,
1330,
7683,
20231,
10669,
198,
6738,
31191,
263,
1330,
16326,
198,
6738,
4738,
1330,
1635,
198,
6738,
6194,
62,
11487,
1330,
38357,
10962,
198,
6738,
6194,
62,
11487,
1330,
38357,
10962,
19667,
628,
198,
11748,
18931,
198,
11748,
35960,
13,
2588,
355,
31191,
198,
11748,
35960,
13,
88,
4134,
355,
331,
4134,
198,
11748,
25064,
628,
198,
6738,
2438,
5235,
1330,
10385,
62,
83,
330,
198,
6738,
2438,
1330,
6127,
198,
6738,
2438,
5235,
1330,
7716,
62,
41873,
198,
15542,
62,
29851,
62,
8189,
796,
7683,
20231,
10669,
3419,
198,
41873,
62,
8189,
796,
6127,
3419,
198,
198,
79,
945,
276,
796,
17635,
198,
1837,
23650,
62,
11487,
796,
38357,
10962,
3419,
198,
7785,
62,
4868,
796,
17635,
628,
198,
27568,
796,
1391,
6,
29510,
10354,
685,
4357,
705,
29982,
10354,
37250,
29982,
62,
15,
6,
4357,
705,
18242,
10354,
685,
4357,
705,
2536,
62,
4868,
10354,
17635,
92,
198,
198,
3866,
771,
594,
796,
357,
198,
220,
220,
220,
19203,
9464,
41707,
25256,
5064,
38311,
33809,
198,
220,
220,
220,
19203,
3506,
41707,
10705,
16284,
62,
3185,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
9858,
5673,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
6561,
10917,
12203,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
6998,
10917,
12203,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
5639,
4261,
11319,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
7397,
4261,
11319,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
16458,
35,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
35,
2394,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
50,
3620,
2149,
3535,
1340,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
25154,
1340,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
50,
2751,
2538,
62,
10917,
2394,
1546,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
35,
2606,
19146,
62,
10917,
2394,
1546,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
41374,
3955,
1847,
62,
43,
2043,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
46,
4177,
1847,
62,
43,
2043,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
39,
6369,
62,
43,
2043,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
3697,
46,
1404,
62,
43,
2043,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
18601,
2751,
62,
43,
2043,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
13965,
24027,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
40438,
10206,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
37815,
1268,
8924,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
26087,
27064,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
21095,
15919,
33809,
198,
220,
220,
220,
19203,
9464,
41707,
35972,
15919,
33809,
198,
220,
220,
220,
19203,
9464,
3256,
705,
1581,
62,
1581,
33809,
198,
220,
220,
220,
19203,
9464,
3256,
705,
23518,
62,
23518,
33809,
198,
220,
220,
220,
19203,
9464,
3256,
705,
36,
48,
62,
36,
48,
3256,
705,
11929,
62,
36,
48,
41707,
27734,
41707,
27734,
62,
36,
48,
41707,
19555,
41707,
19555,
62,
36,
48,
33809,
198,
220,
220,
220,
19203,
9464,
3256,
705,
6489,
2937,
3256,
705,
23678,
2937,
41707,
1581,
41707,
20034,
2767,
33809,
198,
220,
220,
220,
19203,
9464,
3256,
705,
46678,
3256,
705,
33569,
14114,
41707,
33365,
6239,
46,
41707,
23518,
41707,
6981,
62,
1581,
41707,
6561,
41707,
6998,
33809,
198,
8,
198,
198,
4299,
279,
62,
37226,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
37226,
1058,
47035,
11879,
4522,
3525,
5064,
38311,
48603,
2149,
3535,
1340,
17267,
37835,
8053,
5849,
4971,
37835,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
16583,
3255,
5301,
1438,
290,
1846,
3742,
329,
783,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
20,
60,
198,
220,
220,
220,
1401,
62,
4868,
796,
6194,
62,
11487,
13,
15883,
62,
7785,
62,
4868,
3419,
198,
220,
220,
220,
1115,
62,
29851,
62,
8189,
796,
10385,
62,
83,
330,
7,
79,
58,
15,
4083,
51,
2246,
8,
198,
220,
220,
220,
6194,
62,
11487,
13,
20797,
62,
19545,
62,
1904,
7,
15542,
62,
29851,
62,
8189,
8,
198,
220,
220,
220,
10474,
62,
8189,
796,
7716,
62,
41873,
7,
15542,
62,
29851,
62,
8189,
11,
7785,
62,
4868,
11,
1837,
23650,
62,
11487,
8,
198,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
4798,
62,
8189,
3419,
198,
220,
220,
220,
1303,
1115,
62,
29851,
62,
8189,
13,
4798,
62,
8189,
3419,
198,
220,
220,
220,
10474,
62,
8189,
13,
4798,
62,
8189,
3419,
198,
220,
220,
220,
1303,
6194,
62,
11487,
13,
4798,
62,
1837,
23650,
62,
11487,
3419,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
20939,
37835,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
20939,
37835,
8053,
1058,
17267,
37835,
48603,
2149,
3535,
1340,
17267,
37835,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
16583,
3255,
1846,
3742,
329,
783,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
9126,
4971,
37835,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
9126,
4971,
37835,
8053,
1058,
5849,
4971,
37835,
48603,
2149,
3535,
1340,
5849,
4971,
37835,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
18,
60,
14512,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
9126,
4971,
37835,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
11907,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
9126,
4971,
37835,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
60,
4357,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
9126,
4971,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
9126,
4971,
37835,
1058,
24720,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
15553,
37835,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
20939,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
20939,
37835,
1058,
30023,
9863,
37491,
15919,
17267,
22882,
8053,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
30023,
9863,
17267,
22882,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
16583,
3255,
1846,
3742,
329,
783,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
20939,
22882,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
20939,
22882,
8053,
1058,
17267,
22882,
48603,
2149,
3535,
1340,
17267,
22882,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
16583,
3255,
1846,
3742,
329,
783,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
20939,
22882,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
20939,
22882,
1058,
42743,
4731,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
4731,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6565,
4731,
62,
18250,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
16583,
3255,
1846,
3742,
329,
783,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
12235,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
12235,
1058,
22228,
4261,
11319,
41063,
10434,
21983,
8053,
41063,
12915,
13987,
4261,
11319,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
18,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
7890,
796,
279,
58,
17,
4083,
7890,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
12235,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
43642,
10434,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
43642,
10434,
1058,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
29982,
7,
5235,
10786,
29982,
6,
4008,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
43642,
10434,
3256,
6194,
62,
11487,
13,
14421,
62,
29982,
11,
705,
14202,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
43642,
12915,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
43642,
12915,
1058,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
6194,
62,
11487,
13,
437,
62,
29982,
3419,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
48682,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
48682,
8053,
1058,
21983,
48603,
2149,
3535,
1340,
21983,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6565,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
48682,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
4083,
7890,
60,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
48682,
8053,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
48682,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
48682,
1058,
24720,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
17427,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
8229,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
9726,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
1002,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
14645,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
1114,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12243,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
10054,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
402,
2069,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12578,
5317,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12578,
13290,
1273,
16762,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
48682,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
18557,
5317,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
18557,
5317,
1273,
16762,
1058,
4810,
12394,
43,
45,
37491,
15919,
4522,
3525,
5064,
38311,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4810,
12394,
43,
45,
37491,
15919,
493,
62,
18250,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
611,
468,
35226,
7,
79,
58,
18,
4357,
705,
3672,
11537,
290,
279,
58,
18,
4083,
3672,
6624,
705,
600,
62,
18250,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
18,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
271,
43,
8367,
796,
657,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
18,
4357,
705,
12394,
3256,
352,
11,
685,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
4798,
62,
600,
3256,
2198,
62,
45286,
7,
79,
58,
15,
46570,
705,
3256,
10148,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
18557,
5317,
1273,
16762,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
18557,
13290,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
18557,
13290,
1273,
16762,
1058,
4810,
12394,
43,
45,
37491,
15919,
4731,
62,
18250,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
18,
60,
198,
220,
220,
220,
1438,
796,
6194,
62,
11487,
13,
14421,
62,
29982,
1343,
705,
62,
6,
1343,
2429,
10786,
2536,
62,
4868,
11537,
198,
220,
220,
220,
10007,
19667,
796,
38357,
10962,
19667,
7,
79,
58,
18,
4083,
7890,
11,
279,
58,
18,
4083,
15414,
62,
4906,
8,
198,
220,
220,
220,
649,
19667,
796,
38357,
10962,
19667,
7,
3672,
11,
279,
58,
18,
4083,
15414,
62,
4906,
11,
10007,
796,
685,
17143,
7307,
19667,
12962,
198,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
7785,
7,
3605,
19667,
8,
198,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
4798,
62,
2536,
3256,
1438,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
18557,
13290,
1273,
16762,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
37835,
10186,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
37835,
10186,
1058,
4757,
37835,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5994,
37835,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12372,
37835,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
37835,
10186,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
34184,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
34184,
37835,
1058,
7102,
2257,
37491,
15919,
4757,
22882,
8053,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
7102,
2257,
4757,
22882,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
34184,
22882,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
34184,
22882,
8053,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4757,
22882,
8053,
4757,
22882,
48603,
2149,
3535,
1340,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
34184,
22882,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
34184,
22882,
1058,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
36529,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
36529,
41986,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
5994,
36529,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
5994,
36529,
41986,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
33234,
7483,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
33234,
7483,
8053,
1058,
4522,
3525,
5064,
38311,
9440,
5673,
11440,
7483,
20630,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
10139,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4357,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
33234,
7483,
8053,
3256,
657,
11,
705,
14202,
3256,
657,
11,
685,
17440,
60,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
33234,
7483,
20630,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
33234,
7483,
20630,
8053,
1058,
4522,
3525,
5064,
38311,
9440,
5673,
11440,
7483,
20630,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10139,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4357,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
33234,
7483,
20630,
8053,
3256,
657,
11,
705,
14202,
3256,
657,
11,
685,
17440,
12962,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
10139,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4357,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
33234,
7483,
20630,
8053,
3256,
657,
11,
705,
14202,
3256,
657,
11,
685,
17440,
60,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
628,
198,
4299,
279,
62,
16870,
2234,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
16870,
2234,
8053,
1058,
41986,
9440,
5673,
41986,
20630,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
16870,
2234,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
11907,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
16870,
2234,
20630,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
16870,
2234,
20630,
8053,
1058,
41986,
9440,
5673,
41986,
20630,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
16870,
2234,
20630,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
60,
4357,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
16870,
2234,
20630,
8053,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
79,
58,
16,
11907,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
37835,
1058,
41876,
5994,
22882,
9126,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
22882,
9126,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
22882,
9126,
8053,
1058,
5994,
22882,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
5994,
22882,
8053,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
22882,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
22882,
8053,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5994,
22882,
8053,
5994,
22882,
48603,
2149,
3535,
1340,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
22882,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
22882,
1058,
978,
4448,
37835,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5994,
7469,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
40489,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
40489,
37835,
1058,
4522,
3525,
5064,
38311,
36529,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
7469,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
7469,
1058,
4522,
3525,
5064,
38311,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
1058,
5994,
43,
270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
8997,
31431,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
5994,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
6030,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
23615,
31431,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
23615,
31431,
1058,
4810,
1961,
36,
20032,
1961,
62,
9936,
47,
1546,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
23615,
31431,
3256,
279,
58,
16,
4357,
705,
45,
11651,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
6030,
43,
270,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
6030,
43,
270,
1058,
15690,
6030,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
32112,
6030,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
15553,
6030,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
7695,
3849,
6030,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
6030,
43,
270,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
18833,
3849,
6030,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
18833,
3849,
6030,
1058,
25424,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19182,
6030,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19182,
6030,
1058,
30948,
10917,
12203,
15690,
24539,
19340,
10917,
12203,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
19182,
6030,
3256,
279,
58,
17,
4083,
7890,
11,
279,
58,
19,
4083,
7890,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19182,
24539,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19182,
24539,
1058,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
19182,
24539,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
44909,
6030,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
44909,
6030,
1058,
19269,
18415,
22228,
4261,
11319,
7663,
37835,
8053,
13987,
4261,
11319,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
15878,
37835,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
15878,
37835,
8053,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
7663,
37835,
8053,
7663,
37835,
48603,
2149,
3535,
1340,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
15878,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
15878,
37835,
1058,
11440,
7483,
8053,
5994,
17467,
9126,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
5994,
17467,
9126,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
24835,
9126,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
24835,
9126,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
17467,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
24835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
24835,
1058,
4731,
62,
18250,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22203,
6030,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22203,
6030,
1058,
29397,
34,
34894,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
11712,
1300,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
11712,
1300,
1058,
40117,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
40117,
25414,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
11712,
1300,
6,
198,
220,
220,
220,
264,
796,
705,
29982,
62,
6,
1343,
965,
7,
11925,
7,
27568,
17816,
29982,
20520,
4008,
198,
220,
220,
220,
6194,
62,
11487,
13,
3605,
62,
29982,
7,
82,
8,
198,
220,
220,
220,
329,
1200,
287,
279,
58,
16,
4083,
17197,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
738,
7483,
7,
9410,
11,
264,
8,
198,
220,
220,
220,
220,
220,
220,
220,
649,
19667,
796,
38357,
10962,
19667,
7,
82,
1343,
705,
62,
6,
1343,
1200,
13,
7890,
11,
1200,
13,
15414,
62,
4906,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
7785,
7,
3605,
19667,
11,
264,
8,
198,
220,
220,
220,
1303,
6194,
62,
11487,
13,
4798,
62,
1837,
23650,
62,
11487,
3419,
628,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
15414,
62,
4906,
796,
12200,
19667,
10786,
23004,
3256,
657,
11,
705,
14202,
11537,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
15414,
62,
4906,
796,
279,
58,
17,
60,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
23004,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
23004,
1058,
40117,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
279,
58,
16,
4083,
3672,
6624,
705,
6030,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
23004,
3256,
352,
11,
705,
14202,
3256,
657,
11,
685,
79,
58,
16,
11907,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
23004,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
48944,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
48944,
1058,
37491,
15919,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
25139,
2357,
8053,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
48944,
3256,
657,
11,
705,
14202,
11537,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
48944,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
36301,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
36301,
8053,
1058,
25139,
2357,
37835,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
25139,
2357,
8053,
9440,
5673,
25139,
2357,
37835,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
36301,
8053,
6,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
36301,
8053,
3256,
279,
58,
16,
4083,
7890,
1343,
279,
58,
18,
4083,
7890,
11,
705,
14202,
3256,
657,
11,
279,
58,
16,
4083,
17197,
1343,
279,
58,
18,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
36301,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
36301,
37835,
1058,
11440,
7483,
8053,
5994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
5994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5994,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
36301,
37835,
3256,
657,
11,
705,
14202,
11537,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
468,
35226,
7,
79,
58,
16,
4357,
705,
3672,
11537,
290,
220,
279,
58,
16,
4083,
3672,
6624,
705,
33234,
7483,
8053,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
10139,
287,
279,
58,
16,
4083,
17197,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10139,
13,
15414,
62,
4906,
796,
279,
58,
17,
4083,
7890,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
17197,
15853,
685,
17440,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10139,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4357,
279,
58,
17,
4083,
7890,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
17197,
15853,
685,
17440,
60,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
17197,
15853,
685,
79,
58,
16,
11907,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19852,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19852,
37835,
1058,
569,
1503,
12372,
22882,
9126,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
19852,
37835,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19852,
22882,
9126,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19852,
22882,
9126,
8053,
1058,
12372,
22882,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
12372,
22882,
8053,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
19852,
22882,
9126,
8053,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19852,
22882,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19852,
22882,
8053,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12372,
22882,
8053,
12372,
22882,
48603,
2149,
3535,
1340,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
19852,
22882,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
19852,
22882,
1058,
4522,
3525,
5064,
38311,
5994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
36529,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
5994,
36529,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
5994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
36529,
41986,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
11440,
7483,
8053,
5994,
36529,
41986,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
1303,
35835,
656,
6194,
3084,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
19852,
22882,
3256,
657,
11,
705,
45,
11651,
11537,
198,
220,
220,
220,
611,
468,
35226,
7,
79,
58,
16,
4357,
705,
3672,
11537,
290,
220,
279,
58,
16,
4083,
3672,
6624,
705,
33234,
7483,
8053,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
6632,
62,
2100,
796,
12200,
19667,
10786,
12501,
4402,
62,
18250,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
300,
16,
796,
18896,
7,
79,
58,
16,
4083,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
44052,
62,
4868,
796,
12200,
19667,
10786,
3109,
1050,
62,
8053,
3256,
657,
11,
705,
45,
11651,
3256,
657,
11,
685,
22570,
62,
2100,
60,
1635,
300,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1288,
361,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
44052,
62,
4868,
796,
279,
58,
18,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1288,
361,
18896,
7,
79,
8,
6624,
642,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
44052,
62,
4868,
796,
279,
58,
19,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
300,
17,
796,
18896,
7,
31937,
62,
4868,
13,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
31937,
62,
4868,
13,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
611,
300,
16,
6624,
300,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
75,
16,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
28,
3256,
279,
58,
16,
4083,
17197,
58,
72,
4357,
44052,
62,
4868,
13,
17197,
58,
72,
4083,
7890,
11,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
24720,
46318,
25,
366,
1343,
965,
7,
75,
16,
8,
1343,
366,
27421,
7,
82,
8,
475,
366,
1343,
965,
7,
75,
17,
8,
1343,
366,
1988,
7,
82,
8,
4943,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
16,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
79,
58,
16,
60,
4032,
12394,
3256,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
4083,
15414,
62,
4906,
14512,
705,
45,
11651,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7177,
1339,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
17,
4083,
4798,
62,
17440,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6194,
62,
11487,
13,
2860,
62,
738,
7483,
7,
79,
58,
16,
4357,
2546,
796,
279,
58,
17,
4083,
7890,
8,
6624,
10352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
3118,
540,
284,
751,
284,
38357,
10962,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
796,
6194,
62,
11487,
13,
12947,
62,
738,
7483,
7,
79,
58,
16,
4083,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
19667,
796,
38357,
10962,
19667,
7,
3672,
11,
279,
58,
16,
4083,
15414,
62,
4906,
11,
7857,
796,
279,
58,
17,
4083,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
7785,
7,
3605,
19667,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
19852,
22882,
3256,
79,
58,
16,
4083,
7890,
4032,
12394,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
44052,
796,
12200,
19667,
10786,
3109,
1050,
3256,
657,
11,
705,
45,
11651,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
44052,
796,
279,
58,
18,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
28,
3256,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
31937,
828,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1288,
361,
18896,
7,
79,
8,
6624,
642,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
44052,
796,
279,
58,
19,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
19,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
28,
3256,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
31937,
828,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22203,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22203,
37835,
1058,
29397,
34,
15553,
5376,
34894,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
29397,
34,
15553,
5376,
34894,
15553,
25842,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
6194,
62,
11487,
13,
4798,
62,
1837,
23650,
62,
11487,
3419,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
22203,
37835,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
1303,
3601,
6194,
62,
11487,
13,
14421,
62,
29982,
198,
220,
220,
220,
1303,
279,
58,
19,
4083,
51,
2246,
13,
4798,
62,
8189,
3419,
198,
220,
220,
220,
6194,
62,
11487,
13,
2860,
62,
8818,
7,
79,
58,
17,
4083,
7890,
11,
279,
58,
18,
4083,
15414,
62,
4906,
11,
279,
58,
18,
4083,
17197,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
642,
25,
198,
220,
220,
220,
220,
220,
220,
220,
645,
5189,
10044,
4105,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
329,
277,
287,
6194,
62,
11487,
13,
1837,
23650,
62,
11487,
58,
1837,
23650,
62,
11487,
13,
14421,
62,
29982,
7131,
6,
12543,
2733,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
277,
13,
3672,
6624,
279,
58,
17,
4083,
7890,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
5189,
10044,
4105,
796,
18896,
7,
69,
13,
17143,
7307,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
20786,
3256,
2198,
62,
45286,
7,
79,
58,
17,
46570,
965,
7,
3919,
5189,
10044,
4105,
828,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1200,
287,
17687,
7,
79,
58,
18,
4083,
17197,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
1136,
17143,
3256,
279,
58,
19,
4083,
7890,
1343,
705,
62,
6,
1343,
1200,
13,
7890,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
25558,
62,
14689,
3256,
705,
3256,
705,
3256,
10148,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
19,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22203,
5376,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22203,
5376,
1058,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
22203,
5376,
3256,
279,
58,
16,
4357,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22203,
25842,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22203,
25842,
1058,
9726,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
22203,
25842,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
26437,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
26437,
1273,
16762,
1058,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
50144,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
10073,
19852,
37835,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
3457,
10707,
1273,
16762,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
26437,
1273,
16762,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
25517,
10707,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
25517,
10707,
1273,
16762,
1058,
41986,
48635,
62,
6489,
2937,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
20625,
2937,
62,
23678,
2937,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
530,
62,
2100,
796,
12200,
19667,
10786,
25517,
10707,
1273,
16762,
3256,
705,
16,
3256,
705,
12394,
11537,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
611,
279,
58,
16,
4083,
271,
43,
8367,
6624,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
60,
6624,
705,
4880,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
10,
3256,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
16,
46570,
530,
62,
2100,
13,
7890,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
12,
3256,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
16,
46570,
530,
62,
2100,
13,
7890,
12962,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43,
8367,
2672,
4943,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
25517,
10707,
1273,
16762,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
16438,
19852,
37835,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
16438,
19852,
37835,
1058,
41986,
8053,
24994,
16284,
62,
3185,
41986,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
24994,
16284,
62,
3185,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
16926,
46,
25,
3060,
287,
6194,
3084,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
16438,
19852,
37835,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
611,
279,
58,
16,
4083,
3672,
6624,
705,
16870,
2234,
8053,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
18896,
7,
79,
58,
16,
4083,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
300,
17,
796,
18896,
7,
79,
58,
18,
4083,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
300,
16,
6624,
300,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
75,
16,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
16,
4083,
17197,
58,
72,
4083,
271,
43,
8367,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43,
8367,
2672,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6194,
62,
11487,
13,
2860,
62,
738,
7483,
7,
79,
58,
16,
4083,
17197,
58,
72,
12962,
6624,
10352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
3118,
540,
284,
751,
284,
38357,
10962,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
79,
58,
17,
4357,
2198,
62,
45286,
7,
79,
58,
16,
4083,
17197,
58,
72,
46570,
2198,
62,
45286,
7,
79,
58,
18,
4083,
17197,
58,
72,
46570,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
24720,
46318,
25,
366,
1343,
965,
7,
75,
16,
8,
1343,
366,
27421,
7,
82,
8,
475,
366,
1343,
965,
7,
75,
17,
8,
1343,
366,
1988,
7,
82,
8,
4943,
628,
220,
220,
220,
1288,
361,
279,
58,
16,
4083,
3672,
6624,
705,
16870,
2234,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
16,
4083,
271,
43,
8367,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43,
8367,
2672,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6194,
62,
11487,
13,
2860,
62,
738,
7483,
7,
79,
58,
16,
12962,
6624,
10352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
3118,
540,
284,
751,
284,
38357,
10962,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
79,
58,
17,
4357,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
18,
46570,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
8021,
16747,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
8021,
16747,
1058,
41986,
8053,
8333,
62,
404,
41986,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
8333,
62,
404,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
8021,
16747,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
611,
279,
58,
16,
4083,
3672,
6624,
705,
16870,
2234,
8053,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
18896,
7,
79,
58,
16,
4083,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
300,
17,
796,
18896,
7,
79,
58,
18,
4083,
17197,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
300,
16,
6624,
300,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
75,
16,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
16,
4083,
17197,
58,
72,
4083,
271,
43,
8367,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43,
8367,
2672,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6194,
62,
11487,
13,
12947,
62,
738,
7483,
7,
79,
58,
16,
4083,
17197,
58,
72,
4083,
7890,
8,
6624,
10352,
290,
279,
58,
16,
4083,
17197,
58,
72,
4083,
7890,
407,
287,
7560,
17816,
29510,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
366,
1343,
279,
58,
16,
4083,
17197,
58,
72,
4083,
7890,
1343,
366,
318,
28721,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
18,
4083,
17197,
58,
72,
4083,
271,
43,
8367,
6624,
352,
290,
6194,
62,
11487,
13,
12947,
62,
738,
7483,
7,
79,
58,
18,
4083,
17197,
58,
72,
4083,
7890,
8,
6624,
10352,
290,
279,
58,
18,
4083,
17197,
58,
72,
4083,
7890,
407,
287,
7560,
17816,
29510,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
366,
1343,
279,
58,
18,
4083,
17197,
58,
72,
4083,
7890,
1343,
366,
318,
28721,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
79,
58,
17,
4083,
7890,
11,
2198,
62,
45286,
7,
79,
58,
16,
4083,
17197,
58,
72,
46570,
2198,
62,
45286,
7,
79,
58,
18,
4083,
17197,
58,
72,
46570,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
24720,
46318,
25,
366,
1343,
965,
7,
75,
16,
8,
1343,
366,
27421,
7,
82,
8,
475,
366,
1343,
965,
7,
75,
17,
8,
1343,
366,
1988,
7,
82,
8,
4943,
628,
220,
220,
220,
1288,
361,
279,
58,
16,
4083,
3672,
6624,
705,
16870,
2234,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
16,
4083,
271,
43,
8367,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43,
8367,
2672,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6194,
62,
11487,
13,
12947,
62,
738,
7483,
7,
79,
58,
16,
4083,
7890,
8,
6624,
10352,
290,
279,
58,
16,
4083,
7890,
407,
287,
7560,
17816,
29510,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
366,
1343,
279,
58,
16,
4083,
7890,
1343,
366,
318,
28721,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
18,
4083,
271,
43,
8367,
6624,
352,
290,
6194,
62,
11487,
13,
12947,
62,
738,
7483,
7,
79,
58,
18,
4083,
7890,
8,
6624,
10352,
290,
279,
58,
18,
4083,
7890,
407,
287,
7560,
17816,
29510,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
7203,
43015,
366,
1343,
279,
58,
18,
4083,
7890,
1343,
366,
318,
28721,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3601,
6194,
62,
11487,
13,
14421,
62,
29982,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
79,
58,
17,
4083,
7890,
11,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
18,
46570,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
562,
570,
62,
404,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
562,
570,
62,
404,
1058,
36529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
48635,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
20625,
2937,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
6375,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
17368,
2767,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
25424,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
360,
3824,
14114,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
19164,
6239,
46,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
30948,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
19340,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
3001,
47,
62,
36,
48,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5357,
62,
1581,
62,
36,
48,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
562,
570,
62,
404,
3256,
279,
58,
16,
4357,
705,
31054,
25633,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
1532,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
1532,
1273,
16762,
1058,
16876,
41986,
9726,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
16876,
41986,
9726,
17852,
5188,
2073,
51,
603,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
1532,
1273,
16762,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
361,
70,
2069,
27363,
3256,
2198,
62,
45286,
7,
79,
58,
17,
46570,
705,
15,
3256,
300,
16,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
718,
25,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
300,
17,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
1532,
1273,
16762,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
361,
70,
2069,
27363,
3256,
2198,
62,
45286,
7,
79,
58,
17,
46570,
705,
15,
3256,
300,
16,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
70,
2069,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
20,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
17772,
51,
603,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
17772,
51,
603,
1058,
1002,
1273,
16762,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
9726,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
17772,
51,
603,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
38978,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
38978,
1273,
16762,
1058,
1475,
1050,
38978,
1273,
16762,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
38978,
1273,
16762,
3256,
657,
11,
705,
12394,
3256,
657,
11,
685,
4357,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
3109,
1050,
38978,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
3109,
1050,
38978,
1273,
16762,
1058,
12672,
31949,
17427,
1273,
16762,
48603,
2149,
3535,
1340,
22228,
4261,
11319,
41063,
10434,
1475,
1050,
20448,
2601,
682,
8053,
41063,
12915,
13987,
4261,
11319,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12672,
31949,
17427,
1273,
16762,
48603,
2149,
3535,
1340,
41986,
22228,
4261,
11319,
41063,
10434,
1475,
1050,
20448,
2601,
682,
8053,
41063,
12915,
13987,
4261,
11319,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12672,
31949,
22228,
4261,
11319,
41063,
10434,
1475,
1050,
20448,
2601,
682,
8053,
41063,
12915,
13987,
4261,
11319,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12672,
31949,
41986,
22228,
4261,
11319,
41063,
10434,
1475,
1050,
20448,
2601,
682,
8053,
41063,
12915,
13987,
4261,
11319,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
807,
25,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
300,
17,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
3109,
1050,
38978,
1273,
16762,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
256,
16,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
2429,
10786,
29510,
33809,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
28,
3256,
2198,
62,
45286,
7,
83,
16,
8,
837,
2198,
62,
45286,
7,
79,
58,
17,
46570,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
20,
4083,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
11925,
7,
79,
58,
20,
4083,
17197,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
361,
70,
2069,
27363,
3256,
2198,
62,
45286,
7,
83,
16,
828,
279,
58,
20,
4083,
17197,
58,
72,
7131,
15,
4357,
279,
58,
20,
4083,
17197,
58,
72,
7131,
16,
11907,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
70,
2069,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
79,
58,
20,
4083,
51,
2246,
13,
13664,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
287,
279,
58,
20,
4083,
51,
2246,
13,
37553,
58,
16,
25,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
70,
2069,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
79,
58,
20,
4083,
51,
2246,
13,
8189,
58,
72,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
3109,
1050,
20448,
2601,
682,
8053,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
3109,
1050,
20448,
2601,
682,
8053,
1058,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
1475,
1050,
20448,
2601,
682,
8053,
1475,
1050,
20448,
2601,
682,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
309,
2246,
16,
796,
7683,
20231,
10669,
3419,
198,
220,
220,
220,
309,
2246,
17,
796,
7683,
20231,
10669,
3419,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
309,
2246,
16,
796,
279,
58,
16,
4083,
7890,
198,
220,
220,
220,
220,
220,
220,
220,
309,
2246,
17,
796,
279,
58,
17,
4083,
7890,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
3109,
1050,
20448,
2601,
682,
8053,
3256,
309,
2246,
16,
11,
705,
12394,
3256,
657,
11,
279,
58,
16,
4083,
17197,
1343,
279,
58,
17,
4083,
17197,
11,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
27940,
7,
79,
58,
15,
4083,
51,
2246,
13,
13664,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
13,
33295,
62,
51,
2246,
7,
51,
2246,
17,
8,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
3109,
1050,
20448,
2601,
682,
8053,
3256,
309,
2246,
16,
11,
705,
12394,
11537,
628,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
3109,
1050,
20448,
2601,
682,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
3109,
1050,
20448,
2601,
682,
1058,
1475,
1050,
38978,
20448,
20444,
1340,
21983,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
3109,
1050,
20448,
2601,
682,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
361,
23442,
505,
80,
3256,
279,
58,
16,
4083,
17197,
11,
279,
58,
16,
4083,
17197,
11,
300,
16,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
279,
58,
15,
4083,
17197,
796,
16410,
79,
58,
16,
4083,
7890,
11,
75,
16,
11907,
198,
220,
220,
220,
279,
58,
15,
4083,
7890,
796,
279,
58,
16,
4083,
51,
2246,
628,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
3109,
1050,
38978,
20448,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
3109,
1050,
38978,
20448,
1058,
42001,
41986,
8053,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5550,
38865,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
42001,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
3109,
1050,
38978,
20448,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
796,
279,
58,
17,
4083,
7890,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
796,
279,
58,
17,
4083,
51,
2246,
628,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
1890,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
1890,
1273,
16762,
1058,
7473,
41986,
9726,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
7473,
9726,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
1890,
1273,
16762,
3256,
657,
11,
705,
12394,
11537,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
300,
17,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
361,
70,
2069,
27363,
3256,
9122,
62,
45286,
7,
79,
58,
17,
46570,
705,
15,
3256,
300,
17,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
70,
2069,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
17,
11,
705,
3256,
10148,
12962,
628,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
300,
16,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
300,
17,
796,
2429,
10786,
18242,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
18242,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
70,
2069,
3256,
300,
16,
11,
705,
3256,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
75,
17,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
13615,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
13615,
1273,
16762,
1058,
30826,
27064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
30826,
27064,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
30826,
27064,
41986,
8053,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
13615,
1273,
16762,
3256,
657,
11,
705,
14202,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
7783,
3256,
705,
3256,
705,
3256,
10148,
12962,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
4083,
3672,
6624,
705,
16870,
2234,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
13615,
1273,
16762,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
7783,
3256,
2198,
62,
45286,
7,
79,
58,
17,
46570,
705,
3256,
10148,
12962,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
31737,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
31737,
1273,
16762,
1058,
29377,
10206,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
29453,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
29453,
1273,
16762,
1058,
43659,
8924,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
38,
2069,
1273,
16762,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
38,
2069,
1273,
16762,
1058,
402,
26631,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
16870,
2234,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
16870,
2234,
1058,
791,
560,
3109,
1050,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
6375,
62,
1581,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
3001,
47,
62,
23518,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
36529,
62,
36,
48,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
5626,
62,
36,
48,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
34146,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
34146,
62,
36,
48,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
7963,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
7963,
62,
36,
48,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
48635,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
20625,
2937,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
6375,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
17368,
2767,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
25424,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
360,
3824,
14114,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
19164,
6239,
46,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
30948,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
19340,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
3001,
47,
41986,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
41986,
5357,
62,
1581,
41986,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
2429,
10786,
29510,
33809,
705,
12394,
3256,
352,
11,
685,
4357,
279,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
18,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
79,
58,
17,
4357,
9122,
62,
45286,
7,
79,
58,
15,
46570,
2198,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
18,
12962,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
16870,
2234,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
3118,
560,
3109,
1050,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
3118,
560,
3109,
1050,
1058,
21087,
3109,
1050,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
555,
560,
62,
404,
791,
560,
3109,
1050,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
2429,
10786,
29510,
33809,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
26933,
9122,
62,
45286,
7,
79,
58,
16,
46570,
2198,
62,
45286,
7,
79,
58,
15,
46570,
2198,
62,
45286,
7,
79,
58,
17,
46570,
10148,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
3118,
560,
3109,
1050,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
403,
560,
62,
404,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
403,
560,
62,
404,
1058,
48635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
20625,
2937,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
5626,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
17368,
2767,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
25424,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
3001,
47,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
34146,
62,
23678,
2937,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
403,
560,
62,
404,
3256,
279,
58,
16,
4357,
705,
31054,
25633,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
35170,
3109,
1050,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
35170,
3109,
1050,
1058,
6564,
392,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
21087,
3109,
1050,
9683,
273,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
21087,
3109,
1050,
12901,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
21087,
3109,
1050,
20559,
2886,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
13,
48369,
58,
16,
4083,
4906,
6624,
705,
25256,
5064,
38311,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4357,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
279,
58,
16,
4083,
3672,
6624,
705,
18843,
392,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
1288,
361,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
4083,
3672,
6624,
705,
15732,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
279,
58,
16,
4083,
7890,
11,
705,
12394,
3256,
352,
11,
279,
58,
17,
4083,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
279,
58,
17,
4083,
3672,
6624,
705,
28100,
2886,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
25256,
5064,
38311,
3256,
2429,
10786,
29510,
33809,
705,
12394,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
16,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
33295,
62,
51,
2246,
7,
79,
58,
17,
4083,
51,
2246,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
16,
4083,
4798,
62,
17440,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25439,
796,
2198,
62,
45286,
7,
79,
58,
16,
35944,
35312,
7203,
62,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8354,
11,
25439,
5376,
796,
220,
45434,
1911,
22179,
7,
20786,
58,
25,
17,
46570,
45434,
1911,
22179,
7,
20786,
58,
17,
25,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
277,
287,
6194,
62,
11487,
13,
1837,
23650,
62,
11487,
58,
29982,
7131,
6,
12543,
2733,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
277,
13,
3672,
6624,
25439,
5376,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
796,
18896,
7,
69,
13,
17143,
7307,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
58,
17,
4083,
4798,
62,
17440,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1200,
287,
279,
58,
17,
4083,
17197,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
1996,
17143,
3256,
2198,
62,
45286,
7,
9410,
828,
705,
3256,
10148,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
20218,
14512,
279,
58,
17,
4083,
7890,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
18224,
10786,
22203,
705,
1343,
25439,
5376,
1343,
705,
4433,
705,
1343,
965,
7,
29510,
8,
1343,
705,
10007,
475,
705,
1343,
965,
7,
79,
58,
17,
4083,
7890,
8,
1343,
705,
14275,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
13345,
3256,
2198,
62,
45286,
7,
79,
58,
16,
46570,
965,
7,
79,
58,
17,
4083,
7890,
828,
10148,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
51,
2246,
13,
2860,
62,
1370,
7,
17816,
7783,
62,
8367,
3256,
2198,
62,
45286,
7,
79,
58,
15,
46570,
705,
3256,
10148,
12962,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
35170,
3109,
1050,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
18843,
392,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
18843,
392,
220,
1058,
25659,
1691,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
41986,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
18843,
392,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
43,
270,
1691,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
43,
270,
1691,
220,
1058,
14392,
43,
270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
15553,
43,
270,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
43,
270,
1691,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
26416,
43,
270,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
26416,
43,
270,
1058,
493,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
12178,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
4731,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
35930,
62,
18250,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
26416,
43,
270,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
600,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
600,
62,
18250,
1058,
32465,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
19318,
282,
62,
18250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
17910,
62,
18250,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
16,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
600,
62,
18250,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
12501,
4402,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
12501,
4402,
62,
18250,
1058,
27196,
3955,
1847,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
12501,
4402,
62,
18250,
3256,
279,
58,
16,
4357,
705,
12394,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
38441,
282,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
38441,
282,
62,
18250,
1058,
42256,
1847,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
38441,
282,
62,
18250,
3256,
279,
58,
16,
4357,
705,
46,
4177,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
33095,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
33095,
62,
18250,
220,
1058,
367,
6369,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
33095,
62,
18250,
3256,
279,
58,
16,
4357,
705,
39,
6369,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22468,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22468,
62,
18250,
1058,
9977,
46,
1404,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
22468,
62,
18250,
3256,
279,
58,
16,
4357,
705,
3697,
46,
1404,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
22203,
43,
270,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
22203,
43,
270,
1058,
29397,
34,
34894,
15553,
25842,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1303,
19200,
15553,
198,
220,
220,
220,
1303,
1892,
9177,
1865,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
17563,
273,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
17563,
273,
1058,
42743,
4522,
3525,
5064,
38311,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
15732,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
15732,
1058,
30948,
10917,
12203,
41986,
19340,
10917,
12203,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
15732,
6,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
28100,
2886,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
28100,
2886,
1058,
37491,
15919,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
41986,
8053,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
41986,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
5994,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
5994,
9440,
5673,
41986,
8053,
26067,
15919,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
930,
37491,
15919,
5994,
9440,
5673,
41986,
26067,
15919,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
1303,
3601,
279,
13,
48369,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
28100,
2886,
3256,
657,
11,
705,
14202,
11537,
198,
220,
220,
220,
611,
18896,
7,
79,
8,
6624,
604,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
4083,
3672,
6624,
705,
16870,
2234,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
28100,
2886,
3256,
352,
11,
705,
14202,
3256,
657,
11,
685,
79,
58,
17,
60,
4357,
279,
58,
17,
4083,
51,
2246,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
58,
17,
4083,
3672,
6624,
705,
16870,
2234,
8053,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
60,
796,
279,
58,
17,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
3672,
796,
705,
28100,
2886,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
58,
15,
4083,
7890,
796,
18896,
7,
79,
58,
17,
4083,
17197,
8,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
8841,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
8841,
62,
18250,
1058,
19269,
2751,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
8841,
62,
18250,
3256,
279,
58,
16,
4357,
705,
18601,
2751,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
81,
1726,
62,
18250,
7,
79,
2599,
198,
220,
220,
220,
705,
7061,
81,
1726,
62,
18250,
1058,
32494,
36,
62,
43,
2043,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
44267,
13,
33295,
7,
79,
13,
48369,
8,
198,
220,
220,
220,
279,
58,
15,
60,
796,
12200,
19667,
10786,
81,
1726,
62,
18250,
3256,
279,
58,
16,
4357,
705,
49,
41884,
11537,
198,
220,
220,
220,
1441,
198,
198,
4299,
279,
62,
28920,
7,
79,
2599,
198,
220,
220,
220,
705,
28920,
1058,
6,
198,
220,
220,
220,
1208,
198,
198,
2,
8997,
5972,
1362,
198,
6404,
2667,
13,
35487,
16934,
7,
198,
220,
220,
220,
1241,
796,
18931,
13,
30531,
11,
198,
220,
220,
220,
29472,
796,
366,
1845,
741,
519,
13,
14116,
1600,
198,
220,
220,
220,
2393,
14171,
796,
366,
86,
1600,
198,
220,
220,
220,
5794,
796,
36521,
7,
34345,
8,
940,
82,
25,
4,
7,
2815,
23397,
8,
19,
67,
25,
4,
7,
20500,
8,
82,
1,
198,
8,
198,
198,
6404,
796,
18931,
13,
1136,
11187,
1362,
3419,
198,
198,
88,
4134,
13,
88,
4134,
7,
24442,
28,
17821,
11,
14257,
6404,
28,
6404,
8,
198,
198,
15414,
62,
7753,
796,
25064,
13,
853,
85,
58,
16,
60,
198,
198,
11748,
28686,
198,
361,
28686,
13,
6978,
13,
4468,
576,
7,
15414,
62,
7753,
8,
318,
10352,
25,
198,
220,
220,
220,
3601,
10786,
20560,
2393,
705,
1343,
5128,
62,
7753,
1343,
705,
857,
407,
2152,
11537,
198,
220,
220,
220,
25064,
13,
37023,
7,
16,
8,
198,
198,
15414,
62,
8189,
796,
1280,
7,
15414,
62,
7753,
11,
705,
81,
27691,
961,
3419,
198,
198,
361,
5128,
62,
8189,
58,
11925,
7,
15414,
62,
8189,
13219,
16,
60,
14512,
705,
59,
77,
10354,
198,
220,
220,
220,
5128,
62,
8189,
15853,
705,
59,
77,
6,
198,
198,
88,
4134,
13,
29572,
7,
15414,
62,
8189,
11,
14257,
28,
6404,
11,
9646,
28,
17821,
8,
628
] | 1.925113 | 17,533 |
import argparse
import imageio
import progressbar
from _routines import ffi, lib
from pylab import *
from random import Random
RESOLUTIONS = {
"2160p": (3840, 2160),
"1440p": (2560, 1440),
"1080p": (1920, 1080),
"720p": (1280, 720),
"480p": (854, 480),
"360p": (640, 360),
"240p": (426, 240),
"160p": (284, 160),
"80p": (142, 80),
"40p": (71, 40),
}
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Render audio samples')
parser.add_argument('outfile', type=str, help='Output file name')
parser.add_argument('--params', type=str, help='Parameter YAML file name')
parser.add_argument('--resolution', choices=RESOLUTIONS.keys(), help='Video and simulation grid resolution')
parser.add_argument('--width', type=int, help='Video and simulation grid width', metavar='W')
parser.add_argument('--height', type=int, help='Video and simulation grid height', metavar='H')
parser.add_argument('--framerate', type=int, help='Video frame rate')
parser.add_argument('--video-quality', type=int, help='Video quality factor')
parser.add_argument('--video-duration', type=float, help='Duration of video to render in seconds')
args = parser.parse_args()
if not args.framerate:
args.framerate = 24
if not args.video_quality:
args.video_quality = 10
writer = imageio.get_writer(args.outfile, fps=args.framerate, quality=args.video_quality, macro_block_size=1)
# Compute derived parameters
if args.resolution:
width, height = RESOLUTIONS[args.resolution]
if not args.width:
args.width = width
if not args.height:
args.height = height
if (not args.width) or (not args.height):
raise ValueError("Invalid or missing resolution")
if not args.video_duration:
raise ValueError("Missing video duration")
args.aspect = args.width / args.height
args.num_frames = int(args.video_duration * args.framerate)
args.dt = 1.0 / args.num_frames
do_render(args, writer)
writer.close()
| [
11748,
1822,
29572,
198,
11748,
2939,
952,
198,
11748,
4371,
5657,
198,
6738,
4808,
81,
448,
1127,
1330,
277,
12463,
11,
9195,
198,
6738,
279,
2645,
397,
1330,
1635,
198,
6738,
4738,
1330,
14534,
198,
198,
19535,
3535,
3843,
11053,
796,
1391,
198,
220,
220,
220,
366,
17,
14198,
79,
1298,
357,
2548,
1821,
11,
362,
14198,
828,
198,
220,
220,
220,
366,
1415,
1821,
79,
1298,
357,
1495,
1899,
11,
49557,
828,
198,
220,
220,
220,
366,
24045,
79,
1298,
357,
40454,
11,
17729,
828,
198,
220,
220,
220,
366,
23906,
79,
1298,
357,
1065,
1795,
11,
26250,
828,
198,
220,
220,
220,
366,
22148,
79,
1298,
357,
23,
4051,
11,
23487,
828,
198,
220,
220,
220,
366,
15277,
79,
1298,
357,
31102,
11,
11470,
828,
198,
220,
220,
220,
366,
16102,
79,
1298,
357,
42780,
11,
14956,
828,
198,
220,
220,
220,
366,
14198,
79,
1298,
357,
30336,
11,
13454,
828,
198,
220,
220,
220,
366,
1795,
79,
1298,
357,
23726,
11,
4019,
828,
198,
220,
220,
220,
366,
1821,
79,
1298,
357,
4869,
11,
2319,
828,
198,
92,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
30751,
796,
1822,
29572,
13,
28100,
1713,
46677,
7,
11213,
11639,
45819,
6597,
8405,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
448,
7753,
3256,
2099,
28,
2536,
11,
1037,
11639,
26410,
2393,
1438,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
37266,
3256,
2099,
28,
2536,
11,
1037,
11639,
36301,
575,
2390,
43,
2393,
1438,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
29268,
3256,
7747,
28,
19535,
3535,
3843,
11053,
13,
13083,
22784,
1037,
11639,
10798,
290,
18640,
10706,
6323,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
10394,
3256,
2099,
28,
600,
11,
1037,
11639,
10798,
290,
18640,
10706,
9647,
3256,
1138,
615,
283,
11639,
54,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
17015,
3256,
2099,
28,
600,
11,
1037,
11639,
10798,
290,
18640,
10706,
6001,
3256,
1138,
615,
283,
11639,
39,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
19298,
21620,
3256,
2099,
28,
600,
11,
1037,
11639,
10798,
5739,
2494,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
15588,
12,
13237,
3256,
2099,
28,
600,
11,
1037,
11639,
10798,
3081,
5766,
11537,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
10786,
438,
15588,
12,
32257,
3256,
2099,
28,
22468,
11,
1037,
11639,
26054,
286,
2008,
284,
8543,
287,
4201,
11537,
198,
220,
220,
220,
26498,
796,
30751,
13,
29572,
62,
22046,
3419,
628,
220,
220,
220,
611,
407,
26498,
13,
19298,
21620,
25,
198,
220,
220,
220,
220,
220,
220,
220,
26498,
13,
19298,
21620,
796,
1987,
198,
220,
220,
220,
611,
407,
26498,
13,
15588,
62,
13237,
25,
198,
220,
220,
220,
220,
220,
220,
220,
26498,
13,
15588,
62,
13237,
796,
838,
628,
220,
220,
220,
6260,
796,
2939,
952,
13,
1136,
62,
16002,
7,
22046,
13,
448,
7753,
11,
32977,
28,
22046,
13,
19298,
21620,
11,
3081,
28,
22046,
13,
15588,
62,
13237,
11,
15021,
62,
9967,
62,
7857,
28,
16,
8,
628,
220,
220,
220,
1303,
3082,
1133,
10944,
10007,
198,
220,
220,
220,
611,
26498,
13,
29268,
25,
198,
220,
220,
220,
220,
220,
220,
220,
9647,
11,
6001,
796,
15731,
3535,
3843,
11053,
58,
22046,
13,
29268,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
26498,
13,
10394,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26498,
13,
10394,
796,
9647,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
26498,
13,
17015,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26498,
13,
17015,
796,
6001,
198,
220,
220,
220,
611,
357,
1662,
26498,
13,
10394,
8,
393,
357,
1662,
26498,
13,
17015,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
44651,
393,
4814,
6323,
4943,
198,
220,
220,
220,
611,
407,
26498,
13,
15588,
62,
32257,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
43730,
2008,
9478,
4943,
198,
220,
220,
220,
26498,
13,
292,
806,
796,
26498,
13,
10394,
1220,
26498,
13,
17015,
198,
220,
220,
220,
26498,
13,
22510,
62,
37805,
796,
493,
7,
22046,
13,
15588,
62,
32257,
1635,
26498,
13,
19298,
21620,
8,
198,
220,
220,
220,
26498,
13,
28664,
796,
352,
13,
15,
1220,
26498,
13,
22510,
62,
37805,
628,
220,
220,
220,
466,
62,
13287,
7,
22046,
11,
6260,
8,
628,
220,
220,
220,
6260,
13,
19836,
3419,
198
] | 2.682519 | 778 |
# Copyright (c) 2015 Nicolas JOUANIN
#
# See the file license.txt for copying permission.
import anyio
import unittest
from hbmqtt.mqtt.subscribe import SubscribePacket, SubscribePayload
from hbmqtt.mqtt.packet import PacketIdVariableHeader
from hbmqtt.mqtt.constants import QOS_1, QOS_2
from hbmqtt.adapters import BufferAdapter
| [
2,
15069,
357,
66,
8,
1853,
29737,
449,
2606,
1565,
1268,
198,
2,
198,
2,
4091,
262,
2393,
5964,
13,
14116,
329,
23345,
7170,
13,
198,
11748,
597,
952,
198,
11748,
555,
715,
395,
198,
198,
6738,
289,
20475,
80,
926,
13,
76,
80,
926,
13,
7266,
12522,
1330,
19808,
47,
8317,
11,
19808,
19197,
2220,
198,
6738,
289,
20475,
80,
926,
13,
76,
80,
926,
13,
8002,
316,
1330,
6400,
316,
7390,
43015,
39681,
198,
6738,
289,
20475,
80,
926,
13,
76,
80,
926,
13,
9979,
1187,
1330,
1195,
2640,
62,
16,
11,
1195,
2640,
62,
17,
198,
6738,
289,
20475,
80,
926,
13,
324,
12126,
1330,
47017,
47307,
628
] | 2.990991 | 111 |
import logging
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s',
datefmt='%Y/%m/%d %H:%M:%S',
level=logging.INFO,
)
logger = logging.getLogger("Main")
import os,random
import numpy as np
import torch
from processing import convert_examples_to_features, read_squad_examples
from processing import ChineseFullTokenizer
from pytorch_pretrained_bert.my_modeling import BertConfig
from optimization import BERTAdam
import config
from utils import read_and_convert, divide_parameters
from modeling import BertForQASimple, BertForQASimpleAdaptorTraining
from textbrewer import DistillationConfig, TrainingConfig, BasicTrainer
from torch.utils.data import TensorDataset, DataLoader, RandomSampler
from functools import partial
from train_eval import predict
if __name__ == "__main__":
main()
| [
11748,
18931,
198,
6404,
2667,
13,
35487,
16934,
7,
198,
220,
220,
220,
5794,
11639,
4,
7,
292,
310,
524,
8,
82,
532,
4064,
7,
5715,
3672,
8,
82,
532,
4064,
7,
3672,
8,
82,
532,
220,
4064,
7,
20500,
8,
82,
3256,
198,
220,
220,
220,
3128,
69,
16762,
11639,
4,
56,
14,
4,
76,
14,
4,
67,
4064,
39,
25,
4,
44,
25,
4,
50,
3256,
198,
220,
220,
220,
1241,
28,
6404,
2667,
13,
10778,
11,
198,
220,
220,
220,
1267,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7203,
13383,
4943,
198,
198,
11748,
28686,
11,
25120,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
6738,
7587,
1330,
10385,
62,
1069,
12629,
62,
1462,
62,
40890,
11,
1100,
62,
16485,
324,
62,
1069,
12629,
198,
6738,
7587,
1330,
3999,
13295,
30642,
7509,
198,
6738,
12972,
13165,
354,
62,
5310,
13363,
62,
4835,
13,
1820,
62,
4666,
10809,
1330,
22108,
16934,
198,
6738,
23989,
1330,
347,
17395,
23159,
198,
11748,
4566,
198,
6738,
3384,
4487,
1330,
1100,
62,
392,
62,
1102,
1851,
11,
14083,
62,
17143,
7307,
198,
6738,
21128,
1330,
22108,
1890,
48,
1921,
320,
1154,
11,
22108,
1890,
48,
1921,
320,
1154,
48003,
273,
44357,
198,
6738,
2420,
11269,
263,
1330,
4307,
40903,
16934,
11,
13614,
16934,
11,
14392,
2898,
10613,
198,
6738,
28034,
13,
26791,
13,
7890,
1330,
309,
22854,
27354,
292,
316,
11,
6060,
17401,
11,
14534,
16305,
20053,
198,
6738,
1257,
310,
10141,
1330,
13027,
198,
198,
6738,
4512,
62,
18206,
1330,
4331,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 3.083942 | 274 |
# EXPERIMENTAL: all may be removed soon
from gym.benchmarks import scoring
from gym.benchmarks.registration import benchmark_spec, register_benchmark, registry, register_benchmark_view # imports used elsewhere
register_benchmark(
id='Atari200M',
scorer=scoring.TotalReward(),
name='Atari200M',
view_group="Atari",
description='7 Atari games, with pixel observations',
tasks=[
{
'env_id': 'BeamRiderNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 363.9,
'reward_ceiling': 60000.0,
},
{
'env_id': 'BreakoutNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 1.7,
'reward_ceiling': 800.0,
},
{
'env_id': 'EnduroNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 0.0,
'reward_ceiling': 5000.0,
},
{
'env_id': 'PongNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': -20.7,
'reward_ceiling': 21.0,
},
{
'env_id': 'QbertNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 163.9,
'reward_ceiling': 40000.0,
},
{
'env_id': 'SeaquestNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 68.4,
'reward_ceiling': 100000.0,
},
{
'env_id': 'SpaceInvadersNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(2e8),
'reward_floor': 148.0,
'reward_ceiling': 30000.0,
},
])
register_benchmark(
id='Atari40M',
scorer=scoring.TotalReward(),
name='Atari40M',
view_group="Atari",
description='7 Atari games, with pixel observations',
tasks=[
{
'env_id': 'BeamRiderNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 363.9,
'reward_ceiling': 60000.0,
},
{
'env_id': 'BreakoutNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 1.7,
'reward_ceiling': 800.0,
},
{
'env_id': 'EnduroNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 0.0,
'reward_ceiling': 5000.0,
},
{
'env_id': 'PongNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': -20.7,
'reward_ceiling': 21.0,
},
{
'env_id': 'QbertNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 163.9,
'reward_ceiling': 40000.0,
},
{
'env_id': 'SeaquestNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 68.4,
'reward_ceiling': 100000.0,
},
{
'env_id': 'SpaceInvadersNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 148.0,
'reward_ceiling': 30000.0,
}
])
register_benchmark(
id='AtariExploration40M',
scorer=scoring.TotalReward(),
name='AtariExploration40M',
view_group="Atari",
description='7 Atari games, with pixel observations',
tasks=[
{
'env_id': 'FreewayNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 0.1,
'reward_ceiling': 31.0,
},
{
'env_id': 'GravitarNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 245.5,
'reward_ceiling': 1000.0,
},
{
'env_id': 'MontezumaRevengeNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 25.0,
'reward_ceiling': 10000.0,
},
{
'env_id': 'PitfallNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': -348.8,
'reward_ceiling': 1000.0,
},
{
'env_id': 'PrivateEyeNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 662.8,
'reward_ceiling': 100.0,
},
{
'env_id': 'SolarisNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 2047.2,
'reward_ceiling': 5000.0,
},
{
'env_id': 'VentureNoFrameskip-v4',
'trials': 2,
'max_timesteps': int(4e7),
'reward_floor': 18.0,
'reward_ceiling': 100.0,
}
])
register_benchmark(
id='ClassicControl2-v0',
name='ClassicControl2',
view_group="Control",
description='Simple classic control benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'CartPole-v0',
'trials': 1,
'max_timesteps': 2000,
},
{'env_id': 'Pendulum-v0',
'trials': 1,
'max_timesteps': 1000,
},
])
register_benchmark(
id='ClassicControl-v0',
name='ClassicControl',
view_group="Control",
description='Simple classic control benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'CartPole-v1',
'trials': 3,
'max_timesteps': 100000,
'reward_floor': 0.0,
'reward_ceiling': 500.0,
},
{'env_id': 'Acrobot-v1',
'trials': 3,
'max_timesteps': 100000,
'reward_floor': -500.0,
'reward_ceiling': 0.0,
},
{'env_id': 'MountainCar-v0',
'trials': 3,
'max_timesteps': 100000,
'reward_floor': -200.0,
'reward_ceiling': -100.0,
},
{'env_id': 'Pendulum-v0',
'trials': 3,
'max_timesteps': 200000,
'reward_floor': -1400.0,
'reward_ceiling': 0.0,
},
])
### Autogenerated by tinkerbell.benchmark.convert_benchmark.py
register_benchmark(
id='Mujoco10M-v0',
name='Mujoco10M',
view_group="Control",
description='Mujoco benchmark with 10M steps',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'Ant-v1',
'trials': 1,
'max_timesteps': 1000000,
},
{'env_id': 'Hopper-v1',
'trials': 1,
'max_timesteps': 1000000,
},
{'env_id': 'Humanoid-v1',
'trials': 1,
'max_timesteps': 1000000,
},
{'env_id': 'HumanoidStandup-v1',
'trials': 1,
'max_timesteps': 1000000,
},
{'env_id': 'Walker2d-v1',
'trials': 1,
'max_timesteps': 1000000,
}
])
register_benchmark(
id='Mujoco1M-v0',
name='Mujoco1M',
view_group="Control",
description='Mujoco benchmark with 1M steps',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'HalfCheetah-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': -280.0,
'reward_ceiling': 4000.0,
},
{'env_id': 'Hopper-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': 16.0,
'reward_ceiling': 4000.0,
},
{'env_id': 'InvertedDoublePendulum-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': 53.0,
'reward_ceiling': 10000.0,
},
{'env_id': 'InvertedPendulum-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': 5.6,
'reward_ceiling': 1000.0,
},
{'env_id': 'Reacher-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': -43.0,
'reward_ceiling': -0.5,
},
{'env_id': 'Swimmer-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': 0.23,
'reward_ceiling': 500.0,
},
{'env_id': 'Walker2d-v1',
'trials': 3,
'max_timesteps': 1000000,
'reward_floor': 1.6,
'reward_ceiling': 5500.0,
}
])
register_benchmark(
id='MinecraftEasy-v0',
name='MinecraftEasy',
view_group="Minecraft",
description='Minecraft easy benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'MinecraftBasic-v0',
'trials': 2,
'max_timesteps': 600000,
'reward_floor': -2200.0,
'reward_ceiling': 1000.0,
},
{'env_id': 'MinecraftDefaultFlat1-v0',
'trials': 2,
'max_timesteps': 2000000,
'reward_floor': -500.0,
'reward_ceiling': 0.0,
},
{'env_id': 'MinecraftTrickyArena1-v0',
'trials': 2,
'max_timesteps': 300000,
'reward_floor': -1000.0,
'reward_ceiling': 2800.0,
},
{'env_id': 'MinecraftEating1-v0',
'trials': 2,
'max_timesteps': 300000,
'reward_floor': -300.0,
'reward_ceiling': 300.0,
},
])
register_benchmark(
id='MinecraftMedium-v0',
name='MinecraftMedium',
view_group="Minecraft",
description='Minecraft medium benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'MinecraftCliffWalking1-v0',
'trials': 2,
'max_timesteps': 400000,
'reward_floor': -100.0,
'reward_ceiling': 100.0,
},
{'env_id': 'MinecraftVertical-v0',
'trials': 2,
'max_timesteps': 900000,
'reward_floor': -1000.0,
'reward_ceiling': 8040.0,
},
{'env_id': 'MinecraftMaze1-v0',
'trials': 2,
'max_timesteps': 600000,
'reward_floor': -1000.0,
'reward_ceiling': 1000.0,
},
{'env_id': 'MinecraftMaze2-v0',
'trials': 2,
'max_timesteps': 2000000,
'reward_floor': -1000.0,
'reward_ceiling': 1000.0,
},
])
register_benchmark(
id='MinecraftHard-v0',
name='MinecraftHard',
view_group="Minecraft",
description='Minecraft hard benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'MinecraftObstacles-v0',
'trials': 1,
'max_timesteps': 900000,
'reward_floor': -1000.0,
'reward_ceiling': 2080.0,
},
{'env_id': 'MinecraftSimpleRoomMaze-v0',
'trials': 1,
'max_timesteps': 900000,
'reward_floor': -1000.0,
'reward_ceiling': 4160.0,
},
{'env_id': 'MinecraftAttic-v0',
'trials': 1,
'max_timesteps': 600000,
'reward_floor': -1000.0,
'reward_ceiling': 1040.0,
},
{'env_id': 'MinecraftComplexityUsage-v0',
'trials': 1,
'max_timesteps': 600000,
'reward_floor': -1000.0,
'reward_ceiling': 1000.0,
},
])
register_benchmark(
id='MinecraftVeryHard-v0',
name='MinecraftVeryHard',
view_group="Minecraft",
description='Minecraft very hard benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'MinecraftMedium-v0',
'trials': 2,
'max_timesteps': 1800000,
'reward_floor': -10000.0,
'reward_ceiling': 16280.0,
},
{'env_id': 'MinecraftHard-v0',
'trials': 2,
'max_timesteps': 2400000,
'reward_floor': -10000.0,
'reward_ceiling': 32640.0,
},
])
register_benchmark(
id='MinecraftImpossible-v0',
name='MinecraftImpossible',
view_group="Minecraft",
description='Minecraft impossible benchmark',
scorer=scoring.ClipTo01ThenAverage(),
tasks=[
{'env_id': 'MinecraftDefaultWorld1-v0',
'trials': 2,
'max_timesteps': 6000000,
'reward_floor': -1000.0,
'reward_ceiling': 1000.0,
},
])
bandit_tasks = []
for n_arms in [5, 10, 50]:
for n_episodes in [10, 100, 500]:
bandit_tasks.append({
'env_id': 'BernoulliBandit-{k}.arms-{n}.episodes-v0'.format(k=n_arms, n=n_episodes),
'trials': 1,
'max_timesteps': 10 ** 9,
'reward_floor': 0,
'reward_ceiling': n_episodes,
})
register_benchmark(
id='BernoulliBandit-v0',
name='BernoulliBandit',
description='Multi-armed Bernoulli bandits',
scorer=scoring.ClipTo01ThenAverage(num_episodes=1000),
tasks=bandit_tasks
)
tabular_mdp_tasks = []
for n_states in [10]:
for n_actions in [5]:
for episode_length in [10]:
for n_episodes in [10, 25, 50, 75, 100]:
tabular_mdp_tasks.append({
'env_id': 'RandomTabularMDP-{s}.states-{a}.actions-{t}.timesteps-{n}.episodes-v0'.format(
s=n_states, a=n_actions, t=episode_length, n=n_episodes,
),
'trials': 1,
'max_timesteps': 10 ** 9,
'reward_floor': 0,
'reward_ceiling': episode_length * n_episodes * 2,
})
register_benchmark(
id='RandomTabularMDP-v0',
name='RandomTabularMDP',
description='Random tabular MDPs',
scorer=scoring.ClipTo01ThenAverage(num_episodes=1000),
tasks=tabular_mdp_tasks
)
| [
2,
7788,
18973,
3955,
3525,
1847,
25,
477,
743,
307,
4615,
2582,
198,
198,
6738,
11550,
13,
26968,
14306,
1330,
9689,
198,
6738,
11550,
13,
26968,
14306,
13,
2301,
33397,
1330,
18335,
62,
16684,
11,
7881,
62,
26968,
4102,
11,
20478,
11,
7881,
62,
26968,
4102,
62,
1177,
220,
1303,
17944,
973,
8057,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
2953,
2743,
2167,
44,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
14957,
48123,
22784,
198,
220,
220,
220,
1438,
11639,
2953,
2743,
2167,
44,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
2953,
2743,
1600,
198,
220,
220,
220,
6764,
11639,
22,
35884,
1830,
11,
351,
17465,
13050,
3256,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
3856,
321,
49,
1304,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
49327,
13,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
718,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
31737,
448,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
352,
13,
22,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
10460,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
12915,
1434,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
23336,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
47,
506,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
532,
1238,
13,
22,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
2310,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
48,
4835,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
26826,
13,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
604,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
37567,
6138,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
8257,
13,
19,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1802,
830,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
14106,
19904,
9972,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
17,
68,
23,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
22613,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
513,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
2953,
2743,
1821,
44,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
14957,
48123,
22784,
198,
220,
220,
220,
1438,
11639,
2953,
2743,
1821,
44,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
2953,
2743,
1600,
198,
220,
220,
220,
6764,
11639,
22,
35884,
1830,
11,
351,
17465,
13050,
3256,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
3856,
321,
49,
1304,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
49327,
13,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
718,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
31737,
448,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
352,
13,
22,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
10460,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
12915,
1434,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
23336,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
47,
506,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
532,
1238,
13,
22,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
2310,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
48,
4835,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
26826,
13,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
604,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
37567,
6138,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
8257,
13,
19,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1802,
830,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
14106,
19904,
9972,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
22613,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
513,
2388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
2953,
2743,
18438,
6944,
1821,
44,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
14957,
48123,
22784,
198,
220,
220,
220,
1438,
11639,
2953,
2743,
18438,
6944,
1821,
44,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
2953,
2743,
1600,
198,
220,
220,
220,
6764,
11639,
22,
35884,
1830,
11,
351,
17465,
13050,
3256,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
20366,
16172,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
657,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
3261,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
38,
4108,
7940,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
29637,
13,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
9069,
660,
89,
7487,
3041,
18674,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
1679,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
33028,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
47,
270,
7207,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
532,
28978,
13,
23,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
29067,
24876,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
718,
5237,
13,
23,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1802,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
38825,
271,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
1160,
2857,
13,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
23336,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
53,
36697,
2949,
35439,
74,
541,
12,
85,
19,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
493,
7,
19,
68,
22,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
1248,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1802,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
33761,
628,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39914,
15988,
17,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39914,
15988,
17,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
15988,
1600,
198,
220,
220,
220,
6764,
11639,
26437,
6833,
1630,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
43476,
47,
2305,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
4751,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
47,
437,
14452,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
8576,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39914,
15988,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39914,
15988,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
15988,
1600,
198,
220,
220,
220,
6764,
11639,
26437,
6833,
1630,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
43476,
47,
2305,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
220,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
5323,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
12832,
305,
13645,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
4059,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
44,
18635,
9914,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
2167,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
532,
3064,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
47,
437,
14452,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
939,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
1415,
405,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
21017,
5231,
519,
877,
515,
416,
256,
24275,
7923,
13,
26968,
4102,
13,
1102,
1851,
62,
26968,
4102,
13,
9078,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
44,
23577,
25634,
940,
44,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
44,
23577,
25634,
940,
44,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
15988,
1600,
198,
220,
220,
220,
6764,
11639,
44,
23577,
25634,
18335,
351,
838,
44,
4831,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
13217,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
28900,
2848,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
20490,
1868,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
20490,
1868,
15480,
929,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39950,
17,
67,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
44,
23577,
25634,
16,
44,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
44,
23577,
25634,
16,
44,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
15988,
1600,
198,
220,
220,
220,
6764,
11639,
44,
23577,
25634,
18335,
351,
352,
44,
4831,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
31305,
7376,
316,
993,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
532,
21033,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
30123,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
28900,
2848,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
1467,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
30123,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
818,
13658,
25628,
47,
437,
14452,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
7192,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
33028,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
818,
13658,
47,
437,
14452,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
642,
13,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
3041,
3493,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
532,
3559,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
532,
15,
13,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
10462,
10957,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
657,
13,
1954,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
5323,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39950,
17,
67,
12,
85,
16,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
513,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1802,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
220,
352,
13,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
642,
4059,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39194,
28406,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39194,
28406,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
39194,
1600,
198,
220,
220,
220,
6764,
11639,
39194,
2562,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
26416,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
10053,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
34294,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
19463,
7414,
265,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
939,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
4059,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
657,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
2898,
17479,
43199,
64,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
5867,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
2579,
405,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
36,
803,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
5867,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
6200,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
5867,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39194,
31205,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39194,
31205,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
39194,
1600,
198,
220,
220,
220,
6764,
11639,
39194,
7090,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
2601,
733,
54,
18998,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
7337,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
3064,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1802,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
42369,
605,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
15897,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
4019,
1821,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
44,
6201,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
10053,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
44,
6201,
17,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
939,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39194,
17309,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39194,
17309,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
39194,
1600,
198,
220,
220,
220,
6764,
11639,
39194,
1327,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
5944,
301,
9928,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
15897,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1160,
1795,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
26437,
41178,
44,
6201,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
15897,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
604,
14198,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
8086,
291,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
10053,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
838,
1821,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
5377,
11141,
414,
28350,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
10053,
830,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39194,
16371,
17309,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39194,
16371,
17309,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
39194,
1600,
198,
220,
220,
220,
6764,
11639,
39194,
845,
1327,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
31205,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1248,
20483,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
49388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
1467,
21033,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
17309,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
1987,
20483,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
49388,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
40660,
1821,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
39194,
26950,
4733,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
39194,
26950,
4733,
3256,
198,
220,
220,
220,
1570,
62,
8094,
2625,
39194,
1600,
198,
220,
220,
220,
6764,
11639,
39194,
5340,
18335,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
22784,
198,
220,
220,
220,
8861,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
24330,
62,
312,
10354,
705,
39194,
19463,
10603,
16,
12,
85,
15,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
718,
10535,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
532,
12825,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
8576,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
33761,
198,
198,
3903,
270,
62,
83,
6791,
796,
17635,
198,
1640,
299,
62,
8357,
287,
685,
20,
11,
838,
11,
2026,
5974,
198,
220,
220,
220,
329,
299,
62,
538,
8052,
287,
685,
940,
11,
1802,
11,
5323,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
4097,
270,
62,
83,
6791,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
23927,
280,
15516,
31407,
270,
12,
90,
74,
27422,
8357,
12,
90,
77,
27422,
538,
8052,
12,
85,
15,
4458,
18982,
7,
74,
28,
77,
62,
8357,
11,
299,
28,
77,
62,
538,
8052,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
838,
12429,
860,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
299,
62,
538,
8052,
11,
198,
220,
220,
220,
220,
220,
220,
220,
32092,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
23927,
280,
15516,
31407,
270,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
23927,
280,
15516,
31407,
270,
3256,
198,
220,
220,
220,
6764,
11639,
29800,
12,
12026,
6206,
280,
15516,
44149,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
7,
22510,
62,
538,
8052,
28,
12825,
828,
198,
220,
220,
220,
8861,
28,
3903,
270,
62,
83,
6791,
198,
8,
198,
198,
8658,
934,
62,
9132,
79,
62,
83,
6791,
796,
17635,
198,
1640,
299,
62,
27219,
287,
685,
940,
5974,
198,
220,
220,
220,
329,
299,
62,
4658,
287,
685,
20,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
329,
4471,
62,
13664,
287,
685,
940,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
299,
62,
538,
8052,
287,
685,
940,
11,
1679,
11,
2026,
11,
5441,
11,
1802,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7400,
934,
62,
9132,
79,
62,
83,
6791,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24330,
62,
312,
10354,
705,
29531,
33349,
934,
44,
6322,
12,
90,
82,
27422,
27219,
12,
90,
64,
27422,
4658,
12,
90,
83,
27422,
16514,
395,
25386,
12,
90,
77,
27422,
538,
8052,
12,
85,
15,
4458,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
28,
77,
62,
27219,
11,
257,
28,
77,
62,
4658,
11,
256,
28,
38668,
62,
13664,
11,
299,
28,
77,
62,
538,
8052,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10612,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
28461,
874,
10354,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9806,
62,
16514,
395,
25386,
10354,
838,
12429,
860,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
28300,
10354,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
260,
904,
62,
344,
4386,
10354,
4471,
62,
13664,
1635,
299,
62,
538,
8052,
1635,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
198,
198,
30238,
62,
26968,
4102,
7,
198,
220,
220,
220,
4686,
11639,
29531,
33349,
934,
44,
6322,
12,
85,
15,
3256,
198,
220,
220,
220,
1438,
11639,
29531,
33349,
934,
44,
6322,
3256,
198,
220,
220,
220,
6764,
11639,
29531,
7400,
934,
337,
6322,
82,
3256,
198,
220,
220,
220,
30664,
28,
46536,
13,
2601,
541,
2514,
486,
6423,
26287,
7,
22510,
62,
538,
8052,
28,
12825,
828,
198,
220,
220,
220,
8861,
28,
8658,
934,
62,
9132,
79,
62,
83,
6791,
198,
8,
198
] | 1.764511 | 7,839 |
#!/usr/bin/env python3
# Copyright 2020 Benjamin Ehret
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# title :data/timeseries/preprocess_audioset.py
# author :be
# contact :behret@ethz.ch
# created :31/03/2020
# version :1.0
# python_version :3.7
"""
Script to structure the audioset dataset, which can then be used via
:class:`data.timeseries.audioset_data.AudiosetData`.
The result of this script is available at
https://www.dropbox.com/s/07dfeeuf5aq4w1h/audioset_data_balanced?dl=0
If you want to recreate or modify this dataset, download the audioset data from
https://research.google.com/audioset/download.html
and extract the tar.gz into the following folder:
``datasets/sequential/audioset/audioset_download``.
Subsequently executing this script will create a pickle file containing the 100
class subset of audioset used in this study.
The dataset is stored in tensorflow files. Since we work with pytorch and there
is no utility to read tensorflow files, we extract the data and safe them as
numpy arrays in a pickle file.
Furthermore the data are preprocessed to fit our continual learning experiments.
The original dataset provides three subsets with different compositions of
samples and classes. Since we only work with a subset of classes and samples,
we load all available data and then filter and structure them according to our
criteria.
We use the same criteria as Kemker et al. Classes and samples are restricted in
the following way:
Classes:
- no restriction according to ontology file (parsed from ontology.json)
- no parent / child relationship (parsed from ontology.json)
- confidence level > 70% (data was copied from website into txt file)
- number of samples: we only take classes that have more samples than
a certain threshold
Samples:
- since samples can have multiple labels, we only use samples which
only belong to one of the classes we use
- we exclude samples that don't have the full length of 10 seconds
The chosen classes and samples are then split into train and test data and
saved to a pickle file.
"""
import numpy as np
import pickle
import tensorflow as tf
import os
import json
from warnings import warn
warn('The script was created for one time usage and has to be adapted when ' +
'reusing it. All paths specified here are absolute.')
# Tensorflow eager mode needs to be enabled for dataset mapping to work!
tf.enable_eager_execution()
# Set paths and parameters
data_dir = '../../datasets/sequential/audioset/'
download_dir = os.path.join(data_dir,'audioset_download')
fpath_conf_data = os.path.join(data_dir, 'confidence_data.csv')
fpath_label_inds = os.path.join(data_dir, 'class_labels_indices.csv')
fpath_ontology = os.path.join(data_dir, 'ontology.json')
target_path = os.path.join(data_dir, 'audioset_data_balanced.pickle')
n_classes = 100
n_sample = 1000
test_frac = 0.20
### Load data by serializing files and applying decode function.
def decode(serialized_example):
"""Decode data from TFRecord files.
Args:
serialized_example: serialized_example as created by
tf.data.TFRecordDataset
Returns:
(tuple): Tuple containing:
- **audio** (numpy.ndarray): Array of shape (10,128) representing one
sample with 10 timesteps and 128 features
- **label** (numpy.ndarray): Array of shape (1,) containing the class
of the corresponding sample
"""
sequence_features = {
'audio_embedding': tf.FixedLenSequenceFeature([], tf.string),
}
context_features = {
'start_time_seconds': tf.FixedLenFeature([], tf.float32),
'labels': tf.VarLenFeature(dtype=tf.int64),
}
context_parsed, sequence_parsed = tf.parse_single_sequence_example(
serialized_example,
sequence_features=sequence_features,
context_features=context_features
)
audio = tf.decode_raw(sequence_parsed['audio_embedding'], tf.uint8)
label = tf.cast(context_parsed['labels'], tf.int64)
return audio, label
# Apply decode function to all dataset entries using map function.
# Take files from all three data sets since we repartition anyway.
fpaths = []
for path, subdirs, files in os.walk(download_dir):
for name in files:
if 'tfrecord' in name:
fpaths.append(os.path.join(path, name))
# Create dataset and decode
dataset = tf.data.TFRecordDataset(fpaths)
dataset = dataset.map(decode)
# Extract data to lists
x = []
y = []
for d in dataset:
x.append(d[0].numpy())
y.append(tf.sparse.to_dense(tf.sparse.reorder(d[1])).numpy())
### Filter classes as described above.
# Parse confidence values
conf_data = {}
with open(fpath_conf_data) as f:
for line in f:
tokens = line.split()
# parse confidence
c = 0
for t in tokens:
if t.find('%') is not -1:
c = int(t[:-1])
# parse class name
n = ''
for t in tokens:
if t.find('%') == -1 and t != '-':
if n == '':
n = t
else:
n = n+' '+t
else:
break
conf_data.update({n:c})
# Parse class numbers from label csv file
l = -1
csv_data = {}
with open(fpath_label_inds) as f:
for line in f:
if l == -1:
l += 1
continue
tokens = line.split('"')
n = tokens[1]
csv_data.update({n:l})
l +=1
# Parse ontology info from json file
with open(fpath_ontology, 'r') as f:
json_data = json.load(f)
# Put all data into a single list.
all_data = []
for j in json_data:
if j['name'] in conf_data.keys():
class_info = {
'name' : j['name'],
'restricted' : j['restrictions'] != [],
'has_child' : j['child_ids'] != [],
'conf' : conf_data[j['name']],
'id' : csv_data[j['name']]
}
all_data.append(class_info)
# Filter classes
classes = []
for c in all_data:
if not c['restricted'] and not c['has_child'] and c['conf'] >= 70:
classes.append(c['id'])
### Filter the samples.
# Find samples that belong to only one of the potential classes.
# We also exclude some samples that don't have data for the full 10 seconds.
# First discard labels that are not in the set of potential classes
y_fil = []
for i in range(len(y)):
y_fil.append( np.intersect1d(y[i],classes))
# Find samples with one label
n_labels = np.asarray([len(y) for y in y_fil])
single_label_idx = np.where(n_labels == 1)[0]
# Find samples that are shorter than 10 seconds (to be excluded)
too_short = np.where(np.asarray([x.shape[0] for x in x]) != 10)[0]
# Construct the set of valid samples
valid_idx = np.setdiff1d(single_label_idx,too_short)
# Count number of valid samples for potential classes
y_single = np.asarray([y_fil[i][0] for i in valid_idx])
num_samples = [len(np.where(y_single == i)[0]) for i in classes]
# Take the n classes with the highest number of samples
n_sample_cutoff = np.sort(num_samples)[-n_classes]
class_idx = np.where(np.asarray(num_samples) >= n_sample_cutoff)[0]
our_classes = [classes[i] for i in class_idx]
### Filter the data again according the the chosen classes
y_fil = []
for i in range(len(y)):
y_fil.append( np.intersect1d(y[i],our_classes))
# Find samples that belong to only one of the potential classes
n_labels = np.asarray([len(y) for y in y_fil])
single_label_idx = np.where(n_labels == 1)[0]
# Find samples that dont are shorter than 10 seconds
too_short = np.where(np.asarray([x.shape[0] for x in x]) != 10)[0]
# Construct the set of valid samples
valid_idx = np.setdiff1d(single_label_idx,too_short)
# Restructure data and relabel the classes to be between 0 and n_classes
y_data = [y_fil[i][0] for i in valid_idx]
y_data = [np.where(np.asarray(our_classes) == i)[0][0] for i in y_data]
y_data = np.asarray(y_data)
x_data = [x[i] for i in valid_idx]
x_data = np.stack(x_data)
### Split into test and train and restrict the number of samples per class
np.random.seed(42)
n_train = int(n_sample * (1-test_frac))
n_test = int(n_sample * test_frac)
train_ind = []
test_ind = []
for i in range(n_classes):
sample_idx = np.where(y_data == i)[0]
n_sample_class = len(sample_idx)
rand_idx = np.arange(n_sample_class)
np.random.shuffle(rand_idx)
train_ind.extend(sample_idx[rand_idx[0:n_train]])
test_ind.extend(sample_idx[rand_idx[n_train:n_sample]])
train_ind = np.asarray(train_ind)
test_ind = np.asarray(test_ind)
sub_sample_idx = np.hstack((train_ind,test_ind))
x_data_sub = x_data[sub_sample_idx,:,:]
y_data_sub = y_data[sub_sample_idx]
train_ind = np.arange(0,len(train_ind))
test_ind = np.arange(len(train_ind),len(train_ind)+len(test_ind))
### Save data
with open(target_path, 'wb') as f:
pickle.dump([x_data_sub, y_data_sub, train_ind, test_ind], f)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
15069,
12131,
14533,
31480,
1186,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
2,
198,
2,
3670,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
7890,
14,
22355,
10640,
14,
3866,
14681,
62,
3885,
4267,
316,
13,
9078,
198,
2,
1772,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
1350,
198,
2,
2800,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
20709,
1186,
31,
2788,
89,
13,
354,
198,
2,
2727,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
3132,
14,
3070,
14,
42334,
198,
2,
2196,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
16,
13,
15,
198,
2,
21015,
62,
9641,
220,
1058,
18,
13,
22,
198,
37811,
198,
7391,
284,
4645,
262,
2709,
4267,
316,
27039,
11,
543,
460,
788,
307,
973,
2884,
198,
25,
4871,
25,
63,
7890,
13,
22355,
10640,
13,
3885,
4267,
316,
62,
7890,
13,
16353,
4267,
316,
6601,
44646,
198,
198,
464,
1255,
286,
428,
4226,
318,
1695,
379,
628,
220,
220,
220,
3740,
1378,
2503,
13,
14781,
3524,
13,
785,
14,
82,
14,
2998,
7568,
1453,
3046,
20,
30188,
19,
86,
16,
71,
14,
3885,
4267,
316,
62,
7890,
62,
27753,
30,
25404,
28,
15,
198,
198,
1532,
345,
765,
284,
32049,
393,
13096,
428,
27039,
11,
4321,
262,
2709,
4267,
316,
1366,
422,
628,
220,
220,
220,
3740,
1378,
34033,
13,
13297,
13,
785,
14,
3885,
4267,
316,
14,
15002,
13,
6494,
198,
198,
392,
7925,
262,
13422,
13,
34586,
656,
262,
1708,
9483,
25,
628,
220,
220,
220,
7559,
19608,
292,
1039,
14,
3107,
1843,
14,
3885,
4267,
316,
14,
3885,
4267,
316,
62,
15002,
15506,
13,
198,
198,
7004,
20415,
23710,
428,
4226,
481,
2251,
257,
2298,
293,
2393,
7268,
262,
1802,
198,
4871,
24637,
286,
2709,
4267,
316,
973,
287,
428,
2050,
13,
220,
198,
198,
464,
27039,
318,
8574,
287,
11192,
273,
11125,
3696,
13,
4619,
356,
670,
351,
12972,
13165,
354,
290,
612,
220,
198,
271,
645,
10361,
284,
1100,
11192,
273,
11125,
3696,
11,
356,
7925,
262,
1366,
290,
3338,
606,
355,
198,
77,
32152,
26515,
287,
257,
2298,
293,
2393,
13,
198,
198,
24951,
262,
1366,
389,
662,
14681,
276,
284,
4197,
674,
37639,
4673,
10256,
13,
198,
464,
2656,
27039,
3769,
1115,
6352,
1039,
351,
1180,
33543,
286,
198,
82,
12629,
290,
6097,
13,
4619,
356,
691,
670,
351,
257,
24637,
286,
6097,
290,
8405,
11,
220,
198,
732,
3440,
477,
1695,
1366,
290,
788,
8106,
290,
4645,
606,
1864,
284,
674,
220,
198,
22213,
5142,
13,
198,
198,
1135,
779,
262,
976,
9987,
355,
24854,
6122,
2123,
435,
13,
38884,
290,
8405,
389,
10770,
287,
198,
1169,
1708,
835,
25,
198,
220,
220,
220,
38884,
25,
198,
220,
220,
220,
220,
220,
220,
220,
532,
645,
17504,
1864,
284,
39585,
1435,
2393,
357,
79,
945,
276,
422,
39585,
1435,
13,
17752,
8,
198,
220,
220,
220,
220,
220,
220,
220,
532,
645,
2560,
1220,
1200,
2776,
357,
79,
945,
276,
422,
39585,
1435,
13,
17752,
8,
198,
220,
220,
220,
220,
220,
220,
220,
532,
6628,
1241,
1875,
4317,
4,
357,
7890,
373,
18984,
422,
3052,
656,
256,
742,
2393,
8,
198,
220,
220,
220,
220,
220,
220,
220,
532,
1271,
286,
8405,
25,
356,
691,
1011,
6097,
326,
423,
517,
8405,
621,
198,
220,
220,
220,
220,
220,
220,
220,
257,
1728,
11387,
198,
220,
220,
220,
3409,
2374,
25,
198,
220,
220,
220,
220,
220,
220,
220,
532,
1201,
8405,
460,
423,
3294,
14722,
11,
356,
691,
779,
8405,
543,
220,
198,
220,
220,
220,
220,
220,
220,
220,
691,
5594,
284,
530,
286,
262,
6097,
356,
779,
198,
220,
220,
220,
220,
220,
220,
220,
532,
356,
19607,
8405,
326,
836,
470,
423,
262,
1336,
4129,
286,
838,
4201,
198,
198,
464,
7147,
6097,
290,
8405,
389,
788,
6626,
656,
4512,
290,
1332,
1366,
290,
220,
198,
82,
9586,
284,
257,
2298,
293,
2393,
13,
198,
37811,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2298,
293,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
28686,
198,
11748,
33918,
198,
6738,
14601,
1330,
9828,
198,
198,
40539,
10786,
464,
4226,
373,
2727,
329,
530,
640,
8748,
290,
468,
284,
307,
16573,
618,
705,
1343,
198,
220,
220,
220,
220,
705,
260,
3500,
340,
13,
1439,
13532,
7368,
994,
389,
4112,
2637,
8,
198,
198,
2,
309,
22854,
11125,
11069,
4235,
2476,
284,
307,
9343,
329,
27039,
16855,
284,
670,
0,
198,
27110,
13,
21633,
62,
68,
3536,
62,
18558,
1009,
3419,
198,
198,
2,
5345,
13532,
290,
10007,
198,
7890,
62,
15908,
796,
705,
40720,
40720,
19608,
292,
1039,
14,
3107,
1843,
14,
3885,
4267,
316,
14,
6,
198,
15002,
62,
15908,
796,
28686,
13,
6978,
13,
22179,
7,
7890,
62,
15908,
4032,
3885,
4267,
316,
62,
15002,
11537,
198,
69,
6978,
62,
10414,
62,
7890,
796,
28686,
13,
6978,
13,
22179,
7,
7890,
62,
15908,
11,
705,
39745,
62,
7890,
13,
40664,
11537,
198,
69,
6978,
62,
18242,
62,
521,
82,
796,
28686,
13,
6978,
13,
22179,
7,
7890,
62,
15908,
11,
705,
4871,
62,
23912,
1424,
62,
521,
1063,
13,
40664,
11537,
198,
69,
6978,
62,
756,
1435,
796,
28686,
13,
6978,
13,
22179,
7,
7890,
62,
15908,
11,
705,
756,
1435,
13,
17752,
11537,
198,
16793,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
7890,
62,
15908,
11,
705,
3885,
4267,
316,
62,
7890,
62,
27753,
13,
27729,
293,
11537,
198,
198,
77,
62,
37724,
796,
1802,
198,
77,
62,
39873,
796,
8576,
198,
9288,
62,
31944,
796,
657,
13,
1238,
628,
198,
21017,
8778,
1366,
416,
11389,
2890,
3696,
290,
11524,
36899,
2163,
13,
198,
4299,
36899,
7,
46911,
1143,
62,
20688,
2599,
198,
220,
220,
220,
37227,
10707,
1098,
1366,
422,
24958,
23739,
3696,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
11389,
1143,
62,
20688,
25,
11389,
1143,
62,
20688,
355,
2727,
416,
220,
198,
220,
220,
220,
220,
220,
220,
220,
48700,
13,
7890,
13,
10234,
23739,
27354,
292,
316,
628,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
357,
83,
29291,
2599,
309,
29291,
7268,
25,
628,
220,
220,
220,
220,
220,
220,
220,
532,
12429,
24051,
1174,
357,
77,
32152,
13,
358,
18747,
2599,
15690,
286,
5485,
357,
940,
11,
12762,
8,
10200,
530,
220,
198,
220,
220,
220,
220,
220,
220,
220,
6291,
351,
838,
4628,
395,
25386,
290,
13108,
3033,
198,
220,
220,
220,
220,
220,
220,
220,
532,
12429,
18242,
1174,
357,
77,
32152,
13,
358,
18747,
2599,
15690,
286,
5485,
357,
16,
35751,
7268,
262,
1398,
220,
198,
220,
220,
220,
220,
220,
220,
220,
286,
262,
11188,
6291,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
8379,
62,
40890,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
24051,
62,
20521,
12083,
10354,
48700,
13,
13715,
30659,
44015,
594,
38816,
26933,
4357,
48700,
13,
8841,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
4732,
62,
40890,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
9688,
62,
2435,
62,
43012,
10354,
48700,
13,
13715,
30659,
38816,
26933,
4357,
48700,
13,
22468,
2624,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
23912,
1424,
10354,
48700,
13,
19852,
30659,
38816,
7,
67,
4906,
28,
27110,
13,
600,
2414,
828,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
4732,
62,
79,
945,
276,
11,
8379,
62,
79,
945,
276,
796,
48700,
13,
29572,
62,
29762,
62,
43167,
62,
20688,
7,
198,
220,
220,
220,
220,
220,
11389,
1143,
62,
20688,
11,
198,
220,
220,
220,
220,
220,
8379,
62,
40890,
28,
43167,
62,
40890,
11,
198,
220,
220,
220,
220,
220,
4732,
62,
40890,
28,
22866,
62,
40890,
198,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
6597,
796,
48700,
13,
12501,
1098,
62,
1831,
7,
43167,
62,
79,
945,
276,
17816,
24051,
62,
20521,
12083,
6,
4357,
48700,
13,
28611,
23,
8,
198,
220,
220,
220,
6167,
796,
48700,
13,
2701,
7,
22866,
62,
79,
945,
276,
17816,
23912,
1424,
6,
4357,
48700,
13,
600,
2414,
8,
628,
220,
220,
220,
1441,
6597,
11,
6167,
198,
198,
2,
27967,
36899,
2163,
284,
477,
27039,
12784,
1262,
3975,
2163,
13,
198,
2,
7214,
3696,
422,
477,
1115,
1366,
5621,
1201,
356,
1128,
433,
653,
6949,
13,
198,
69,
6978,
82,
796,
17635,
198,
1640,
3108,
11,
850,
15908,
82,
11,
3696,
287,
28686,
13,
11152,
7,
15002,
62,
15908,
2599,
198,
220,
220,
220,
329,
1438,
287,
3696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
705,
27110,
22105,
6,
287,
1438,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
6978,
82,
13,
33295,
7,
418,
13,
6978,
13,
22179,
7,
6978,
11,
1438,
4008,
198,
198,
2,
13610,
27039,
290,
36899,
198,
19608,
292,
316,
796,
48700,
13,
7890,
13,
10234,
23739,
27354,
292,
316,
7,
69,
6978,
82,
8,
198,
19608,
292,
316,
796,
27039,
13,
8899,
7,
12501,
1098,
8,
198,
198,
2,
29677,
1366,
284,
8341,
198,
87,
796,
17635,
198,
88,
796,
17635,
198,
1640,
288,
287,
27039,
25,
198,
220,
220,
220,
2124,
13,
33295,
7,
67,
58,
15,
4083,
77,
32152,
28955,
198,
220,
220,
220,
331,
13,
33295,
7,
27110,
13,
82,
29572,
13,
1462,
62,
67,
1072,
7,
27110,
13,
82,
29572,
13,
260,
2875,
7,
67,
58,
16,
12962,
737,
77,
32152,
28955,
628,
198,
21017,
25853,
6097,
355,
3417,
2029,
13,
220,
220,
198,
2,
2547,
325,
6628,
3815,
198,
10414,
62,
7890,
796,
23884,
198,
4480,
1280,
7,
69,
6978,
62,
10414,
62,
7890,
8,
355,
277,
25,
198,
220,
220,
220,
329,
1627,
287,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
16326,
796,
1627,
13,
35312,
3419,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
21136,
6628,
198,
220,
220,
220,
220,
220,
220,
220,
269,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
16326,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
256,
13,
19796,
10786,
4,
11537,
318,
407,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
796,
493,
7,
83,
58,
21912,
16,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
21136,
1398,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
299,
796,
10148,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
16326,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
256,
13,
19796,
10786,
4,
11537,
6624,
532,
16,
290,
256,
14512,
705,
12,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
299,
6624,
10148,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
796,
256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
796,
299,
10,
6,
705,
10,
83,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
1013,
62,
7890,
13,
19119,
15090,
77,
25,
66,
30072,
198,
220,
220,
220,
220,
198,
2,
2547,
325,
1398,
3146,
422,
6167,
269,
21370,
2393,
198,
75,
796,
532,
16,
198,
40664,
62,
7890,
796,
23884,
198,
4480,
1280,
7,
69,
6978,
62,
18242,
62,
521,
82,
8,
355,
277,
25,
198,
220,
220,
220,
329,
1627,
287,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
300,
6624,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
16326,
796,
1627,
13,
35312,
10786,
1,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
299,
796,
16326,
58,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
269,
21370,
62,
7890,
13,
19119,
15090,
77,
25,
75,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
300,
15853,
16,
198,
198,
2,
2547,
325,
39585,
1435,
7508,
422,
33918,
2393,
198,
4480,
1280,
7,
69,
6978,
62,
756,
1435,
11,
705,
81,
11537,
355,
277,
25,
198,
220,
220,
220,
33918,
62,
7890,
796,
33918,
13,
2220,
7,
69,
8,
198,
220,
220,
220,
220,
198,
2,
5930,
477,
1366,
656,
257,
2060,
1351,
13,
198,
439,
62,
7890,
796,
17635,
220,
220,
220,
220,
198,
1640,
474,
287,
33918,
62,
7890,
25,
198,
220,
220,
220,
611,
474,
17816,
3672,
20520,
287,
1013,
62,
7890,
13,
13083,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
62,
10951,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
3672,
6,
1058,
474,
17816,
3672,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
49343,
6,
1058,
474,
17816,
2118,
2012,
507,
20520,
14512,
685,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
10134,
62,
9410,
6,
1058,
474,
17816,
9410,
62,
2340,
20520,
14512,
685,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
10414,
6,
1058,
1013,
62,
7890,
58,
73,
17816,
3672,
20520,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
312,
6,
1058,
269,
21370,
62,
7890,
58,
73,
17816,
3672,
6,
11907,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
477,
62,
7890,
13,
33295,
7,
4871,
62,
10951,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
2,
25853,
6097,
198,
37724,
796,
17635,
198,
1640,
269,
287,
477,
62,
7890,
25,
198,
220,
220,
220,
611,
407,
269,
17816,
49343,
20520,
290,
407,
269,
17816,
10134,
62,
9410,
20520,
290,
269,
17816,
10414,
20520,
18189,
4317,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6097,
13,
33295,
7,
66,
17816,
312,
6,
12962,
628,
198,
21017,
25853,
262,
8405,
13,
198,
2,
9938,
8405,
326,
5594,
284,
691,
530,
286,
262,
2785,
6097,
13,
198,
2,
775,
635,
19607,
617,
8405,
326,
836,
470,
423,
1366,
329,
262,
1336,
838,
4201,
13,
198,
2,
3274,
27537,
14722,
326,
389,
407,
287,
262,
900,
286,
2785,
6097,
198,
88,
62,
10379,
796,
17635,
198,
1640,
1312,
287,
2837,
7,
11925,
7,
88,
8,
2599,
198,
220,
220,
220,
331,
62,
10379,
13,
33295,
7,
45941,
13,
3849,
8831,
16,
67,
7,
88,
58,
72,
4357,
37724,
4008,
198,
198,
2,
9938,
8405,
351,
530,
6167,
220,
220,
220,
220,
198,
77,
62,
23912,
1424,
796,
45941,
13,
292,
18747,
26933,
11925,
7,
88,
8,
329,
331,
287,
331,
62,
10379,
12962,
198,
29762,
62,
18242,
62,
312,
87,
796,
45941,
13,
3003,
7,
77,
62,
23912,
1424,
6624,
352,
38381,
15,
60,
198,
198,
2,
9938,
8405,
326,
389,
12238,
621,
838,
4201,
357,
1462,
307,
15009,
8,
198,
18820,
62,
19509,
796,
45941,
13,
3003,
7,
37659,
13,
292,
18747,
26933,
87,
13,
43358,
58,
15,
60,
329,
2124,
287,
2124,
12962,
14512,
838,
38381,
15,
60,
198,
198,
2,
28407,
262,
900,
286,
4938,
8405,
198,
12102,
62,
312,
87,
796,
45941,
13,
2617,
26069,
16,
67,
7,
29762,
62,
18242,
62,
312,
87,
11,
18820,
62,
19509,
8,
198,
198,
2,
2764,
1271,
286,
4938,
8405,
329,
2785,
6097,
198,
88,
62,
29762,
796,
45941,
13,
292,
18747,
26933,
88,
62,
10379,
58,
72,
7131,
15,
60,
329,
1312,
287,
4938,
62,
312,
87,
12962,
198,
22510,
62,
82,
12629,
796,
685,
11925,
7,
37659,
13,
3003,
7,
88,
62,
29762,
6624,
1312,
38381,
15,
12962,
220,
329,
1312,
287,
6097,
60,
198,
198,
2,
7214,
262,
299,
6097,
351,
262,
4511,
1271,
286,
8405,
198,
77,
62,
39873,
62,
8968,
2364,
796,
45941,
13,
30619,
7,
22510,
62,
82,
12629,
38381,
12,
77,
62,
37724,
60,
198,
4871,
62,
312,
87,
796,
45941,
13,
3003,
7,
37659,
13,
292,
18747,
7,
22510,
62,
82,
12629,
8,
18189,
299,
62,
39873,
62,
8968,
2364,
38381,
15,
60,
198,
454,
62,
37724,
796,
685,
37724,
58,
72,
60,
329,
1312,
287,
1398,
62,
312,
87,
60,
628,
198,
21017,
25853,
262,
1366,
757,
1864,
262,
262,
7147,
6097,
198,
88,
62,
10379,
796,
17635,
198,
1640,
1312,
287,
2837,
7,
11925,
7,
88,
8,
2599,
198,
220,
220,
220,
331,
62,
10379,
13,
33295,
7,
45941,
13,
3849,
8831,
16,
67,
7,
88,
58,
72,
4357,
454,
62,
37724,
4008,
198,
198,
2,
9938,
8405,
326,
5594,
284,
691,
530,
286,
262,
2785,
6097,
198,
77,
62,
23912,
1424,
796,
45941,
13,
292,
18747,
26933,
11925,
7,
88,
8,
329,
331,
287,
331,
62,
10379,
12962,
198,
29762,
62,
18242,
62,
312,
87,
796,
45941,
13,
3003,
7,
77,
62,
23912,
1424,
6624,
352,
38381,
15,
60,
198,
198,
2,
9938,
8405,
326,
17666,
389,
12238,
621,
838,
4201,
220,
198,
18820,
62,
19509,
796,
45941,
13,
3003,
7,
37659,
13,
292,
18747,
26933,
87,
13,
43358,
58,
15,
60,
329,
2124,
287,
2124,
12962,
14512,
838,
38381,
15,
60,
198,
198,
2,
28407,
262,
900,
286,
4938,
8405,
198,
12102,
62,
312,
87,
796,
45941,
13,
2617,
26069,
16,
67,
7,
29762,
62,
18242,
62,
312,
87,
11,
18820,
62,
19509,
8,
198,
198,
2,
8324,
5620,
1366,
290,
823,
9608,
262,
6097,
284,
307,
1022,
657,
290,
299,
62,
37724,
198,
88,
62,
7890,
796,
685,
88,
62,
10379,
58,
72,
7131,
15,
60,
329,
1312,
287,
4938,
62,
312,
87,
60,
198,
88,
62,
7890,
796,
685,
37659,
13,
3003,
7,
37659,
13,
292,
18747,
7,
454,
62,
37724,
8,
6624,
1312,
38381,
15,
7131,
15,
60,
329,
1312,
287,
331,
62,
7890,
60,
198,
88,
62,
7890,
796,
45941,
13,
292,
18747,
7,
88,
62,
7890,
8,
198,
198,
87,
62,
7890,
796,
685,
87,
58,
72,
60,
329,
1312,
287,
4938,
62,
312,
87,
60,
198,
87,
62,
7890,
796,
45941,
13,
25558,
7,
87,
62,
7890,
8,
628,
198,
21017,
27758,
656,
1332,
290,
4512,
290,
4239,
262,
1271,
286,
8405,
583,
1398,
198,
37659,
13,
25120,
13,
28826,
7,
3682,
8,
198,
77,
62,
27432,
796,
493,
7,
77,
62,
39873,
1635,
357,
16,
12,
9288,
62,
31944,
4008,
198,
77,
62,
9288,
796,
493,
7,
77,
62,
39873,
1635,
1332,
62,
31944,
8,
198,
198,
27432,
62,
521,
796,
17635,
198,
9288,
62,
521,
796,
17635,
198,
198,
1640,
1312,
287,
2837,
7,
77,
62,
37724,
2599,
198,
220,
220,
220,
6291,
62,
312,
87,
796,
45941,
13,
3003,
7,
88,
62,
7890,
6624,
1312,
38381,
15,
60,
198,
220,
220,
220,
299,
62,
39873,
62,
4871,
796,
18896,
7,
39873,
62,
312,
87,
8,
198,
220,
220,
220,
43720,
62,
312,
87,
796,
45941,
13,
283,
858,
7,
77,
62,
39873,
62,
4871,
8,
198,
220,
220,
220,
45941,
13,
25120,
13,
1477,
18137,
7,
25192,
62,
312,
87,
8,
198,
220,
220,
220,
4512,
62,
521,
13,
2302,
437,
7,
39873,
62,
312,
87,
58,
25192,
62,
312,
87,
58,
15,
25,
77,
62,
27432,
11907,
8,
198,
220,
220,
220,
1332,
62,
521,
13,
2302,
437,
7,
39873,
62,
312,
87,
58,
25192,
62,
312,
87,
58,
77,
62,
27432,
25,
77,
62,
39873,
11907,
8,
198,
198,
27432,
62,
521,
796,
45941,
13,
292,
18747,
7,
27432,
62,
521,
8,
198,
9288,
62,
521,
796,
45941,
13,
292,
18747,
7,
9288,
62,
521,
8,
198,
198,
7266,
62,
39873,
62,
312,
87,
796,
45941,
13,
71,
25558,
19510,
27432,
62,
521,
11,
9288,
62,
521,
4008,
198,
87,
62,
7890,
62,
7266,
796,
2124,
62,
7890,
58,
7266,
62,
39873,
62,
312,
87,
11,
45299,
47715,
198,
88,
62,
7890,
62,
7266,
796,
331,
62,
7890,
58,
7266,
62,
39873,
62,
312,
87,
60,
198,
27432,
62,
521,
796,
45941,
13,
283,
858,
7,
15,
11,
11925,
7,
27432,
62,
521,
4008,
198,
9288,
62,
521,
796,
45941,
13,
283,
858,
7,
11925,
7,
27432,
62,
521,
828,
11925,
7,
27432,
62,
521,
47762,
11925,
7,
9288,
62,
521,
4008,
628,
198,
21017,
12793,
1366,
198,
4480,
1280,
7,
16793,
62,
6978,
11,
705,
39346,
11537,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2298,
293,
13,
39455,
26933,
87,
62,
7890,
62,
7266,
11,
331,
62,
7890,
62,
7266,
11,
4512,
62,
521,
11,
1332,
62,
521,
4357,
277,
8,
198
] | 2.600327 | 3,668 |
from django.conf import settings
from django.core import serializers
from django.utils import timezone
import requests
from Posts.commentModel import Comments
#from Posts.commentView import add_Comment
from rest_framework import status
from rest_framework.decorators import api_view, authentication_classes, permission_classes
from rest_framework.response import Response
from django.shortcuts import HttpResponse, render
from requests import get
from .serializers import CommentSerializer, PostSerializer
from Author.serializers import LikeSerializer
from Author.models import Like
from Author.views import updateForeignAuthors, GetForeignAuthors
from .models import Post, Author
from .form import PostForm
from Posts.commentForm import CommentForm
import json
import uuid
import re
import base64
from django.db.models import Q
import django.core
from permissions import CustomAuthentication, AccessPermission
from django.core.paginator import Paginator
import traceback
| [
6738,
42625,
14208,
13,
10414,
1330,
6460,
198,
6738,
42625,
14208,
13,
7295,
1330,
11389,
11341,
198,
6738,
42625,
14208,
13,
26791,
1330,
640,
11340,
198,
11748,
7007,
198,
6738,
12043,
13,
23893,
17633,
1330,
19502,
198,
2,
6738,
12043,
13,
23893,
7680,
1330,
751,
62,
21357,
198,
6738,
1334,
62,
30604,
1330,
3722,
198,
6738,
1334,
62,
30604,
13,
12501,
273,
2024,
1330,
40391,
62,
1177,
11,
18239,
62,
37724,
11,
7170,
62,
37724,
198,
6738,
1334,
62,
30604,
13,
26209,
1330,
18261,
198,
6738,
42625,
14208,
13,
19509,
23779,
1330,
367,
29281,
31077,
11,
8543,
198,
6738,
7007,
1330,
651,
198,
6738,
764,
46911,
11341,
1330,
18957,
32634,
7509,
11,
2947,
32634,
7509,
198,
6738,
6434,
13,
46911,
11341,
1330,
4525,
32634,
7509,
198,
6738,
6434,
13,
27530,
1330,
4525,
198,
6738,
6434,
13,
33571,
1330,
4296,
33616,
30515,
669,
11,
3497,
33616,
30515,
669,
198,
6738,
764,
27530,
1330,
2947,
11,
6434,
198,
6738,
764,
687,
1330,
2947,
8479,
198,
6738,
12043,
13,
23893,
8479,
1330,
18957,
8479,
198,
11748,
33918,
198,
11748,
334,
27112,
198,
11748,
302,
198,
11748,
2779,
2414,
198,
6738,
42625,
14208,
13,
9945,
13,
27530,
1330,
1195,
198,
11748,
42625,
14208,
13,
7295,
198,
6738,
21627,
1330,
8562,
47649,
3299,
11,
8798,
5990,
3411,
198,
6738,
42625,
14208,
13,
7295,
13,
79,
363,
20900,
1330,
31525,
20900,
198,
11748,
12854,
1891,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
628
] | 4.061728 | 243 |
import pytest
import sys, os
import xarray as xr
import numpy as np
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import process
from process._common import ProcessArgumentInvalid, ProcessArgumentRequired
###################################
# tests:
###################################
def test_with_xarray_out_bounds(execute_array_element_process, generate_data):
"""
Test array_element process with xarray.DataArrays with out of bounds index
"""
with pytest.raises(ProcessArgumentInvalid) as ex:
result = execute_array_element_process(index=5)
assert ex.value.args[0] == "The argument 'index' in process 'array_element' is invalid: Index out of bounds."
| [
11748,
12972,
9288,
198,
11748,
25064,
11,
28686,
198,
11748,
2124,
18747,
355,
2124,
81,
198,
11748,
299,
32152,
355,
45941,
198,
198,
17597,
13,
6978,
13,
33295,
7,
418,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
397,
2777,
776,
7,
834,
7753,
834,
35514,
198,
11748,
1429,
198,
6738,
1429,
13557,
11321,
1330,
10854,
28100,
1713,
44651,
11,
10854,
28100,
1713,
37374,
628,
628,
198,
29113,
21017,
198,
2,
5254,
25,
198,
29113,
21017,
628,
198,
198,
4299,
1332,
62,
4480,
62,
87,
18747,
62,
448,
62,
65,
3733,
7,
41049,
62,
18747,
62,
30854,
62,
14681,
11,
7716,
62,
7890,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
6208,
7177,
62,
30854,
1429,
351,
2124,
18747,
13,
6601,
3163,
20477,
351,
503,
286,
22303,
6376,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
351,
12972,
9288,
13,
430,
2696,
7,
18709,
28100,
1713,
44651,
8,
355,
409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
12260,
62,
18747,
62,
30854,
62,
14681,
7,
9630,
28,
20,
8,
198,
220,
220,
220,
6818,
409,
13,
8367,
13,
22046,
58,
15,
60,
6624,
366,
464,
4578,
705,
9630,
6,
287,
1429,
705,
18747,
62,
30854,
6,
318,
12515,
25,
12901,
503,
286,
22303,
526,
628
] | 3.235556 | 225 |
#!/usr/bin/env python
#
# Copyright 2016 Google Inc.
#
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
# Generate Android.bp for Skia from GN configuration.
import json
import os
import pprint
import string
import subprocess
import tempfile
import gn_to_bp_utils
# First we start off with a template for Android.bp,
# with holes for source lists and include directories.
bp = string.Template('''// This file is autogenerated by gn_to_bp.py.
cc_library_static {
name: "libskia",
cflags: [
$cflags
],
cppflags:[
$cflags_cc
],
export_include_dirs: [
$export_includes
],
local_include_dirs: [
$local_includes
],
srcs: [
$srcs
],
arch: {
arm: {
srcs: [
$arm_srcs
],
neon: {
srcs: [
$arm_neon_srcs
],
},
},
arm64: {
srcs: [
$arm64_srcs
],
},
mips: {
srcs: [
$none_srcs
],
},
mips64: {
srcs: [
$none_srcs
],
},
x86: {
srcs: [
$x86_srcs
],
cflags: [
// Clang seems to think new/malloc will only be 4-byte aligned
// on x86 Android. We're pretty sure it's actually 8-byte
// alignment. tests/OverAlignedTest.cpp has more information,
// and should fail if we're wrong.
"-Wno-over-aligned"
],
},
x86_64: {
srcs: [
$x86_srcs
],
},
},
defaults: ["skia_deps",
"skia_pgo",
],
}
// Build libskia with PGO by default.
// Location of PGO profile data is defined in build/soong/cc/pgo.go
// and is separate from skia.
// To turn it off, set ANDROID_PGO_NO_PROFILE_USE environment variable
// or set enable_profile_use property to false.
cc_defaults {
name: "skia_pgo",
pgo: {
instrumentation: true,
profile_file: "hwui/hwui.profdata",
benchmarks: ["hwui", "skia"],
enable_profile_use: true,
},
}
// "defaults" property to disable profile use for Skia tools and benchmarks.
cc_defaults {
name: "skia_pgo_no_profile_use",
defaults: [
"skia_pgo",
],
pgo: {
enable_profile_use: false,
},
}
cc_defaults {
name: "skia_deps",
shared_libs: [
"libEGL",
"libGLESv2",
"libdng_sdk",
"libexpat",
"libft2",
"libheif",
"libicui18n",
"libicuuc",
"libjpeg",
"liblog",
"libpiex",
"libpng",
"libvulkan",
"libz",
"libcutils",
"libnativewindow",
],
static_libs: [
"libarect",
"libsfntly",
"libwebp-decode",
"libwebp-encode",
],
group_static_libs: true,
}
cc_defaults {
name: "skia_tool_deps",
defaults: [
"skia_deps",
"skia_pgo_no_profile_use"
],
static_libs: [
"libjsoncpp",
"libskia",
],
cflags: [
"-Wno-unused-parameter",
"-Wno-unused-variable",
],
}
cc_test {
name: "skia_dm",
defaults: [
"skia_tool_deps"
],
local_include_dirs: [
$dm_includes
],
srcs: [
$dm_srcs
],
shared_libs: [
"libbinder",
"libutils",
],
}
cc_test {
name: "skia_nanobench",
defaults: [
"skia_tool_deps"
],
local_include_dirs: [
$nanobench_includes
],
srcs: [
$nanobench_srcs
],
data: [
"resources/*",
],
}''')
# We'll run GN to get the main source lists and include directories for Skia.
gn_args = {
'is_official_build': 'true',
'skia_enable_tools': 'true',
'skia_enable_skottie': 'false', # requires rapidjson third-party
'skia_use_libheif': 'true',
'skia_use_vulkan': 'true',
'target_cpu': '"none"',
'target_os': '"android"',
'skia_vulkan_header': '"Skia_Vulkan_Android.h"',
}
js = gn_to_bp_utils.GenerateJSONFromGN(gn_args)
srcs = strip_slashes(js['targets']['//:skia']['sources'])
cflags = strip_slashes(js['targets']['//:skia']['cflags'])
cflags_cc = strip_slashes(js['targets']['//:skia']['cflags_cc'])
local_includes = strip_slashes(js['targets']['//:skia']['include_dirs'])
export_includes = strip_slashes(js['targets']['//:public']['include_dirs'])
defines = [str(d) for d in js['targets']['//:skia']['defines']]
dm_srcs = strip_slashes(js['targets']['//:dm']['sources'])
dm_includes = strip_slashes(js['targets']['//:dm']['include_dirs'])
nanobench_target = js['targets']['//:nanobench']
nanobench_srcs = strip_slashes(nanobench_target['sources'])
nanobench_includes = strip_slashes(nanobench_target['include_dirs'])
gn_to_bp_utils.GrabDependentValues(js, '//:skia', 'sources', srcs, None)
gn_to_bp_utils.GrabDependentValues(js, '//:dm', 'sources', dm_srcs, 'skia')
gn_to_bp_utils.GrabDependentValues(js, '//:nanobench', 'sources',
nanobench_srcs, 'skia')
# skcms is a little special, kind of a second-party library.
srcs .add("third_party/skcms/skcms.c")
local_includes.add("third_party/skcms")
dm_includes .add("third_party/skcms")
# No need to list headers.
srcs = {s for s in srcs if not s.endswith('.h')}
dm_srcs = {s for s in dm_srcs if not s.endswith('.h')}
nanobench_srcs = {s for s in nanobench_srcs if not s.endswith('.h')}
cflags = gn_to_bp_utils.CleanupCFlags(cflags)
cflags_cc = gn_to_bp_utils.CleanupCCFlags(cflags_cc)
# We need to add the include path to the vulkan defines and header file set in
# then skia_vulkan_header gn arg that is used for framework builds.
local_includes.add("platform_tools/android/vulkan")
export_includes.add("platform_tools/android/vulkan")
here = os.path.dirname(__file__)
defs = gn_to_bp_utils.GetArchSources(os.path.join(here, 'opts.gni'))
gn_to_bp_utils.WriteUserConfig('include/config/SkUserConfig.h', defines)
# Turn a list of strings into the style bpfmt outputs.
# OK! We have everything to fill in Android.bp...
with open('Android.bp', 'w') as f:
print >>f, bp.substitute({
'export_includes': bpfmt(8, export_includes),
'local_includes': bpfmt(8, local_includes),
'srcs': bpfmt(8, srcs),
'cflags': bpfmt(8, cflags, False),
'cflags_cc': bpfmt(8, cflags_cc),
'arm_srcs': bpfmt(16, defs['armv7']),
'arm_neon_srcs': bpfmt(20, defs['neon']),
'arm64_srcs': bpfmt(16, defs['arm64'] +
defs['crc32']),
'none_srcs': bpfmt(16, defs['none']),
'x86_srcs': bpfmt(16, defs['sse2'] +
defs['ssse3'] +
defs['sse41'] +
defs['sse42'] +
defs['avx' ] +
defs['hsw' ]),
'dm_includes' : bpfmt(8, dm_includes),
'dm_srcs' : bpfmt(8, dm_srcs),
'nanobench_includes' : bpfmt(8, nanobench_includes),
'nanobench_srcs' : bpfmt(8, nanobench_srcs),
})
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
198,
2,
15069,
1584,
3012,
3457,
13,
198,
2,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
257,
347,
10305,
12,
7635,
5964,
326,
460,
307,
198,
2,
1043,
287,
262,
38559,
24290,
2393,
13,
198,
198,
2,
2980,
378,
5565,
13,
46583,
329,
3661,
544,
422,
15484,
8398,
13,
198,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
279,
4798,
198,
11748,
4731,
198,
11748,
850,
14681,
198,
11748,
20218,
7753,
198,
198,
11748,
19967,
62,
1462,
62,
46583,
62,
26791,
198,
198,
2,
3274,
356,
923,
572,
351,
257,
11055,
329,
5565,
13,
46583,
11,
198,
2,
351,
10421,
329,
2723,
8341,
290,
2291,
29196,
13,
198,
46583,
796,
4731,
13,
30800,
7,
7061,
6,
1003,
770,
2393,
318,
1960,
519,
877,
515,
416,
19967,
62,
1462,
62,
46583,
13,
9078,
13,
198,
198,
535,
62,
32016,
62,
12708,
1391,
198,
220,
220,
220,
1438,
25,
366,
8019,
8135,
544,
1600,
198,
220,
220,
220,
269,
33152,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
66,
33152,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
269,
381,
33152,
33250,
198,
220,
220,
220,
220,
220,
220,
220,
720,
66,
33152,
62,
535,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
10784,
62,
17256,
62,
15908,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
39344,
62,
42813,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
1957,
62,
17256,
62,
15908,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
12001,
62,
42813,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
10677,
82,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
3934,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
3211,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
1670,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25988,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
1670,
62,
710,
261,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
628,
220,
220,
220,
220,
220,
220,
220,
3211,
2414,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
1670,
2414,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
628,
220,
220,
220,
220,
220,
220,
220,
285,
2419,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
23108,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
628,
220,
220,
220,
220,
220,
220,
220,
285,
2419,
2414,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
23108,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
628,
220,
220,
220,
220,
220,
220,
220,
2124,
4521,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
87,
4521,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
33152,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3373,
1012,
648,
2331,
284,
892,
649,
14,
76,
32332,
481,
691,
307,
604,
12,
26327,
19874,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3373,
319,
2124,
4521,
5565,
13,
775,
821,
2495,
1654,
340,
338,
1682,
807,
12,
26327,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3373,
19114,
13,
5254,
14,
5886,
2348,
3916,
14402,
13,
20322,
468,
517,
1321,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3373,
290,
815,
2038,
611,
356,
821,
2642,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27444,
54,
3919,
12,
2502,
12,
41634,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
628,
220,
220,
220,
220,
220,
220,
220,
2124,
4521,
62,
2414,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
720,
87,
4521,
62,
10677,
82,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
8964,
628,
220,
220,
220,
26235,
25,
14631,
8135,
544,
62,
10378,
82,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
79,
2188,
1600,
198,
220,
220,
220,
16589,
198,
92,
198,
198,
1003,
10934,
9195,
8135,
544,
351,
350,
11230,
416,
4277,
13,
198,
1003,
13397,
286,
350,
11230,
7034,
1366,
318,
5447,
287,
1382,
14,
568,
506,
14,
535,
14,
79,
2188,
13,
2188,
198,
1003,
290,
318,
4553,
422,
1341,
544,
13,
198,
1003,
1675,
1210,
340,
572,
11,
900,
5357,
13252,
2389,
62,
6968,
46,
62,
15285,
62,
31190,
25664,
62,
19108,
2858,
7885,
198,
1003,
393,
900,
7139,
62,
13317,
62,
1904,
3119,
284,
3991,
13,
198,
535,
62,
12286,
82,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
79,
2188,
1600,
198,
220,
220,
220,
279,
2188,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
8875,
341,
25,
2081,
11,
198,
220,
220,
220,
220,
220,
220,
220,
7034,
62,
7753,
25,
366,
36599,
9019,
14,
36599,
9019,
13,
5577,
7890,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
31747,
25,
14631,
36599,
9019,
1600,
366,
8135,
544,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
7139,
62,
13317,
62,
1904,
25,
2081,
11,
198,
220,
220,
220,
8964,
198,
92,
198,
198,
1003,
366,
12286,
82,
1,
3119,
284,
15560,
7034,
779,
329,
3661,
544,
4899,
290,
31747,
13,
198,
535,
62,
12286,
82,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
79,
2188,
62,
3919,
62,
13317,
62,
1904,
1600,
198,
220,
220,
220,
26235,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
79,
2188,
1600,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
279,
2188,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
7139,
62,
13317,
62,
1904,
25,
3991,
11,
198,
220,
220,
220,
8964,
198,
92,
198,
198,
535,
62,
12286,
82,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
10378,
82,
1600,
198,
220,
220,
220,
4888,
62,
8019,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
7156,
43,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
8763,
1546,
85,
17,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
67,
782,
62,
21282,
74,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
1069,
8071,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
701,
17,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
258,
361,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
291,
9019,
1507,
77,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
291,
84,
1229,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
73,
22071,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
6404,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
21749,
87,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
11134,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
85,
31263,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
89,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
8968,
4487,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
30191,
17497,
1600,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
9037,
62,
8019,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
533,
310,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
28202,
429,
306,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
12384,
79,
12,
12501,
1098,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
12384,
79,
12,
268,
8189,
1600,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
1448,
62,
12708,
62,
8019,
82,
25,
2081,
11,
198,
92,
198,
198,
535,
62,
12286,
82,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
25981,
62,
10378,
82,
1600,
198,
220,
220,
220,
26235,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
10378,
82,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
79,
2188,
62,
3919,
62,
13317,
62,
1904,
1,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
9037,
62,
8019,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
17752,
20322,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
8135,
544,
1600,
198,
220,
220,
220,
16589,
198,
220,
220,
220,
269,
33152,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
27444,
54,
3919,
12,
403,
1484,
12,
17143,
2357,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
27444,
54,
3919,
12,
403,
1484,
12,
45286,
1600,
198,
220,
220,
220,
16589,
198,
92,
198,
198,
535,
62,
9288,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
36020,
1600,
628,
220,
220,
220,
26235,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
25981,
62,
10378,
82,
1,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
1957,
62,
17256,
62,
15908,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
36020,
62,
42813,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
36020,
62,
10677,
82,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
4888,
62,
8019,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
65,
5540,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8019,
26791,
1600,
198,
220,
220,
220,
16589,
198,
92,
198,
198,
535,
62,
9288,
1391,
198,
220,
220,
220,
1438,
25,
366,
8135,
544,
62,
12647,
672,
24421,
1600,
628,
220,
220,
220,
26235,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8135,
544,
62,
25981,
62,
10378,
82,
1,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
1957,
62,
17256,
62,
15908,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
12647,
672,
24421,
62,
42813,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
12351,
82,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
720,
12647,
672,
24421,
62,
10677,
82,
198,
220,
220,
220,
16589,
628,
220,
220,
220,
1366,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
37540,
15211,
1600,
198,
220,
220,
220,
16589,
198,
92,
7061,
11537,
198,
198,
2,
775,
1183,
1057,
15484,
284,
651,
262,
1388,
2723,
8341,
290,
2291,
29196,
329,
3661,
544,
13,
198,
4593,
62,
22046,
796,
1391,
198,
220,
705,
271,
62,
16841,
62,
11249,
10354,
220,
220,
705,
7942,
3256,
198,
220,
705,
8135,
544,
62,
21633,
62,
31391,
10354,
220,
220,
705,
7942,
3256,
198,
220,
705,
8135,
544,
62,
21633,
62,
8135,
1252,
494,
10354,
705,
9562,
3256,
1303,
4433,
5801,
17752,
2368,
12,
10608,
198,
220,
705,
8135,
544,
62,
1904,
62,
8019,
258,
361,
10354,
220,
220,
220,
705,
7942,
3256,
198,
220,
705,
8135,
544,
62,
1904,
62,
85,
31263,
10354,
220,
220,
220,
220,
705,
7942,
3256,
198,
220,
705,
16793,
62,
36166,
10354,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
1,
23108,
1,
3256,
198,
220,
705,
16793,
62,
418,
10354,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
1,
19411,
1,
3256,
198,
220,
705,
8135,
544,
62,
85,
31263,
62,
25677,
10354,
220,
705,
1,
15739,
544,
62,
53,
31263,
62,
25934,
13,
71,
1,
3256,
198,
92,
198,
198,
8457,
796,
19967,
62,
1462,
62,
46583,
62,
26791,
13,
8645,
378,
40386,
4863,
16630,
7,
4593,
62,
22046,
8,
198,
198,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
8135,
544,
6,
7131,
6,
82,
2203,
6,
12962,
198,
66,
33152,
220,
220,
220,
220,
220,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
8135,
544,
6,
7131,
6,
66,
33152,
6,
12962,
198,
66,
33152,
62,
535,
220,
220,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
8135,
544,
6,
7131,
6,
66,
33152,
62,
535,
6,
12962,
198,
12001,
62,
42813,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
8135,
544,
6,
7131,
6,
17256,
62,
15908,
82,
6,
12962,
198,
39344,
62,
42813,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
11377,
6,
7131,
6,
17256,
62,
15908,
82,
6,
12962,
198,
4299,
1127,
220,
220,
220,
220,
220,
796,
685,
2536,
7,
67,
8,
329,
288,
287,
44804,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
8135,
544,
6,
7131,
6,
4299,
1127,
6,
11907,
198,
198,
36020,
62,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
36020,
6,
7131,
6,
82,
2203,
6,
12962,
198,
36020,
62,
42813,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
8457,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
36020,
6,
7131,
6,
17256,
62,
15908,
82,
6,
12962,
198,
198,
12647,
672,
24421,
62,
16793,
796,
44804,
17816,
83,
853,
1039,
6,
7131,
6,
1003,
25,
12647,
672,
24421,
20520,
198,
12647,
672,
24421,
62,
10677,
82,
220,
220,
220,
220,
796,
10283,
62,
6649,
7465,
7,
12647,
672,
24421,
62,
16793,
17816,
82,
2203,
6,
12962,
198,
12647,
672,
24421,
62,
42813,
796,
10283,
62,
6649,
7465,
7,
12647,
672,
24421,
62,
16793,
17816,
17256,
62,
15908,
82,
6,
12962,
198,
198,
4593,
62,
1462,
62,
46583,
62,
26791,
13,
48400,
35,
8682,
40161,
7,
8457,
11,
705,
1003,
25,
8135,
544,
3256,
705,
82,
2203,
3256,
12351,
82,
11,
6045,
8,
198,
4593,
62,
1462,
62,
46583,
62,
26791,
13,
48400,
35,
8682,
40161,
7,
8457,
11,
705,
1003,
25,
36020,
3256,
705,
82,
2203,
3256,
288,
76,
62,
10677,
82,
11,
705,
8135,
544,
11537,
198,
4593,
62,
1462,
62,
46583,
62,
26791,
13,
48400,
35,
8682,
40161,
7,
8457,
11,
705,
1003,
25,
12647,
672,
24421,
3256,
705,
82,
2203,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15709,
672,
24421,
62,
10677,
82,
11,
705,
8135,
544,
11537,
198,
198,
2,
1341,
46406,
318,
257,
1310,
2041,
11,
1611,
286,
257,
1218,
12,
10608,
5888,
13,
198,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
220,
220,
764,
2860,
7203,
17089,
62,
10608,
14,
8135,
46406,
14,
8135,
46406,
13,
66,
4943,
198,
12001,
62,
42813,
13,
2860,
7203,
17089,
62,
10608,
14,
8135,
46406,
4943,
198,
36020,
62,
42813,
220,
220,
764,
2860,
7203,
17089,
62,
10608,
14,
8135,
46406,
4943,
198,
198,
2,
1400,
761,
284,
1351,
24697,
13,
198,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
796,
1391,
82,
329,
264,
287,
12351,
82,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
264,
13,
437,
2032,
342,
7,
4458,
71,
11537,
92,
198,
36020,
62,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
220,
796,
1391,
82,
329,
264,
287,
288,
76,
62,
10677,
82,
220,
220,
220,
220,
220,
220,
220,
611,
407,
264,
13,
437,
2032,
342,
7,
4458,
71,
11537,
92,
198,
12647,
672,
24421,
62,
10677,
82,
220,
796,
1391,
82,
329,
264,
287,
15709,
672,
24421,
62,
10677,
82,
611,
407,
264,
13,
437,
2032,
342,
7,
4458,
71,
11537,
92,
198,
198,
66,
33152,
796,
19967,
62,
1462,
62,
46583,
62,
26791,
13,
32657,
929,
34,
40053,
7,
66,
33152,
8,
198,
66,
33152,
62,
535,
796,
19967,
62,
1462,
62,
46583,
62,
26791,
13,
32657,
929,
4093,
40053,
7,
66,
33152,
62,
535,
8,
198,
198,
2,
775,
761,
284,
751,
262,
2291,
3108,
284,
262,
410,
31263,
15738,
290,
13639,
2393,
900,
287,
198,
2,
788,
1341,
544,
62,
85,
31263,
62,
25677,
19967,
1822,
326,
318,
973,
329,
9355,
12188,
13,
198,
12001,
62,
42813,
13,
2860,
7203,
24254,
62,
31391,
14,
19411,
14,
85,
31263,
4943,
198,
39344,
62,
42813,
13,
2860,
7203,
24254,
62,
31391,
14,
19411,
14,
85,
31263,
4943,
198,
198,
1456,
796,
28686,
13,
6978,
13,
15908,
3672,
7,
834,
7753,
834,
8,
198,
4299,
82,
796,
19967,
62,
1462,
62,
46583,
62,
26791,
13,
3855,
19895,
21188,
7,
418,
13,
6978,
13,
22179,
7,
1456,
11,
705,
404,
912,
13,
4593,
72,
6,
4008,
198,
198,
4593,
62,
1462,
62,
46583,
62,
26791,
13,
16594,
12982,
16934,
10786,
17256,
14,
11250,
14,
15739,
12982,
16934,
13,
71,
3256,
15738,
8,
198,
198,
2,
6756,
257,
1351,
286,
13042,
656,
262,
3918,
275,
79,
69,
16762,
23862,
13,
198,
198,
2,
7477,
0,
220,
775,
423,
2279,
284,
6070,
287,
5565,
13,
46583,
986,
198,
4480,
1280,
10786,
25934,
13,
46583,
3256,
705,
86,
11537,
355,
277,
25,
198,
220,
3601,
9609,
69,
11,
275,
79,
13,
7266,
301,
3678,
15090,
198,
220,
220,
220,
705,
39344,
62,
42813,
10354,
275,
79,
69,
16762,
7,
23,
11,
10784,
62,
42813,
828,
198,
220,
220,
220,
705,
12001,
62,
42813,
10354,
220,
275,
79,
69,
16762,
7,
23,
11,
1957,
62,
42813,
828,
198,
220,
220,
220,
705,
10677,
82,
10354,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
23,
11,
12351,
82,
828,
198,
220,
220,
220,
705,
66,
33152,
10354,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
23,
11,
269,
33152,
11,
10352,
828,
198,
220,
220,
220,
705,
66,
33152,
62,
535,
10354,
220,
220,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
23,
11,
269,
33152,
62,
535,
828,
628,
220,
220,
220,
705,
1670,
62,
10677,
82,
10354,
220,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
1433,
11,
825,
82,
17816,
1670,
85,
22,
20520,
828,
198,
220,
220,
220,
705,
1670,
62,
710,
261,
62,
10677,
82,
10354,
275,
79,
69,
16762,
7,
1238,
11,
825,
82,
17816,
710,
261,
20520,
828,
198,
220,
220,
220,
705,
1670,
2414,
62,
10677,
82,
10354,
220,
220,
220,
275,
79,
69,
16762,
7,
1433,
11,
825,
82,
17816,
1670,
2414,
20520,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
66,
6015,
2624,
20520,
828,
198,
220,
220,
220,
705,
23108,
62,
10677,
82,
10354,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
1433,
11,
825,
82,
17816,
23108,
20520,
828,
198,
220,
220,
220,
705,
87,
4521,
62,
10677,
82,
10354,
220,
220,
220,
220,
220,
275,
79,
69,
16762,
7,
1433,
11,
825,
82,
17816,
82,
325,
17,
20520,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
824,
325,
18,
20520,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
82,
325,
3901,
20520,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
82,
325,
3682,
20520,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
615,
87,
6,
220,
2361,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
82,
17816,
71,
2032,
6,
220,
2361,
828,
628,
220,
220,
220,
705,
36020,
62,
42813,
6,
220,
220,
220,
220,
220,
220,
1058,
275,
79,
69,
16762,
7,
23,
11,
288,
76,
62,
42813,
828,
198,
220,
220,
220,
705,
36020,
62,
10677,
82,
6,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
275,
79,
69,
16762,
7,
23,
11,
288,
76,
62,
10677,
82,
828,
628,
220,
220,
220,
705,
12647,
672,
24421,
62,
42813,
6,
220,
220,
220,
1058,
275,
79,
69,
16762,
7,
23,
11,
15709,
672,
24421,
62,
42813,
828,
198,
220,
220,
220,
705,
12647,
672,
24421,
62,
10677,
82,
6,
220,
220,
220,
220,
220,
220,
220,
1058,
275,
79,
69,
16762,
7,
23,
11,
15709,
672,
24421,
62,
10677,
82,
828,
198,
220,
32092,
198
] | 1.904896 | 3,901 |
"""The Ray autoscaler uses tags/labels to associate metadata with instances."""
# Tag for the name of the node
TAG_RAY_NODE_NAME = "ray-node-name"
# Tag for the kind of node (e.g. Head, Worker). For legacy reasons, the tag
# value says 'type' instead of 'kind'.
TAG_RAY_NODE_KIND = "ray-node-type"
NODE_KIND_HEAD = "head"
NODE_KIND_WORKER = "worker"
NODE_KIND_UNMANAGED = "unmanaged"
# Tag for user defined node types (e.g., m4xl_spot). This is used for multi
# node type clusters.
TAG_RAY_USER_NODE_TYPE = "ray-user-node-type"
# Tag for autofilled node types for legacy cluster yamls without multi
# node type defined in the cluster configs.
NODE_TYPE_LEGACY_HEAD = "ray-legacy-head-node-type"
NODE_TYPE_LEGACY_WORKER = "ray-legacy-worker-node-type"
# Tag that reports the current state of the node (e.g. Updating, Up-to-date)
TAG_RAY_NODE_STATUS = "ray-node-status"
STATUS_UNINITIALIZED = "uninitialized"
STATUS_WAITING_FOR_SSH = "waiting-for-ssh"
STATUS_SYNCING_FILES = "syncing-files"
STATUS_SETTING_UP = "setting-up"
STATUS_UPDATE_FAILED = "update-failed"
STATUS_UP_TO_DATE = "up-to-date"
# Tag uniquely identifying all nodes of a cluster
TAG_RAY_CLUSTER_NAME = "ray-cluster-name"
# Hash of the node launch config, used to identify out-of-date nodes
TAG_RAY_LAUNCH_CONFIG = "ray-launch-config"
# Hash of the node runtime config, used to determine if updates are needed
TAG_RAY_RUNTIME_CONFIG = "ray-runtime-config"
# Hash of the contents of the directories specified by the file_mounts config
# if the node is a worker, this also hashes content of the directories
# specified by the cluster_synced_files config
TAG_RAY_FILE_MOUNTS_CONTENTS = "ray-file-mounts-contents"
| [
37811,
464,
7760,
44619,
9948,
263,
3544,
15940,
14,
23912,
1424,
284,
11602,
20150,
351,
10245,
526,
15931,
198,
198,
2,
17467,
329,
262,
1438,
286,
262,
10139,
198,
42197,
62,
30631,
62,
45,
16820,
62,
20608,
796,
366,
2433,
12,
17440,
12,
3672,
1,
198,
198,
2,
17467,
329,
262,
1611,
286,
10139,
357,
68,
13,
70,
13,
7123,
11,
35412,
737,
1114,
10655,
3840,
11,
262,
7621,
198,
2,
1988,
1139,
705,
4906,
6,
2427,
286,
705,
11031,
4458,
198,
42197,
62,
30631,
62,
45,
16820,
62,
42,
12115,
796,
366,
2433,
12,
17440,
12,
4906,
1,
198,
45,
16820,
62,
42,
12115,
62,
37682,
796,
366,
2256,
1,
198,
45,
16820,
62,
42,
12115,
62,
33249,
1137,
796,
366,
28816,
1,
198,
45,
16820,
62,
42,
12115,
62,
4944,
10725,
4760,
1961,
796,
366,
403,
39935,
1,
198,
198,
2,
17467,
329,
2836,
5447,
10139,
3858,
357,
68,
13,
70,
1539,
285,
19,
87,
75,
62,
20485,
737,
770,
318,
973,
329,
5021,
198,
2,
10139,
2099,
23163,
13,
198,
42197,
62,
30631,
62,
29904,
62,
45,
16820,
62,
25216,
796,
366,
2433,
12,
7220,
12,
17440,
12,
4906,
1,
198,
2,
17467,
329,
1960,
1659,
2967,
10139,
3858,
329,
10655,
13946,
331,
321,
7278,
1231,
5021,
198,
2,
10139,
2099,
5447,
287,
262,
13946,
4566,
82,
13,
198,
45,
16820,
62,
25216,
62,
2538,
38,
43300,
62,
37682,
796,
366,
2433,
12,
1455,
1590,
12,
2256,
12,
17440,
12,
4906,
1,
198,
45,
16820,
62,
25216,
62,
2538,
38,
43300,
62,
33249,
1137,
796,
366,
2433,
12,
1455,
1590,
12,
28816,
12,
17440,
12,
4906,
1,
198,
198,
2,
17467,
326,
3136,
262,
1459,
1181,
286,
262,
10139,
357,
68,
13,
70,
13,
3205,
38734,
11,
3205,
12,
1462,
12,
4475,
8,
198,
42197,
62,
30631,
62,
45,
16820,
62,
35744,
2937,
796,
366,
2433,
12,
17440,
12,
13376,
1,
198,
35744,
2937,
62,
4944,
1268,
2043,
12576,
14887,
1961,
796,
366,
403,
17532,
1,
198,
35744,
2937,
62,
15543,
2043,
2751,
62,
13775,
62,
5432,
39,
796,
366,
10247,
1780,
12,
1640,
12,
45824,
1,
198,
35744,
2937,
62,
23060,
7792,
2751,
62,
46700,
1546,
796,
366,
28869,
2259,
12,
16624,
1,
198,
35744,
2937,
62,
28480,
48996,
62,
8577,
796,
366,
33990,
12,
929,
1,
198,
35744,
2937,
62,
16977,
62,
7708,
4146,
1961,
796,
366,
19119,
12,
47904,
1,
198,
35744,
2937,
62,
8577,
62,
10468,
62,
35,
6158,
796,
366,
929,
12,
1462,
12,
4475,
1,
198,
198,
2,
17467,
24139,
13720,
477,
13760,
286,
257,
13946,
198,
42197,
62,
30631,
62,
5097,
7759,
1137,
62,
20608,
796,
366,
2433,
12,
565,
5819,
12,
3672,
1,
198,
198,
2,
21059,
286,
262,
10139,
4219,
4566,
11,
973,
284,
5911,
503,
12,
1659,
12,
4475,
13760,
198,
42197,
62,
30631,
62,
13534,
47461,
62,
10943,
16254,
796,
366,
2433,
12,
35681,
12,
11250,
1,
198,
198,
2,
21059,
286,
262,
10139,
19124,
4566,
11,
973,
284,
5004,
611,
5992,
389,
2622,
198,
42197,
62,
30631,
62,
49,
4944,
34694,
62,
10943,
16254,
796,
366,
2433,
12,
43282,
12,
11250,
1,
198,
2,
21059,
286,
262,
10154,
286,
262,
29196,
7368,
416,
262,
2393,
62,
14948,
82,
4566,
198,
2,
611,
262,
10139,
318,
257,
8383,
11,
428,
635,
46621,
2695,
286,
262,
29196,
198,
2,
7368,
416,
262,
13946,
62,
28869,
771,
62,
16624,
4566,
198,
42197,
62,
30631,
62,
25664,
62,
44,
19385,
4694,
62,
37815,
15365,
796,
366,
2433,
12,
7753,
12,
14948,
82,
12,
3642,
658,
1,
198
] | 2.858844 | 588 |
import unittest
from worldengine.plates import Step, center_land, world_gen
from worldengine.world import World
from tests.draw_test import TestBase
if __name__ == '__main__':
unittest.main()
| [
11748,
555,
715,
395,
198,
6738,
995,
18392,
13,
17041,
1330,
5012,
11,
3641,
62,
1044,
11,
995,
62,
5235,
198,
6738,
995,
18392,
13,
6894,
1330,
2159,
198,
198,
6738,
5254,
13,
19334,
62,
9288,
1330,
6208,
14881,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 3.174603 | 63 |
import pytest
import torch
from mmedit.models.builder import build_component
from mmedit.models.components.discriminators.light_cnn import MaxFeature
| [
11748,
12972,
9288,
198,
11748,
28034,
198,
198,
6738,
285,
1150,
270,
13,
27530,
13,
38272,
1330,
1382,
62,
42895,
198,
6738,
285,
1150,
270,
13,
27530,
13,
5589,
3906,
13,
15410,
3036,
47721,
13,
2971,
62,
66,
20471,
1330,
5436,
38816,
628,
198
] | 3.477273 | 44 |
import json
import logging
from typing import Iterable
from kafka import KafkaConsumer
log = logging.getLogger(__name__)
log.addHandler(logging.NullHandler())
# I've used this example:
# https://github.com/aiven/aiven-examples/blob/master/kafka/python/consumer_example.py
# as well as Aiven Kafka tutorials
| [
11748,
33918,
198,
11748,
18931,
198,
198,
6738,
19720,
1330,
40806,
540,
198,
198,
6738,
479,
1878,
4914,
1330,
46906,
49106,
628,
198,
6404,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
198,
6404,
13,
2860,
25060,
7,
6404,
2667,
13,
35067,
25060,
28955,
198,
198,
2,
314,
1053,
973,
428,
1672,
25,
198,
2,
3740,
1378,
12567,
13,
785,
14,
64,
1469,
14,
64,
1469,
12,
1069,
12629,
14,
2436,
672,
14,
9866,
14,
74,
1878,
4914,
14,
29412,
14,
49827,
62,
20688,
13,
9078,
198,
2,
355,
880,
355,
317,
1469,
46906,
27992,
628
] | 3.161616 | 99 |
from tensorflow.keras import *
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers, Sequential,regularizers
from tensorflow.keras.layers import Dropout
# from tensorflow.keras import *
# 3x3kernel_initializer='he_normal','glorot_normal'
from tensorflow.python.keras.layers import Concatenate
############################### ###############################
############################### ###############################
######################################
def build_resblock(self, filter_num, blocks, stride=1):
res_blocks = Sequential()
# may down sample
res_blocks.add(BasicBlock(filter_num, stride))
for _ in range(1, blocks):
res_blocks.add(BasicBlock(filter_num, stride=1))
return res_blocks
######################################
########################### pp2 ########################################
def network_up(input_layer_up,filters_num,dropout_rate,Block_res):
# input_layer = Input(input_shape)
# conv1 = layers.Conv3D(filters_num[0], kernel_size=(3, 3, 7), padding='same')(input_layer) # filters_num = 8
# conv1 = layers.Conv3D(filters_num[0], kernel_size=(3, 3, 3),padding='same',kernel_initializer='he_normal',kernel_regularizer=regularizers.l2(0.0001))(input_layer_up) # filters_num = 8
conv1 = layers.Conv3D(filters_num[0], kernel_size=(3, 3, 3), padding='same',
kernel_regularizer=regularizers.l2(0.0001))(input_layer_up) #kernel_initializer='he_normal',
# conv_layer1m = tf.keras.layers.MaxPooling3D(pool_size=(1, 1, 1),padding='same')(conv1)
# conv_layer1g = tf.keras.layers.GlobalMaxPooling3D()(conv1)
conv1_bn = layers.BatchNormalization()(conv1)
conv1_relu = layers.Activation('relu')(conv1_bn)
# conv1_relu = Dropout(0.5)(conv1_relu)
# conv1_relu = tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2), strides=(1, 1, 1), padding='same')(conv1_relu)
# conv2 = layers.Conv3D(filters_num[1], kernel_size=(3, 3, 5), padding='same')(conv1_relu) # filters_num = 16
conv2 = layers.Conv3D(filters_num[1], kernel_size=(3, 3, 3),padding='same',kernel_regularizer=regularizers.l2(0.0001))(conv1_relu) # filters_num = 16
conv2_bn = layers.BatchNormalization()(conv2)
conv2_relu = layers.Activation('relu')(conv2_bn)
# conv2_relu = Dropout(0.5)(conv2_relu)
# conv2_relu = tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2), strides=(1, 1, 1), padding='same')(conv2_relu)
conv3 = layers.Conv3D(filters_num[2], kernel_size=(3, 3, 3),padding='same',kernel_regularizer=regularizers.l2(0.0001))(conv2_relu) # filters_num = 32
conv3_bn = layers.BatchNormalization()(conv3)
conv3_relu = layers.Activation('relu')(conv3_bn)
# conv3_relu = Dropout(0.5)(conv3_relu)
# conv3_relu = tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2), strides=(1, 1, 1), padding='same')(conv3_relu)
conv3_relu_reshape = layers.Reshape((conv3_relu.shape[1],conv3_relu.shape[2],conv3_relu.shape[3]*conv3_relu.shape[4]))(conv3_relu)
conv3_relu_reshape = Dropout(0.5)(conv3_relu_reshape)
###########################################
# conv11 = layers.Conv3D(filters_num[0], kernel_size=(5, 5, 3), padding='same',
# kernel_initializer='he_normal', kernel_regularizer=regularizers.l2(0.0001))(input_layer_up)
# conv11_bn = layers.BatchNormalization()(conv11)
# conv11_relu = layers.Activation('relu')(conv11_bn)
#
# # conv2 = layers.Conv3D(filters_num[1], kernel_size=(3, 3, 5), padding='same')(conv1_relu) # filters_num = 16
# conv22 = layers.Conv3D(filters_num[1], kernel_size=(5, 5, 3), padding='same', kernel_initializer='he_normal',
# kernel_regularizer=regularizers.l2(0.0001))(conv11_relu) # filters_num = 16
# conv22_bn = layers.BatchNormalization()(conv22)
# conv22_relu = layers.Activation('relu')(conv22_bn)
#
# conv33 = layers.Conv3D(filters_num[2], kernel_size=(5, 5, 3), padding='same', kernel_initializer='he_normal',
# kernel_regularizer=regularizers.l2(0.0001))(conv22_relu) # filters_num = 32
# conv33_bn = layers.BatchNormalization()(conv33)
# conv33_relu = layers.Activation('relu')(conv33_bn)
#
# conv33_relu_reshape = layers.Reshape(
# (conv3_relu.shape[1], conv3_relu.shape[2], conv3_relu.shape[3] * conv3_relu.shape[4]))(conv33_relu)
####################################################
# conv111 = layers.Conv3D(filters_num[0], kernel_size=(7, 7, 3), padding='same',
# kernel_initializer='he_normal', kernel_regularizer=regularizers.l2(0.0001))(input_layer_up)
# conv111_bn = layers.BatchNormalization()(conv111)
# conv111_relu = layers.Activation('relu')(conv111_bn)
#
# # conv2 = layers.Conv3D(filters_num[1], kernel_size=(3, 3, 5), padding='same')(conv1_relu) # filters_num = 16
# conv222 = layers.Conv3D(filters_num[1], kernel_size=(7, 7, 3), padding='same', kernel_initializer='he_normal',
# kernel_regularizer=regularizers.l2(0.0001))(conv111_relu) # filters_num = 16
# conv222_bn = layers.BatchNormalization()(conv222)
# conv222_relu = layers.Activation('relu')(conv222_bn)
#
# conv333 = layers.Conv3D(filters_num[2], kernel_size=(7, 7, 3), padding='same', kernel_initializer='he_normal',
# kernel_regularizer=regularizers.l2(0.0001))(conv222_relu) # filters_num = 32
# conv333_bn = layers.BatchNormalization()(conv333)
# conv333_relu = layers.Activation('relu')(conv333_bn)
#
# conv333_relu_reshape = layers.Reshape(
# (conv3_relu.shape[1], conv3_relu.shape[2], conv3_relu.shape[3] * conv3_relu.shape[4]))(conv333_relu)
#################concatenate########################
# conv33333_relu_reshape = Concatenate(axis=-1)([conv3_relu_reshape, conv33_relu_reshape])
#########################################
conv4 = layers.Conv2D(filters_num[3], kernel_size=(3, 3), padding='same',kernel_regularizer=regularizers.l2(0.0001))(conv3_relu_reshape) # filters_num = 64
conv4_bn = layers.BatchNormalization()(conv4)
conv4_relu = layers.Activation('relu')(conv4_bn)
# conv4_relu = Dropout(0.5)(conv4_relu)
# conv4_relu = tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=(1, 1), padding='same')(conv4_relu)
# conv4_relu = tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2), strides=(1, 1, 1), padding='same')(conv4_relu)
conv5 = layers.Conv2D(filters_num[4], kernel_size=(3, 3), padding='same',kernel_regularizer=regularizers.l2(0.0001))(conv4_relu) # filters_num = **
conv5_bn = layers.BatchNormalization()(conv5)
conv5_relu = layers.Activation('relu')(conv5_bn)
# conv5_relu = Dropout(0.5)(conv5_relu)
# conv5_relu = tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=(1, 1), padding='same')(conv5_relu)
# conv5_relu = tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2), strides=(1, 1, 1), padding='same')(conv5_relu)
# conv5_dpout = layers.Dropout(dropout_rate)(conv5)
# conv5_reshape = layers.Reshape((conv5_dpout.shape[1],conv5_dpout.shape[2],conv5_dpout.shape[3]))(conv5_dpout)
outputs2,outputs4 = Block_res(conv5_relu)
return conv5,outputs2,outputs4
# layer1 = build_resblock(filters_num[5], layer_dims[0]) # filters_num = 64
# layer2 = build_resblock(filters_num[6], layer_dims[1], stride=2) # filters_num = 128
# layer3 = build_resblock(filters_num[7], layer_dims[2], stride=2) # filters_num = 256
# layer4 = build_resblock(filters_num[8], layer_dims[3], stride=2) # filters_num = 512
| [
201,
198,
6738,
11192,
273,
11125,
13,
6122,
292,
1330,
1635,
201,
198,
11748,
220,
11192,
273,
11125,
355,
48700,
201,
198,
6738,
220,
220,
220,
11192,
273,
11125,
1330,
41927,
292,
201,
198,
6738,
220,
220,
220,
11192,
273,
11125,
13,
6122,
292,
1330,
11685,
11,
24604,
1843,
11,
16338,
11341,
201,
198,
6738,
11192,
273,
11125,
13,
6122,
292,
13,
75,
6962,
1330,
14258,
448,
201,
198,
2,
422,
11192,
273,
11125,
13,
6122,
292,
1330,
1635,
201,
198,
2,
220,
513,
87,
18,
33885,
62,
36733,
7509,
11639,
258,
62,
11265,
41707,
70,
4685,
313,
62,
11265,
6,
201,
198,
6738,
11192,
273,
11125,
13,
29412,
13,
6122,
292,
13,
75,
6962,
1330,
1482,
9246,
268,
378,
201,
198,
201,
198,
14468,
7804,
4242,
21017,
220,
1303,
14468,
7804,
4242,
2235,
201,
198,
201,
198,
201,
198,
14468,
7804,
4242,
21017,
220,
1303,
14468,
7804,
4242,
2235,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
29113,
4242,
2235,
201,
198,
201,
198,
201,
198,
201,
198,
4299,
1382,
62,
411,
9967,
7,
944,
11,
8106,
62,
22510,
11,
7021,
11,
33769,
28,
16,
2599,
201,
198,
201,
198,
220,
220,
220,
581,
62,
27372,
796,
24604,
1843,
3419,
201,
198,
220,
220,
220,
1303,
743,
866,
6291,
201,
198,
220,
220,
220,
581,
62,
27372,
13,
2860,
7,
26416,
12235,
7,
24455,
62,
22510,
11,
33769,
4008,
201,
198,
201,
198,
220,
220,
220,
329,
4808,
287,
2837,
7,
16,
11,
7021,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
62,
27372,
13,
2860,
7,
26416,
12235,
7,
24455,
62,
22510,
11,
33769,
28,
16,
4008,
201,
198,
201,
198,
220,
220,
220,
1441,
581,
62,
27372,
201,
198,
201,
198,
29113,
4242,
2235,
201,
198,
201,
198,
201,
198,
201,
198,
14468,
7804,
21017,
220,
9788,
17,
1303,
29113,
4242,
21017,
201,
198,
201,
198,
201,
198,
201,
198,
4299,
3127,
62,
929,
7,
15414,
62,
29289,
62,
929,
11,
10379,
1010,
62,
22510,
11,
14781,
448,
62,
4873,
11,
12235,
62,
411,
2599,
201,
198,
220,
220,
220,
1303,
5128,
62,
29289,
796,
23412,
7,
15414,
62,
43358,
8,
201,
198,
220,
220,
220,
1303,
3063,
16,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
15,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
767,
828,
24511,
11639,
31642,
6,
5769,
15414,
62,
29289,
8,
220,
1303,
16628,
62,
22510,
796,
807,
201,
198,
220,
220,
220,
1303,
3063,
16,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
15,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
513,
828,
39231,
11639,
31642,
3256,
33885,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
33885,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
15414,
62,
29289,
62,
929,
8,
220,
1303,
16628,
62,
22510,
796,
807,
201,
198,
220,
220,
220,
3063,
16,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
15,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
513,
828,
24511,
11639,
31642,
3256,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
15414,
62,
29289,
62,
929,
8,
220,
1303,
33885,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
201,
198,
220,
220,
220,
1303,
3063,
62,
29289,
16,
76,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
16,
11,
352,
11,
352,
828,
39231,
11639,
31642,
6,
5769,
42946,
16,
8,
201,
198,
220,
220,
220,
1303,
3063,
62,
29289,
16,
70,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
22289,
11518,
27201,
278,
18,
35,
3419,
7,
42946,
16,
8,
201,
198,
220,
220,
220,
3063,
16,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
16,
8,
201,
198,
220,
220,
220,
3063,
16,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
16,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
3063,
16,
62,
260,
2290,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
16,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
16,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
11,
362,
828,
35002,
16193,
16,
11,
352,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
16,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
1303,
3063,
17,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
642,
828,
24511,
11639,
31642,
6,
5769,
42946,
16,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
3063,
17,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
513,
828,
39231,
11639,
31642,
3256,
33885,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
16,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
3063,
17,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
17,
8,
201,
198,
220,
220,
220,
3063,
17,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
17,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
3063,
17,
62,
260,
2290,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
17,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
17,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
11,
362,
828,
35002,
16193,
16,
11,
352,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
17,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
3063,
18,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
17,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
513,
828,
39231,
11639,
31642,
3256,
33885,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
17,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
3933,
201,
198,
220,
220,
220,
3063,
18,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
18,
8,
201,
198,
220,
220,
220,
3063,
18,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
18,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
3063,
18,
62,
260,
2290,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
18,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
18,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
11,
362,
828,
35002,
16193,
16,
11,
352,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
18,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
3063,
18,
62,
260,
2290,
62,
3447,
1758,
796,
11685,
13,
4965,
71,
1758,
19510,
42946,
18,
62,
260,
2290,
13,
43358,
58,
16,
4357,
42946,
18,
62,
260,
2290,
13,
43358,
58,
17,
4357,
42946,
18,
62,
260,
2290,
13,
43358,
58,
18,
60,
9,
42946,
18,
62,
260,
2290,
13,
43358,
58,
19,
60,
4008,
7,
42946,
18,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
3063,
18,
62,
260,
2290,
62,
3447,
1758,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
18,
62,
260,
2290,
62,
3447,
1758,
8,
201,
198,
220,
220,
220,
1303,
29113,
7804,
2235,
201,
198,
220,
220,
220,
1303,
3063,
1157,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
15,
4357,
9720,
62,
7857,
16193,
20,
11,
642,
11,
513,
828,
24511,
11639,
31642,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
15414,
62,
29289,
62,
929,
8,
201,
198,
220,
220,
220,
1303,
3063,
1157,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
1157,
8,
201,
198,
220,
220,
220,
1303,
3063,
1157,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
1157,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
1303,
3063,
17,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
642,
828,
24511,
11639,
31642,
6,
5769,
42946,
16,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
1303,
3063,
1828,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
20,
11,
642,
11,
513,
828,
24511,
11639,
31642,
3256,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
1157,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
1303,
3063,
1828,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
1828,
8,
201,
198,
220,
220,
220,
1303,
3063,
1828,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
1828,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
3063,
2091,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
17,
4357,
9720,
62,
7857,
16193,
20,
11,
642,
11,
513,
828,
24511,
11639,
31642,
3256,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
1828,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
3933,
201,
198,
220,
220,
220,
1303,
3063,
2091,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
2091,
8,
201,
198,
220,
220,
220,
1303,
3063,
2091,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
2091,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
3063,
2091,
62,
260,
2290,
62,
3447,
1758,
796,
11685,
13,
4965,
71,
1758,
7,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
357,
42946,
18,
62,
260,
2290,
13,
43358,
58,
16,
4357,
3063,
18,
62,
260,
2290,
13,
43358,
58,
17,
4357,
3063,
18,
62,
260,
2290,
13,
43358,
58,
18,
60,
1635,
3063,
18,
62,
260,
2290,
13,
43358,
58,
19,
60,
4008,
7,
42946,
2091,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
29113,
14468,
21017,
201,
198,
220,
220,
220,
1303,
3063,
16243,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
15,
4357,
9720,
62,
7857,
16193,
22,
11,
767,
11,
513,
828,
24511,
11639,
31642,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
15414,
62,
29289,
62,
929,
8,
201,
198,
220,
220,
220,
1303,
3063,
16243,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
16243,
8,
201,
198,
220,
220,
220,
1303,
3063,
16243,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
16243,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
1303,
3063,
17,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
11,
642,
828,
24511,
11639,
31642,
6,
5769,
42946,
16,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
1303,
3063,
23148,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
16,
4357,
9720,
62,
7857,
16193,
22,
11,
767,
11,
513,
828,
24511,
11639,
31642,
3256,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
16243,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
1467,
201,
198,
220,
220,
220,
1303,
3063,
23148,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
23148,
8,
201,
198,
220,
220,
220,
1303,
3063,
23148,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
23148,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
3063,
20370,
796,
11685,
13,
3103,
85,
18,
35,
7,
10379,
1010,
62,
22510,
58,
17,
4357,
9720,
62,
7857,
16193,
22,
11,
767,
11,
513,
828,
24511,
11639,
31642,
3256,
9720,
62,
36733,
7509,
11639,
258,
62,
11265,
3256,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9720,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
23148,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
3933,
201,
198,
220,
220,
220,
1303,
3063,
20370,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
20370,
8,
201,
198,
220,
220,
220,
1303,
3063,
20370,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
20370,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
201,
198,
220,
220,
220,
1303,
3063,
20370,
62,
260,
2290,
62,
3447,
1758,
796,
11685,
13,
4965,
71,
1758,
7,
201,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
357,
42946,
18,
62,
260,
2290,
13,
43358,
58,
16,
4357,
3063,
18,
62,
260,
2290,
13,
43358,
58,
17,
4357,
3063,
18,
62,
260,
2290,
13,
43358,
58,
18,
60,
1635,
3063,
18,
62,
260,
2290,
13,
43358,
58,
19,
60,
4008,
7,
42946,
20370,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
1303,
14468,
1102,
9246,
268,
378,
14468,
7804,
201,
198,
220,
220,
220,
1303,
3063,
2091,
20370,
62,
260,
2290,
62,
3447,
1758,
796,
1482,
9246,
268,
378,
7,
22704,
10779,
16,
5769,
58,
42946,
18,
62,
260,
2290,
62,
3447,
1758,
11,
3063,
2091,
62,
260,
2290,
62,
3447,
1758,
12962,
201,
198,
201,
198,
220,
220,
220,
1303,
29113,
7804,
201,
198,
220,
220,
220,
3063,
19,
796,
11685,
13,
3103,
85,
17,
35,
7,
10379,
1010,
62,
22510,
58,
18,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
828,
24511,
11639,
31642,
3256,
33885,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
18,
62,
260,
2290,
62,
3447,
1758,
8,
220,
1303,
16628,
62,
22510,
796,
5598,
201,
198,
220,
220,
220,
3063,
19,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
19,
8,
201,
198,
220,
220,
220,
3063,
19,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
19,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
3063,
19,
62,
260,
2290,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
19,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
19,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
17,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
828,
35002,
16193,
16,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
19,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
19,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
11,
362,
828,
35002,
16193,
16,
11,
352,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
19,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
3063,
20,
796,
11685,
13,
3103,
85,
17,
35,
7,
10379,
1010,
62,
22510,
58,
19,
4357,
9720,
62,
7857,
16193,
18,
11,
513,
828,
24511,
11639,
31642,
3256,
33885,
62,
16338,
7509,
28,
16338,
11341,
13,
75,
17,
7,
15,
13,
18005,
4008,
7,
42946,
19,
62,
260,
2290,
8,
220,
1303,
16628,
62,
22510,
796,
12429,
201,
198,
220,
220,
220,
3063,
20,
62,
9374,
796,
11685,
13,
33,
963,
26447,
1634,
3419,
7,
42946,
20,
8,
201,
198,
220,
220,
220,
3063,
20,
62,
260,
2290,
796,
11685,
13,
25526,
341,
10786,
260,
2290,
6,
5769,
42946,
20,
62,
9374,
8,
201,
198,
220,
220,
220,
1303,
3063,
20,
62,
260,
2290,
796,
14258,
448,
7,
15,
13,
20,
5769,
42946,
20,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
20,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
17,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
828,
35002,
16193,
16,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
20,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
20,
62,
260,
2290,
796,
48700,
13,
6122,
292,
13,
75,
6962,
13,
11518,
27201,
278,
18,
35,
7,
7742,
62,
7857,
16193,
17,
11,
362,
11,
362,
828,
35002,
16193,
16,
11,
352,
11,
352,
828,
24511,
11639,
31642,
6,
5769,
42946,
20,
62,
260,
2290,
8,
201,
198,
220,
220,
220,
1303,
3063,
20,
62,
26059,
448,
796,
11685,
13,
26932,
448,
7,
14781,
448,
62,
4873,
5769,
42946,
20,
8,
201,
198,
201,
198,
220,
220,
220,
1303,
3063,
20,
62,
3447,
1758,
796,
11685,
13,
4965,
71,
1758,
19510,
42946,
20,
62,
26059,
448,
13,
43358,
58,
16,
4357,
42946,
20,
62,
26059,
448,
13,
43358,
58,
17,
4357,
42946,
20,
62,
26059,
448,
13,
43358,
58,
18,
60,
4008,
7,
42946,
20,
62,
26059,
448,
8,
201,
198,
220,
220,
220,
23862,
17,
11,
22915,
82,
19,
796,
9726,
62,
411,
7,
42946,
20,
62,
260,
2290,
8,
201,
198,
201,
198,
220,
220,
220,
1441,
3063,
20,
11,
22915,
82,
17,
11,
22915,
82,
19,
201,
198,
201,
198,
201,
198,
201,
198,
220,
220,
220,
1303,
7679,
16,
796,
1382,
62,
411,
9967,
7,
10379,
1010,
62,
22510,
58,
20,
4357,
7679,
62,
67,
12078,
58,
15,
12962,
220,
1303,
16628,
62,
22510,
796,
5598,
201,
198,
220,
220,
220,
1303,
7679,
17,
796,
1382,
62,
411,
9967,
7,
10379,
1010,
62,
22510,
58,
21,
4357,
7679,
62,
67,
12078,
58,
16,
4357,
33769,
28,
17,
8,
220,
220,
220,
1303,
16628,
62,
22510,
796,
13108,
201,
198,
220,
220,
220,
1303,
7679,
18,
796,
1382,
62,
411,
9967,
7,
10379,
1010,
62,
22510,
58,
22,
4357,
7679,
62,
67,
12078,
58,
17,
4357,
33769,
28,
17,
8,
220,
220,
1303,
16628,
62,
22510,
796,
17759,
201,
198,
220,
220,
220,
1303,
7679,
19,
796,
1382,
62,
411,
9967,
7,
10379,
1010,
62,
22510,
58,
23,
4357,
7679,
62,
67,
12078,
58,
18,
4357,
33769,
28,
17,
8,
220,
1303,
16628,
62,
22510,
796,
22243,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198
] | 2.277826 | 3,441 |
""" A universal module with functions / classes without dependencies. """
import sys
import contextlib
import functools
import re
import os
from medi._compatibility import reraise
_sep = os.path.sep
if os.path.altsep is not None:
_sep += os.path.altsep
_path_re = re.compile(r'(?:\.[^{0}]+|[{0}]__init__\.py)$'.format(re.escape(_sep)))
del _sep
def unite(iterable):
"""Turns a two dimensional array into a one dimensional."""
return set(typ for types in iterable for typ in types)
def reraise_uncaught(func):
"""
Re-throw uncaught `AttributeError`.
Usage: Put ``@rethrow_uncaught`` in front of the function
which does **not** suppose to raise `AttributeError`.
AttributeError is easily get caught by `hasattr` and another
``except AttributeError`` clause. This becomes problem when you use
a lot of "dynamic" attributes (e.g., using ``@property``) because you
can't distinguish if the property does not exist for real or some code
inside of the "dynamic" attribute through that error. In a well
written code, such error should not exist but getting there is very
difficult. This decorator is to help us getting there by changing
`AttributeError` to `UncaughtAttributeError` to avoid unexpected catch.
This helps us noticing bugs earlier and facilitates debugging.
.. note:: Treating StopIteration here is easy.
Add that feature when needed.
"""
return wrapper
| [
37811,
317,
10112,
8265,
351,
5499,
1220,
6097,
1231,
20086,
13,
37227,
198,
11748,
25064,
198,
11748,
4732,
8019,
198,
11748,
1257,
310,
10141,
198,
11748,
302,
198,
11748,
28686,
198,
198,
6738,
16957,
13557,
5589,
25901,
1330,
302,
40225,
628,
198,
62,
325,
79,
796,
28686,
13,
6978,
13,
325,
79,
198,
361,
28686,
13,
6978,
13,
2501,
325,
79,
318,
407,
6045,
25,
198,
220,
220,
220,
4808,
325,
79,
15853,
28686,
13,
6978,
13,
2501,
325,
79,
198,
62,
6978,
62,
260,
796,
302,
13,
5589,
576,
7,
81,
6,
7,
30,
7479,
3693,
36796,
15,
92,
48688,
91,
58,
90,
15,
92,
60,
834,
15003,
834,
17405,
9078,
8,
3,
4458,
18982,
7,
260,
13,
41915,
28264,
325,
79,
22305,
198,
12381,
4808,
325,
79,
628,
628,
198,
4299,
24558,
7,
2676,
540,
2599,
198,
220,
220,
220,
37227,
17278,
82,
257,
734,
38517,
7177,
656,
257,
530,
38517,
526,
15931,
198,
220,
220,
220,
1441,
900,
7,
28004,
329,
3858,
287,
11629,
540,
329,
2170,
287,
3858,
8,
628,
628,
198,
4299,
302,
40225,
62,
19524,
3413,
7,
20786,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
797,
12,
16939,
4591,
3413,
4600,
33682,
12331,
44646,
628,
220,
220,
220,
29566,
25,
220,
5930,
7559,
31,
260,
16939,
62,
19524,
3413,
15506,
287,
2166,
286,
262,
2163,
198,
220,
220,
220,
543,
857,
12429,
1662,
1174,
11691,
284,
5298,
4600,
33682,
12331,
44646,
628,
220,
220,
220,
3460,
4163,
12331,
318,
3538,
651,
4978,
416,
4600,
10134,
35226,
63,
290,
1194,
198,
220,
220,
220,
7559,
16341,
3460,
4163,
12331,
15506,
13444,
13,
220,
770,
4329,
1917,
618,
345,
779,
198,
220,
220,
220,
257,
1256,
286,
366,
67,
28995,
1,
12608,
357,
68,
13,
70,
1539,
1262,
7559,
31,
26745,
15506,
8,
780,
345,
198,
220,
220,
220,
460,
470,
15714,
611,
262,
3119,
857,
407,
2152,
329,
1103,
393,
617,
2438,
198,
220,
220,
220,
2641,
286,
262,
366,
67,
28995,
1,
11688,
832,
326,
4049,
13,
220,
554,
257,
880,
198,
220,
220,
220,
3194,
2438,
11,
884,
4049,
815,
407,
2152,
475,
1972,
612,
318,
845,
198,
220,
220,
220,
2408,
13,
220,
770,
11705,
1352,
318,
284,
1037,
514,
1972,
612,
416,
5609,
198,
220,
220,
220,
4600,
33682,
12331,
63,
284,
4600,
3118,
66,
3413,
33682,
12331,
63,
284,
3368,
10059,
4929,
13,
198,
220,
220,
220,
770,
5419,
514,
28107,
11316,
2961,
290,
42699,
28769,
13,
628,
220,
220,
220,
11485,
3465,
3712,
11217,
278,
13707,
29993,
341,
994,
318,
2562,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3060,
326,
3895,
618,
2622,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
29908,
628,
198
] | 3.202614 | 459 |
"""Bioconductor run git transition code.
This module assembles the classes for the SVN --> Git transition
can be run in a sequential manner.
It runs the following aspects fo the Bioconductor transition.
Note: Update the SVN dump
1. Run Bioconductor Software package transition
2. Run Bioconductor Experiment Data package transition
3. Run Workflow package transition
4. Run Manifest file transition
5. Run Rapid update of master (trunk) and RELEASE_3_5 branches on
software packages
Manual tasks which need to be done:
1. Copy over bare repos to repositories/packages
2. Copy manifest bare git repo to repositories/admin
"""
import src.run_transition as rt
import src.svn_dump_update as sdu
import logging
import time
logging.basicConfig(filename='transition.log',
format='%(levelname)s %(asctime)s %(message)s',
level=logging.DEBUG)
if __name__ == '__main__':
start_time = time.time()
config_file = "./settings.ini"
svn_dump_update(config_file)
run(config_file)
# TODO: Run updates after dump update
svn_dump_update(config_file)
rt.run_updates(config_file)
logging.info("--- %s seconds ---" % (time.time() - start_time))
| [
37811,
23286,
420,
40990,
1057,
17606,
6801,
2438,
13,
198,
198,
1212,
8265,
11156,
829,
262,
6097,
329,
262,
20546,
45,
14610,
15151,
6801,
198,
5171,
307,
1057,
287,
257,
35582,
5642,
13,
198,
198,
1026,
4539,
262,
1708,
7612,
11511,
262,
8436,
420,
40990,
6801,
13,
198,
198,
6425,
25,
10133,
262,
20546,
45,
10285,
198,
198,
16,
13,
5660,
8436,
420,
40990,
10442,
5301,
6801,
198,
17,
13,
5660,
8436,
420,
40990,
29544,
6060,
5301,
6801,
198,
18,
13,
5660,
5521,
11125,
5301,
6801,
198,
19,
13,
5660,
36757,
2393,
6801,
198,
20,
13,
5660,
26430,
4296,
286,
4958,
357,
2213,
2954,
8,
290,
46492,
62,
18,
62,
20,
13737,
319,
198,
220,
220,
3788,
10392,
198,
198,
5124,
723,
8861,
543,
761,
284,
307,
1760,
25,
198,
16,
13,
17393,
625,
6247,
1128,
418,
284,
38072,
14,
43789,
198,
17,
13,
17393,
10561,
6247,
17606,
29924,
284,
38072,
14,
28482,
198,
37811,
198,
198,
11748,
12351,
13,
5143,
62,
7645,
653,
355,
374,
83,
198,
11748,
12351,
13,
21370,
77,
62,
39455,
62,
19119,
355,
264,
646,
198,
11748,
18931,
198,
11748,
640,
198,
6404,
2667,
13,
35487,
16934,
7,
34345,
11639,
7645,
653,
13,
6404,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5794,
11639,
4,
7,
5715,
3672,
8,
82,
4064,
7,
292,
310,
524,
8,
82,
4064,
7,
20500,
8,
82,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1241,
28,
6404,
2667,
13,
30531,
8,
628,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
923,
62,
2435,
796,
640,
13,
2435,
3419,
198,
220,
220,
220,
4566,
62,
7753,
796,
366,
19571,
33692,
13,
5362,
1,
198,
220,
220,
220,
38487,
77,
62,
39455,
62,
19119,
7,
11250,
62,
7753,
8,
198,
220,
220,
220,
1057,
7,
11250,
62,
7753,
8,
198,
2,
16926,
46,
25,
5660,
5992,
706,
10285,
4296,
198,
220,
220,
220,
38487,
77,
62,
39455,
62,
19119,
7,
11250,
62,
7753,
8,
198,
220,
220,
220,
374,
83,
13,
5143,
62,
929,
19581,
7,
11250,
62,
7753,
8,
198,
220,
220,
220,
18931,
13,
10951,
7203,
6329,
4064,
82,
4201,
11420,
1,
4064,
357,
2435,
13,
2435,
3419,
532,
923,
62,
2435,
4008,
198
] | 3.015038 | 399 |
from __future__ import with_statement
from .. import Lock, NeedRegenerationException
from ..util import NameRegistry
from . import exception
from ..util import PluginLoader, memoized_property, coerce_string_conf
from .util import function_key_generator, function_multi_key_generator
from .api import NO_VALUE, CachedValue
from .proxy import ProxyBackend
from ..util import compat
import time
import datetime
from numbers import Number
from functools import wraps
import threading
_backend_loader = PluginLoader("dogpile.cache")
register_backend = _backend_loader.register
from . import backends # noqa
value_version = 1
"""An integer placed in the :class:`.CachedValue`
so that new versions of dogpile.cache can detect cached
values from a previous, backwards-incompatible version.
"""
def _unexpired_value_fn(self, expiration_time, ignore_expiration):
if ignore_expiration:
return lambda value: value
else:
if expiration_time is None:
expiration_time = self.expiration_time
current_time = time.time()
return value_fn
def get_multi(self, keys, expiration_time=None, ignore_expiration=False):
"""Return multiple values from the cache, based on the given keys.
Returns values as a list matching the keys given.
E.g.::
values = region.get_multi(["one", "two", "three"])
To convert values to a dictionary, use ``zip()``::
keys = ["one", "two", "three"]
values = region.get_multi(keys)
dictionary = dict(zip(keys, values))
Keys which aren't present in the list are returned as
the ``NO_VALUE`` token. ``NO_VALUE`` evaluates to False,
but is separate from
``None`` to distinguish between a cached value of ``None``.
By default, the configured expiration time of the
:class:`.CacheRegion`, or alternatively the expiration
time supplied by the ``expiration_time`` argument,
is tested against the creation time of the retrieved
value versus the current time (as reported by ``time.time()``).
If stale, the cached value is ignored and the ``NO_VALUE``
token is returned. Passing the flag ``ignore_expiration=True``
bypasses the expiration time check.
.. versionadded:: 0.5.0
"""
if not keys:
return []
if self.key_mangler:
keys = list(map(lambda key: self.key_mangler(key), keys))
backend_values = self.backend.get_multi(keys)
_unexpired_value_fn = self._unexpired_value_fn(
expiration_time, ignore_expiration)
return [
value.payload if value is not NO_VALUE else value
for value in
(
_unexpired_value_fn(value) for value in
backend_values
)
]
def get_or_create(
self, key, creator, expiration_time=None, should_cache_fn=None):
"""Return a cached value based on the given key.
If the value does not exist or is considered to be expired
based on its creation time, the given
creation function may or may not be used to recreate the value
and persist the newly generated value in the cache.
Whether or not the function is used depends on if the
*dogpile lock* can be acquired or not. If it can't, it means
a different thread or process is already running a creation
function for this key against the cache. When the dogpile
lock cannot be acquired, the method will block if no
previous value is available, until the lock is released and
a new value available. If a previous value
is available, that value is returned immediately without blocking.
If the :meth:`.invalidate` method has been called, and
the retrieved value's timestamp is older than the invalidation
timestamp, the value is unconditionally prevented from
being returned. The method will attempt to acquire the dogpile
lock to generate a new value, or will wait
until the lock is released to return the new value.
.. versionchanged:: 0.3.0
The value is unconditionally regenerated if the creation
time is older than the last call to :meth:`.invalidate`.
:param key: Key to be retrieved. While it's typical for a key to be a
string, it is ultimately passed directly down to the cache backend,
before being optionally processed by the key_mangler function, so can
be of any type recognized by the backend or by the key_mangler
function, if present.
:param creator: function which creates a new value.
:param expiration_time: optional expiration time which will overide
the expiration time already configured on this :class:`.CacheRegion`
if not None. To set no expiration, use the value -1.
:param should_cache_fn: optional callable function which will receive
the value returned by the "creator", and will then return True or
False, indicating if the value should actually be cached or not. If
it returns False, the value is still returned, but isn't cached.
E.g.::
def dont_cache_none(value):
return value is not None
value = region.get_or_create("some key",
create_value,
should_cache_fn=dont_cache_none)
Above, the function returns the value of create_value() if
the cache is invalid, however if the return value is None,
it won't be cached.
.. versionadded:: 0.4.3
.. seealso::
:meth:`.CacheRegion.cache_on_arguments` - applies
:meth:`.get_or_create` to any function using a decorator.
:meth:`.CacheRegion.get_or_create_multi` - multiple key/value
version
"""
orig_key = key
if self.key_mangler:
key = self.key_mangler(key)
if expiration_time is None:
expiration_time = self.expiration_time
if (expiration_time is None and
self.region_invalidator.was_soft_invalidated()):
raise exception.DogpileCacheException(
"Non-None expiration time required "
"for soft invalidation")
if expiration_time == -1:
expiration_time = None
if self.async_creation_runner:
else:
async_creator = None
with Lock(
self._mutex(key),
gen_value,
get_value,
expiration_time,
async_creator) as value:
return value
def get_or_create_multi(
self, keys, creator, expiration_time=None, should_cache_fn=None):
"""Return a sequence of cached values based on a sequence of keys.
The behavior for generation of values based on keys corresponds
to that of :meth:`.Region.get_or_create`, with the exception that
the ``creator()`` function may be asked to generate any subset of
the given keys. The list of keys to be generated is passed to
``creator()``, and ``creator()`` should return the generated values
as a sequence corresponding to the order of the keys.
The method uses the same approach as :meth:`.Region.get_multi`
and :meth:`.Region.set_multi` to get and set values from the
backend.
If you are using a :class:`.CacheBackend` or :class:`.ProxyBackend`
that modifies values, take note this function invokes
``.set_multi()`` for newly generated values using the same values it
returns to the calling function. A correct implementation of
``.set_multi()`` will not modify values in-place on the submitted
``mapping`` dict.
:param keys: Sequence of keys to be retrieved.
:param creator: function which accepts a sequence of keys and
returns a sequence of new values.
:param expiration_time: optional expiration time which will overide
the expiration time already configured on this :class:`.CacheRegion`
if not None. To set no expiration, use the value -1.
:param should_cache_fn: optional callable function which will receive
each value returned by the "creator", and will then return True or
False, indicating if the value should actually be cached or not. If
it returns False, the value is still returned, but isn't cached.
.. versionadded:: 0.5.0
.. seealso::
:meth:`.CacheRegion.cache_multi_on_arguments`
:meth:`.CacheRegion.get_or_create`
"""
if expiration_time is None:
expiration_time = self.expiration_time
if (expiration_time is None and
self.region_invalidator.was_soft_invalidated()):
raise exception.DogpileCacheException(
"Non-None expiration time required "
"for soft invalidation")
if expiration_time == -1:
expiration_time = None
mutexes = {}
sorted_unique_keys = sorted(set(keys))
if self.key_mangler:
mangled_keys = [self.key_mangler(k) for k in sorted_unique_keys]
else:
mangled_keys = sorted_unique_keys
orig_to_mangled = dict(zip(sorted_unique_keys, mangled_keys))
values = dict(zip(mangled_keys, self.backend.get_multi(mangled_keys)))
for orig_key, mangled_key in orig_to_mangled.items():
with Lock(
self._mutex(mangled_key),
gen_value,
lambda: get_value(mangled_key),
expiration_time,
async_creator=lambda mutex: async_creator(orig_key, mutex)
):
pass
try:
if mutexes:
# sort the keys, the idea is to prevent deadlocks.
# though haven't been able to simulate one anyway.
keys_to_get = sorted(mutexes)
new_values = creator(*keys_to_get)
values_w_created = dict(
(orig_to_mangled[k], self._value(v))
for k, v in zip(keys_to_get, new_values)
)
if not should_cache_fn:
self.backend.set_multi(values_w_created)
else:
self.backend.set_multi(dict(
(k, v)
for k, v in values_w_created.items()
if should_cache_fn(v[0])
))
values.update(values_w_created)
return [values[orig_to_mangled[k]].payload for k in keys]
finally:
for mutex in mutexes.values():
mutex.release()
def _value(self, value):
"""Return a :class:`.CachedValue` given a value."""
return CachedValue(
value,
{
"ct": time.time(),
"v": value_version
})
def set(self, key, value):
"""Place a new value in the cache under the given key."""
if self.key_mangler:
key = self.key_mangler(key)
self.backend.set(key, self._value(value))
def set_multi(self, mapping):
"""Place new values in the cache under the given keys.
.. versionadded:: 0.5.0
"""
if not mapping:
return
if self.key_mangler:
mapping = dict((
self.key_mangler(k), self._value(v))
for k, v in mapping.items())
else:
mapping = dict((k, self._value(v)) for k, v in mapping.items())
self.backend.set_multi(mapping)
def delete(self, key):
"""Remove a value from the cache.
This operation is idempotent (can be called multiple times, or on a
non-existent key, safely)
"""
if self.key_mangler:
key = self.key_mangler(key)
self.backend.delete(key)
def delete_multi(self, keys):
"""Remove multiple values from the cache.
This operation is idempotent (can be called multiple times, or on a
non-existent key, safely)
.. versionadded:: 0.5.0
"""
if self.key_mangler:
keys = list(map(lambda key: self.key_mangler(key), keys))
self.backend.delete_multi(keys)
def cache_on_arguments(
self, namespace=None,
expiration_time=None,
should_cache_fn=None,
to_str=compat.string_type,
function_key_generator=None):
"""A function decorator that will cache the return
value of the function using a key derived from the
function itself and its arguments.
The decorator internally makes use of the
:meth:`.CacheRegion.get_or_create` method to access the
cache and conditionally call the function. See that
method for additional behavioral details.
E.g.::
@someregion.cache_on_arguments()
def generate_something(x, y):
return somedatabase.query(x, y)
The decorated function can then be called normally, where
data will be pulled from the cache region unless a new
value is needed::
result = generate_something(5, 6)
The function is also given an attribute ``invalidate()``, which
provides for invalidation of the value. Pass to ``invalidate()``
the same arguments you'd pass to the function itself to represent
a particular value::
generate_something.invalidate(5, 6)
Another attribute ``set()`` is added to provide extra caching
possibilities relative to the function. This is a convenience
method for :meth:`.CacheRegion.set` which will store a given
value directly without calling the decorated function.
The value to be cached is passed as the first argument, and the
arguments which would normally be passed to the function
should follow::
generate_something.set(3, 5, 6)
The above example is equivalent to calling
``generate_something(5, 6)``, if the function were to produce
the value ``3`` as the value to be cached.
.. versionadded:: 0.4.1 Added ``set()`` method to decorated function.
Similar to ``set()`` is ``refresh()``. This attribute will
invoke the decorated function and populate a new value into
the cache with the new value, as well as returning that value::
newvalue = generate_something.refresh(5, 6)
.. versionadded:: 0.5.0 Added ``refresh()`` method to decorated
function.
Lastly, the ``get()`` method returns either the value cached
for the given key, or the token ``NO_VALUE`` if no such key
exists::
value = generate_something.get(5, 6)
.. versionadded:: 0.5.3 Added ``get()`` method to decorated
function.
The default key generation will use the name
of the function, the module name for the function,
the arguments passed, as well as an optional "namespace"
parameter in order to generate a cache key.
Given a function ``one`` inside the module
``myapp.tools``::
@region.cache_on_arguments(namespace="foo")
def one(a, b):
return a + b
Above, calling ``one(3, 4)`` will produce a
cache key as follows::
myapp.tools:one|foo|3 4
The key generator will ignore an initial argument
of ``self`` or ``cls``, making the decorator suitable
(with caveats) for use with instance or class methods.
Given the example::
class MyClass(object):
@region.cache_on_arguments(namespace="foo")
def one(self, a, b):
return a + b
The cache key above for ``MyClass().one(3, 4)`` will
again produce the same cache key of ``myapp.tools:one|foo|3 4`` -
the name ``self`` is skipped.
The ``namespace`` parameter is optional, and is used
normally to disambiguate two functions of the same
name within the same module, as can occur when decorating
instance or class methods as below::
class MyClass(object):
@region.cache_on_arguments(namespace='MC')
def somemethod(self, x, y):
""
class MyOtherClass(object):
@region.cache_on_arguments(namespace='MOC')
def somemethod(self, x, y):
""
Above, the ``namespace`` parameter disambiguates
between ``somemethod`` on ``MyClass`` and ``MyOtherClass``.
Python class declaration mechanics otherwise prevent
the decorator from having awareness of the ``MyClass``
and ``MyOtherClass`` names, as the function is received
by the decorator before it becomes an instance method.
The function key generation can be entirely replaced
on a per-region basis using the ``function_key_generator``
argument present on :func:`.make_region` and
:class:`.CacheRegion`. If defaults to
:func:`.function_key_generator`.
:param namespace: optional string argument which will be
established as part of the cache key. This may be needed
to disambiguate functions of the same name within the same
source file, such as those
associated with classes - note that the decorator itself
can't see the parent class on a function as the class is
being declared.
:param expiration_time: if not None, will override the normal
expiration time.
May be specified as a callable, taking no arguments, that
returns a value to be used as the ``expiration_time``. This callable
will be called whenever the decorated function itself is called, in
caching or retrieving. Thus, this can be used to
determine a *dynamic* expiration time for the cached function
result. Example use cases include "cache the result until the
end of the day, week or time period" and "cache until a certain date
or time passes".
.. versionchanged:: 0.5.0
``expiration_time`` may be passed as a callable to
:meth:`.CacheRegion.cache_on_arguments`.
:param should_cache_fn: passed to :meth:`.CacheRegion.get_or_create`.
.. versionadded:: 0.4.3
:param to_str: callable, will be called on each function argument
in order to convert to a string. Defaults to ``str()``. If the
function accepts non-ascii unicode arguments on Python 2.x, the
``unicode()`` builtin can be substituted, but note this will
produce unicode cache keys which may require key mangling before
reaching the cache.
.. versionadded:: 0.5.0
:param function_key_generator: a function that will produce a
"cache key". This function will supersede the one configured on the
:class:`.CacheRegion` itself.
.. versionadded:: 0.5.5
.. seealso::
:meth:`.CacheRegion.cache_multi_on_arguments`
:meth:`.CacheRegion.get_or_create`
"""
expiration_time_is_callable = compat.callable(expiration_time)
if function_key_generator is None:
function_key_generator = self.function_key_generator
return decorator
def cache_multi_on_arguments(
self, namespace=None, expiration_time=None,
should_cache_fn=None,
asdict=False, to_str=compat.string_type,
function_multi_key_generator=None):
"""A function decorator that will cache multiple return
values from the function using a sequence of keys derived from the
function itself and the arguments passed to it.
This method is the "multiple key" analogue to the
:meth:`.CacheRegion.cache_on_arguments` method.
Example::
@someregion.cache_multi_on_arguments()
def generate_something(*keys):
return [
somedatabase.query(key)
for key in keys
]
The decorated function can be called normally. The decorator
will produce a list of cache keys using a mechanism similar to
that of :meth:`.CacheRegion.cache_on_arguments`, combining the
name of the function with the optional namespace and with the
string form of each key. It will then consult the cache using
the same mechanism as that of :meth:`.CacheRegion.get_multi`
to retrieve all current values; the originally passed keys
corresponding to those values which aren't generated or need
regeneration will be assembled into a new argument list, and
the decorated function is then called with that subset of
arguments.
The returned result is a list::
result = generate_something("key1", "key2", "key3")
The decorator internally makes use of the
:meth:`.CacheRegion.get_or_create_multi` method to access the
cache and conditionally call the function. See that
method for additional behavioral details.
Unlike the :meth:`.CacheRegion.cache_on_arguments` method,
:meth:`.CacheRegion.cache_multi_on_arguments` works only with
a single function signature, one which takes a simple list of
keys as arguments.
Like :meth:`.CacheRegion.cache_on_arguments`, the decorated function
is also provided with a ``set()`` method, which here accepts a
mapping of keys and values to set in the cache::
generate_something.set({"k1": "value1",
"k2": "value2", "k3": "value3"})
...an ``invalidate()`` method, which has the effect of deleting
the given sequence of keys using the same mechanism as that of
:meth:`.CacheRegion.delete_multi`::
generate_something.invalidate("k1", "k2", "k3")
...a ``refresh()`` method, which will call the creation
function, cache the new values, and return them::
values = generate_something.refresh("k1", "k2", "k3")
...and a ``get()`` method, which will return values
based on the given arguments::
values = generate_something.get("k1", "k2", "k3")
.. versionadded:: 0.5.3 Added ``get()`` method to decorated
function.
Parameters passed to :meth:`.CacheRegion.cache_multi_on_arguments`
have the same meaning as those passed to
:meth:`.CacheRegion.cache_on_arguments`.
:param namespace: optional string argument which will be
established as part of each cache key.
:param expiration_time: if not None, will override the normal
expiration time. May be passed as an integer or a
callable.
:param should_cache_fn: passed to
:meth:`.CacheRegion.get_or_create_multi`. This function is given a
value as returned by the creator, and only if it returns True will
that value be placed in the cache.
:param asdict: if ``True``, the decorated function should return
its result as a dictionary of keys->values, and the final result
of calling the decorated function will also be a dictionary.
If left at its default value of ``False``, the decorated function
should return its result as a list of values, and the final
result of calling the decorated function will also be a list.
When ``asdict==True`` if the dictionary returned by the decorated
function is missing keys, those keys will not be cached.
:param to_str: callable, will be called on each function argument
in order to convert to a string. Defaults to ``str()``. If the
function accepts non-ascii unicode arguments on Python 2.x, the
``unicode()`` builtin can be substituted, but note this will
produce unicode cache keys which may require key mangling before
reaching the cache.
.. versionadded:: 0.5.0
:param function_multi_key_generator: a function that will produce a
list of keys. This function will supersede the one configured on the
:class:`.CacheRegion` itself.
.. versionadded:: 0.5.5
.. seealso::
:meth:`.CacheRegion.cache_on_arguments`
:meth:`.CacheRegion.get_or_create_multi`
"""
expiration_time_is_callable = compat.callable(expiration_time)
if function_multi_key_generator is None:
function_multi_key_generator = self.function_multi_key_generator
return decorator
def make_region(*arg, **kw):
"""Instantiate a new :class:`.CacheRegion`.
Currently, :func:`.make_region` is a passthrough
to :class:`.CacheRegion`. See that class for
constructor arguments.
"""
return CacheRegion(*arg, **kw)
| [
6738,
11593,
37443,
834,
1330,
351,
62,
26090,
198,
6738,
11485,
1330,
13656,
11,
10664,
8081,
877,
341,
16922,
198,
6738,
11485,
22602,
1330,
6530,
8081,
4592,
198,
6738,
764,
1330,
6631,
198,
6738,
11485,
22602,
1330,
42636,
17401,
11,
16155,
1143,
62,
26745,
11,
31255,
344,
62,
8841,
62,
10414,
198,
6738,
764,
22602,
1330,
2163,
62,
2539,
62,
8612,
1352,
11,
2163,
62,
41684,
62,
2539,
62,
8612,
1352,
198,
6738,
764,
15042,
1330,
8005,
62,
39488,
11,
327,
2317,
11395,
198,
6738,
764,
36436,
1330,
38027,
7282,
437,
198,
6738,
11485,
22602,
1330,
8330,
198,
11748,
640,
198,
11748,
4818,
8079,
198,
6738,
3146,
1330,
7913,
198,
6738,
1257,
310,
10141,
1330,
27521,
198,
11748,
4704,
278,
198,
198,
62,
1891,
437,
62,
29356,
796,
42636,
17401,
7203,
9703,
79,
576,
13,
23870,
4943,
198,
30238,
62,
1891,
437,
796,
4808,
1891,
437,
62,
29356,
13,
30238,
198,
6738,
764,
1330,
736,
2412,
220,
1303,
645,
20402,
198,
198,
8367,
62,
9641,
796,
352,
198,
37811,
2025,
18253,
4624,
287,
262,
1058,
4871,
25,
44646,
34,
2317,
11395,
63,
198,
568,
326,
649,
6300,
286,
3290,
79,
576,
13,
23870,
460,
4886,
39986,
198,
27160,
422,
257,
2180,
11,
16196,
12,
259,
38532,
2196,
13,
198,
198,
37811,
628,
628,
198,
220,
220,
220,
825,
4808,
403,
1069,
6474,
62,
8367,
62,
22184,
7,
944,
11,
28385,
62,
2435,
11,
8856,
62,
1069,
10514,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
8856,
62,
1069,
10514,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
37456,
1988,
25,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
28385,
62,
2435,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
796,
2116,
13,
1069,
10514,
62,
2435,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1459,
62,
2435,
796,
640,
13,
2435,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
62,
22184,
628,
220,
220,
220,
825,
651,
62,
41684,
7,
944,
11,
8251,
11,
28385,
62,
2435,
28,
14202,
11,
8856,
62,
1069,
10514,
28,
25101,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
3294,
3815,
422,
262,
12940,
11,
1912,
319,
262,
1813,
8251,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
3815,
355,
257,
1351,
12336,
262,
8251,
1813,
13,
628,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
3814,
13,
1136,
62,
41684,
7,
14692,
505,
1600,
366,
11545,
1600,
366,
15542,
8973,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1675,
10385,
3815,
284,
257,
22155,
11,
779,
7559,
13344,
3419,
15506,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
14631,
505,
1600,
366,
11545,
1600,
366,
15542,
8973,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
3814,
13,
1136,
62,
41684,
7,
13083,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22155,
796,
8633,
7,
13344,
7,
13083,
11,
3815,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
26363,
543,
3588,
470,
1944,
287,
262,
1351,
389,
4504,
355,
198,
220,
220,
220,
220,
220,
220,
220,
262,
7559,
15285,
62,
39488,
15506,
11241,
13,
220,
7559,
15285,
62,
39488,
15506,
47850,
284,
10352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
475,
318,
4553,
422,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
14202,
15506,
284,
15714,
1022,
257,
39986,
1988,
286,
7559,
14202,
15506,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2750,
4277,
11,
262,
17839,
28385,
640,
286,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
44646,
30562,
47371,
47671,
393,
46596,
262,
28385,
198,
220,
220,
220,
220,
220,
220,
220,
640,
14275,
416,
262,
7559,
1069,
10514,
62,
2435,
15506,
4578,
11,
198,
220,
220,
220,
220,
220,
220,
220,
318,
6789,
1028,
262,
6282,
640,
286,
262,
29517,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
9051,
262,
1459,
640,
357,
292,
2098,
416,
7559,
2435,
13,
2435,
3419,
15506,
737,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
39985,
11,
262,
39986,
1988,
318,
9514,
290,
262,
7559,
15285,
62,
39488,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
11241,
318,
4504,
13,
220,
46389,
262,
6056,
7559,
46430,
62,
1069,
10514,
28,
17821,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
17286,
274,
262,
28385,
640,
2198,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
8251,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
17635,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
1351,
7,
8899,
7,
50033,
1994,
25,
2116,
13,
2539,
62,
76,
49910,
7,
2539,
828,
8251,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
30203,
62,
27160,
796,
2116,
13,
1891,
437,
13,
1136,
62,
41684,
7,
13083,
8,
628,
220,
220,
220,
220,
220,
220,
220,
4808,
403,
1069,
6474,
62,
8367,
62,
22184,
796,
2116,
13557,
403,
1069,
6474,
62,
8367,
62,
22184,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
11,
8856,
62,
1069,
10514,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
13,
15577,
2220,
611,
1988,
318,
407,
8005,
62,
39488,
2073,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1988,
287,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4808,
403,
1069,
6474,
62,
8367,
62,
22184,
7,
8367,
8,
329,
1988,
287,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30203,
62,
27160,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
825,
651,
62,
273,
62,
17953,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
1994,
11,
13172,
11,
28385,
62,
2435,
28,
14202,
11,
815,
62,
23870,
62,
22184,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
257,
39986,
1988,
1912,
319,
262,
1813,
1994,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1002,
262,
1988,
857,
407,
2152,
393,
318,
3177,
284,
307,
21350,
198,
220,
220,
220,
220,
220,
220,
220,
1912,
319,
663,
6282,
640,
11,
262,
1813,
198,
220,
220,
220,
220,
220,
220,
220,
6282,
2163,
743,
393,
743,
407,
307,
973,
284,
32049,
262,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
290,
21160,
262,
8308,
7560,
1988,
287,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
10127,
393,
407,
262,
2163,
318,
973,
8338,
319,
611,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1635,
9703,
79,
576,
5793,
9,
460,
307,
9477,
393,
407,
13,
220,
1002,
340,
460,
470,
11,
340,
1724,
198,
220,
220,
220,
220,
220,
220,
220,
257,
1180,
4704,
393,
1429,
318,
1541,
2491,
257,
6282,
198,
220,
220,
220,
220,
220,
220,
220,
2163,
329,
428,
1994,
1028,
262,
12940,
13,
220,
1649,
262,
3290,
79,
576,
198,
220,
220,
220,
220,
220,
220,
220,
5793,
2314,
307,
9477,
11,
262,
2446,
481,
2512,
611,
645,
198,
220,
220,
220,
220,
220,
220,
220,
2180,
1988,
318,
1695,
11,
1566,
262,
5793,
318,
2716,
290,
198,
220,
220,
220,
220,
220,
220,
220,
257,
649,
1988,
1695,
13,
220,
1002,
257,
2180,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
318,
1695,
11,
326,
1988,
318,
4504,
3393,
1231,
12013,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1002,
262,
1058,
76,
2788,
25,
44646,
259,
12102,
378,
63,
2446,
468,
587,
1444,
11,
290,
198,
220,
220,
220,
220,
220,
220,
220,
262,
29517,
1988,
338,
41033,
318,
4697,
621,
262,
12515,
341,
198,
220,
220,
220,
220,
220,
220,
220,
41033,
11,
262,
1988,
318,
31776,
8736,
13351,
422,
198,
220,
220,
220,
220,
220,
220,
220,
852,
4504,
13,
220,
383,
2446,
481,
2230,
284,
12831,
262,
3290,
79,
576,
198,
220,
220,
220,
220,
220,
220,
220,
5793,
284,
7716,
257,
649,
1988,
11,
393,
481,
4043,
198,
220,
220,
220,
220,
220,
220,
220,
1566,
262,
5793,
318,
2716,
284,
1441,
262,
649,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
40985,
3712,
657,
13,
18,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1988,
318,
31776,
8736,
16935,
515,
611,
262,
6282,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
318,
4697,
621,
262,
938,
869,
284,
1058,
76,
2788,
25,
44646,
259,
12102,
378,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
1994,
25,
7383,
284,
307,
29517,
13,
2893,
340,
338,
7226,
329,
257,
1994,
284,
307,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
4731,
11,
340,
318,
6165,
3804,
3264,
866,
284,
262,
12940,
30203,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
878,
852,
42976,
13686,
416,
262,
1994,
62,
76,
49910,
2163,
11,
523,
460,
198,
220,
220,
220,
220,
220,
220,
220,
220,
307,
286,
597,
2099,
8018,
416,
262,
30203,
393,
416,
262,
1994,
62,
76,
49910,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
11,
611,
1944,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
13172,
25,
2163,
543,
8075,
257,
649,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
28385,
62,
2435,
25,
11902,
28385,
640,
543,
481,
625,
485,
198,
220,
220,
220,
220,
220,
220,
220,
220,
262,
28385,
640,
1541,
17839,
319,
428,
1058,
4871,
25,
44646,
30562,
47371,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
6045,
13,
220,
220,
1675,
900,
645,
28385,
11,
779,
262,
1988,
532,
16,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
815,
62,
23870,
62,
22184,
25,
11902,
869,
540,
2163,
543,
481,
3328,
198,
220,
220,
220,
220,
220,
220,
220,
220,
262,
1988,
4504,
416,
262,
366,
45382,
1600,
290,
481,
788,
1441,
6407,
393,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10352,
11,
12739,
611,
262,
1988,
815,
1682,
307,
39986,
393,
407,
13,
220,
1002,
198,
220,
220,
220,
220,
220,
220,
220,
220,
340,
5860,
10352,
11,
262,
1988,
318,
991,
4504,
11,
475,
2125,
470,
39986,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
17666,
62,
23870,
62,
23108,
7,
8367,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
318,
407,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
3814,
13,
1136,
62,
273,
62,
17953,
7203,
11246,
1994,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2251,
62,
8367,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
815,
62,
23870,
62,
22184,
28,
67,
756,
62,
23870,
62,
23108,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
23302,
11,
262,
2163,
5860,
262,
1988,
286,
2251,
62,
8367,
3419,
611,
198,
220,
220,
220,
220,
220,
220,
220,
220,
262,
12940,
318,
12515,
11,
2158,
611,
262,
1441,
1988,
318,
6045,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
340,
1839,
470,
307,
39986,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
19,
13,
18,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
766,
14508,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
63,
532,
8991,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
1136,
62,
273,
62,
17953,
63,
284,
597,
2163,
1262,
257,
11705,
1352,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
62,
41684,
63,
532,
3294,
1994,
14,
8367,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2196,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1796,
62,
2539,
796,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
2116,
13,
2539,
62,
76,
49910,
7,
2539,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
28385,
62,
2435,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
796,
2116,
13,
1069,
10514,
62,
2435,
628,
220,
220,
220,
220,
220,
220,
220,
611,
357,
1069,
10514,
62,
2435,
318,
6045,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
36996,
62,
259,
12102,
1352,
13,
9776,
62,
4215,
62,
259,
12102,
515,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
6631,
13,
32942,
79,
576,
30562,
16922,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
15419,
12,
14202,
28385,
640,
2672,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1640,
2705,
12515,
341,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
611,
28385,
62,
2435,
6624,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
292,
13361,
62,
38793,
62,
16737,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30351,
62,
45382,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
351,
13656,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
21973,
1069,
7,
2539,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2429,
62,
8367,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
651,
62,
8367,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30351,
62,
45382,
8,
355,
1988,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1988,
628,
220,
220,
220,
825,
651,
62,
273,
62,
17953,
62,
41684,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
8251,
11,
13172,
11,
28385,
62,
2435,
28,
14202,
11,
815,
62,
23870,
62,
22184,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
257,
8379,
286,
39986,
3815,
1912,
319,
257,
8379,
286,
8251,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
4069,
329,
5270,
286,
3815,
1912,
319,
8251,
24866,
198,
220,
220,
220,
220,
220,
220,
220,
284,
326,
286,
1058,
76,
2788,
25,
44646,
47371,
13,
1136,
62,
273,
62,
17953,
47671,
351,
262,
6631,
326,
198,
220,
220,
220,
220,
220,
220,
220,
262,
7559,
45382,
3419,
15506,
2163,
743,
307,
1965,
284,
7716,
597,
24637,
286,
198,
220,
220,
220,
220,
220,
220,
220,
262,
1813,
8251,
13,
220,
220,
383,
1351,
286,
8251,
284,
307,
7560,
318,
3804,
284,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
45382,
3419,
15506,
11,
290,
7559,
45382,
3419,
15506,
815,
1441,
262,
7560,
3815,
198,
220,
220,
220,
220,
220,
220,
220,
355,
257,
8379,
11188,
284,
262,
1502,
286,
262,
8251,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
2446,
3544,
262,
976,
3164,
355,
1058,
76,
2788,
25,
44646,
47371,
13,
1136,
62,
41684,
63,
198,
220,
220,
220,
220,
220,
220,
220,
290,
1058,
76,
2788,
25,
44646,
47371,
13,
2617,
62,
41684,
63,
284,
651,
290,
900,
3815,
422,
262,
198,
220,
220,
220,
220,
220,
220,
220,
30203,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1002,
345,
389,
1262,
257,
1058,
4871,
25,
44646,
30562,
7282,
437,
63,
393,
1058,
4871,
25,
44646,
44148,
7282,
437,
63,
198,
220,
220,
220,
220,
220,
220,
220,
326,
953,
6945,
3815,
11,
1011,
3465,
428,
2163,
800,
3369,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
13,
2617,
62,
41684,
3419,
15506,
329,
8308,
7560,
3815,
1262,
262,
976,
3815,
340,
198,
220,
220,
220,
220,
220,
220,
220,
5860,
284,
262,
4585,
2163,
13,
317,
3376,
7822,
286,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
13,
2617,
62,
41684,
3419,
15506,
481,
407,
13096,
3815,
287,
12,
5372,
319,
262,
8948,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
76,
5912,
15506,
8633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
8251,
25,
45835,
286,
8251,
284,
307,
29517,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
13172,
25,
2163,
543,
18178,
257,
8379,
286,
8251,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
5860,
257,
8379,
286,
649,
3815,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
28385,
62,
2435,
25,
11902,
28385,
640,
543,
481,
625,
485,
198,
220,
220,
220,
220,
220,
220,
220,
220,
262,
28385,
640,
1541,
17839,
319,
428,
1058,
4871,
25,
44646,
30562,
47371,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
6045,
13,
220,
220,
1675,
900,
645,
28385,
11,
779,
262,
1988,
532,
16,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
815,
62,
23870,
62,
22184,
25,
11902,
869,
540,
2163,
543,
481,
3328,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1123,
1988,
4504,
416,
262,
366,
45382,
1600,
290,
481,
788,
1441,
6407,
393,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10352,
11,
12739,
611,
262,
1988,
815,
1682,
307,
39986,
393,
407,
13,
220,
1002,
198,
220,
220,
220,
220,
220,
220,
220,
220,
340,
5860,
10352,
11,
262,
1988,
318,
991,
4504,
11,
475,
2125,
470,
39986,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
766,
14508,
3712,
628,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
41684,
62,
261,
62,
853,
2886,
63,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
63,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
28385,
62,
2435,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
796,
2116,
13,
1069,
10514,
62,
2435,
628,
220,
220,
220,
220,
220,
220,
220,
611,
357,
1069,
10514,
62,
2435,
318,
6045,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
36996,
62,
259,
12102,
1352,
13,
9776,
62,
4215,
62,
259,
12102,
515,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
6631,
13,
32942,
79,
576,
30562,
16922,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
15419,
12,
14202,
28385,
640,
2672,
366,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
1640,
2705,
12515,
341,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
611,
28385,
62,
2435,
6624,
532,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
4517,
1069,
274,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
23243,
62,
34642,
62,
13083,
796,
23243,
7,
2617,
7,
13083,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45663,
992,
62,
13083,
796,
685,
944,
13,
2539,
62,
76,
49910,
7,
74,
8,
329,
479,
287,
23243,
62,
34642,
62,
13083,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45663,
992,
62,
13083,
796,
23243,
62,
34642,
62,
13083,
628,
220,
220,
220,
220,
220,
220,
220,
1796,
62,
1462,
62,
76,
22393,
796,
8633,
7,
13344,
7,
82,
9741,
62,
34642,
62,
13083,
11,
45663,
992,
62,
13083,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
8633,
7,
13344,
7,
76,
22393,
62,
13083,
11,
2116,
13,
1891,
437,
13,
1136,
62,
41684,
7,
76,
22393,
62,
13083,
22305,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1796,
62,
2539,
11,
45663,
992,
62,
2539,
287,
1796,
62,
1462,
62,
76,
22393,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
351,
13656,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
21973,
1069,
7,
76,
22393,
62,
2539,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2429,
62,
8367,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37456,
25,
651,
62,
8367,
7,
76,
22393,
62,
2539,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30351,
62,
45382,
28,
50033,
4517,
1069,
25,
30351,
62,
45382,
7,
11612,
62,
2539,
11,
4517,
1069,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
4517,
1069,
274,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3297,
262,
8251,
11,
262,
2126,
318,
284,
2948,
2636,
28860,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
996,
4398,
470,
587,
1498,
284,
29308,
530,
6949,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8251,
62,
1462,
62,
1136,
796,
23243,
7,
21973,
1069,
274,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
27160,
796,
13172,
46491,
13083,
62,
1462,
62,
1136,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
62,
86,
62,
25598,
796,
8633,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
11612,
62,
1462,
62,
76,
22393,
58,
74,
4357,
2116,
13557,
8367,
7,
85,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
11,
410,
287,
19974,
7,
13083,
62,
1462,
62,
1136,
11,
649,
62,
27160,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
815,
62,
23870,
62,
22184,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
2617,
62,
41684,
7,
27160,
62,
86,
62,
25598,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
2617,
62,
41684,
7,
11600,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
74,
11,
410,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
11,
410,
287,
3815,
62,
86,
62,
25598,
13,
23814,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
815,
62,
23870,
62,
22184,
7,
85,
58,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15306,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
13,
19119,
7,
27160,
62,
86,
62,
25598,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
27160,
58,
11612,
62,
1462,
62,
76,
22393,
58,
74,
60,
4083,
15577,
2220,
329,
479,
287,
8251,
60,
198,
220,
220,
220,
220,
220,
220,
220,
3443,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
4517,
1069,
287,
4517,
1069,
274,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4517,
1069,
13,
20979,
3419,
628,
220,
220,
220,
825,
4808,
8367,
7,
944,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
257,
1058,
4871,
25,
44646,
34,
2317,
11395,
63,
1813,
257,
1988,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
327,
2317,
11395,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
310,
1298,
640,
13,
2435,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
85,
1298,
1988,
62,
9641,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
220,
220,
220,
825,
900,
7,
944,
11,
1994,
11,
1988,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
27271,
257,
649,
1988,
287,
262,
12940,
739,
262,
1813,
1994,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
2116,
13,
2539,
62,
76,
49910,
7,
2539,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
2617,
7,
2539,
11,
2116,
13557,
8367,
7,
8367,
4008,
628,
220,
220,
220,
825,
900,
62,
41684,
7,
944,
11,
16855,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
27271,
649,
3815,
287,
262,
12940,
739,
262,
1813,
8251,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
16855,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16855,
796,
8633,
19510,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2539,
62,
76,
49910,
7,
74,
828,
2116,
13557,
8367,
7,
85,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
11,
410,
287,
16855,
13,
23814,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16855,
796,
8633,
19510,
74,
11,
2116,
13557,
8367,
7,
85,
4008,
329,
479,
11,
410,
287,
16855,
13,
23814,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
2617,
62,
41684,
7,
76,
5912,
8,
628,
220,
220,
220,
825,
12233,
7,
944,
11,
1994,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
27914,
257,
1988,
422,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
4905,
318,
4686,
368,
13059,
298,
357,
5171,
307,
1444,
3294,
1661,
11,
393,
319,
257,
198,
220,
220,
220,
220,
220,
220,
220,
1729,
12,
32786,
1994,
11,
11512,
8,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
2116,
13,
2539,
62,
76,
49910,
7,
2539,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
33678,
7,
2539,
8,
628,
220,
220,
220,
825,
12233,
62,
41684,
7,
944,
11,
8251,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
27914,
3294,
3815,
422,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
4905,
318,
4686,
368,
13059,
298,
357,
5171,
307,
1444,
3294,
1661,
11,
393,
319,
257,
198,
220,
220,
220,
220,
220,
220,
220,
1729,
12,
32786,
1994,
11,
11512,
8,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
2539,
62,
76,
49910,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8251,
796,
1351,
7,
8899,
7,
50033,
1994,
25,
2116,
13,
2539,
62,
76,
49910,
7,
2539,
828,
8251,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1891,
437,
13,
33678,
62,
41684,
7,
13083,
8,
628,
220,
220,
220,
825,
12940,
62,
261,
62,
853,
2886,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
25745,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
815,
62,
23870,
62,
22184,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
62,
2536,
28,
5589,
265,
13,
8841,
62,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
62,
2539,
62,
8612,
1352,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
32,
2163,
11705,
1352,
326,
481,
12940,
262,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
286,
262,
2163,
1262,
257,
1994,
10944,
422,
262,
198,
220,
220,
220,
220,
220,
220,
220,
2163,
2346,
290,
663,
7159,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
11705,
1352,
20947,
1838,
779,
286,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
63,
2446,
284,
1895,
262,
198,
220,
220,
220,
220,
220,
220,
220,
12940,
290,
4006,
453,
869,
262,
2163,
13,
220,
4091,
326,
198,
220,
220,
220,
220,
220,
220,
220,
2446,
329,
3224,
17211,
3307,
13,
628,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
11246,
36996,
13,
23870,
62,
261,
62,
853,
2886,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
7716,
62,
18927,
7,
87,
11,
331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
3870,
276,
265,
5754,
13,
22766,
7,
87,
11,
331,
8,
628,
220,
220,
220,
220,
220,
220,
220,
383,
24789,
2163,
460,
788,
307,
1444,
7685,
11,
810,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
481,
307,
5954,
422,
262,
12940,
3814,
4556,
257,
649,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
318,
2622,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
7716,
62,
18927,
7,
20,
11,
718,
8,
628,
220,
220,
220,
220,
220,
220,
220,
383,
2163,
318,
635,
1813,
281,
11688,
7559,
259,
12102,
378,
3419,
15506,
11,
543,
198,
220,
220,
220,
220,
220,
220,
220,
3769,
329,
12515,
341,
286,
262,
1988,
13,
220,
6251,
284,
7559,
259,
12102,
378,
3419,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
262,
976,
7159,
345,
1549,
1208,
284,
262,
2163,
2346,
284,
2380,
198,
220,
220,
220,
220,
220,
220,
220,
257,
1948,
1988,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7716,
62,
18927,
13,
259,
12102,
378,
7,
20,
11,
718,
8,
628,
220,
220,
220,
220,
220,
220,
220,
6023,
11688,
7559,
2617,
3419,
15506,
318,
2087,
284,
2148,
3131,
40918,
198,
220,
220,
220,
220,
220,
220,
220,
12779,
3585,
284,
262,
2163,
13,
220,
220,
770,
318,
257,
15607,
198,
220,
220,
220,
220,
220,
220,
220,
2446,
329,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
2617,
63,
543,
481,
3650,
257,
1813,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
3264,
1231,
4585,
262,
24789,
2163,
13,
198,
220,
220,
220,
220,
220,
220,
220,
383,
1988,
284,
307,
39986,
318,
3804,
355,
262,
717,
4578,
11,
290,
262,
198,
220,
220,
220,
220,
220,
220,
220,
7159,
543,
561,
7685,
307,
3804,
284,
262,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
815,
1061,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7716,
62,
18927,
13,
2617,
7,
18,
11,
642,
11,
718,
8,
628,
220,
220,
220,
220,
220,
220,
220,
383,
2029,
1672,
318,
7548,
284,
4585,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
8612,
378,
62,
18927,
7,
20,
11,
718,
8,
15506,
11,
611,
262,
2163,
547,
284,
4439,
198,
220,
220,
220,
220,
220,
220,
220,
262,
1988,
7559,
18,
15506,
355,
262,
1988,
284,
307,
39986,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
19,
13,
16,
10687,
7559,
2617,
3419,
15506,
2446,
284,
24789,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11014,
284,
7559,
2617,
3419,
15506,
318,
7559,
5420,
3447,
3419,
15506,
13,
220,
220,
770,
11688,
481,
198,
220,
220,
220,
220,
220,
220,
220,
26342,
262,
24789,
2163,
290,
48040,
257,
649,
1988,
656,
198,
220,
220,
220,
220,
220,
220,
220,
262,
12940,
351,
262,
649,
1988,
11,
355,
880,
355,
8024,
326,
1988,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
8367,
796,
7716,
62,
18927,
13,
5420,
3447,
7,
20,
11,
718,
8,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
10687,
7559,
5420,
3447,
3419,
15506,
2446,
284,
24789,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
36778,
11,
262,
7559,
1136,
3419,
15506,
2446,
5860,
2035,
262,
1988,
39986,
198,
220,
220,
220,
220,
220,
220,
220,
329,
262,
1813,
1994,
11,
393,
262,
11241,
7559,
15285,
62,
39488,
15506,
611,
645,
884,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
7160,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
7716,
62,
18927,
13,
1136,
7,
20,
11,
718,
8,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
18,
10687,
7559,
1136,
3419,
15506,
2446,
284,
24789,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
4277,
1994,
5270,
481,
779,
262,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
286,
262,
2163,
11,
262,
8265,
1438,
329,
262,
2163,
11,
198,
220,
220,
220,
220,
220,
220,
220,
262,
7159,
3804,
11,
355,
880,
355,
281,
11902,
366,
14933,
10223,
1,
198,
220,
220,
220,
220,
220,
220,
220,
11507,
287,
1502,
284,
7716,
257,
12940,
1994,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11259,
257,
2163,
7559,
505,
15506,
2641,
262,
8265,
198,
220,
220,
220,
220,
220,
220,
220,
7559,
1820,
1324,
13,
31391,
15506,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
36996,
13,
23870,
62,
261,
62,
853,
2886,
7,
14933,
10223,
2625,
21943,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
530,
7,
64,
11,
275,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
257,
1343,
275,
628,
220,
220,
220,
220,
220,
220,
220,
23302,
11,
4585,
7559,
505,
7,
18,
11,
604,
8,
15506,
481,
4439,
257,
198,
220,
220,
220,
220,
220,
220,
220,
12940,
1994,
355,
5679,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
616,
1324,
13,
31391,
25,
505,
91,
21943,
91,
18,
604,
628,
220,
220,
220,
220,
220,
220,
220,
383,
1994,
17301,
481,
8856,
281,
4238,
4578,
198,
220,
220,
220,
220,
220,
220,
220,
286,
7559,
944,
15506,
393,
7559,
565,
82,
15506,
11,
1642,
262,
11705,
1352,
11080,
198,
220,
220,
220,
220,
220,
220,
220,
357,
4480,
47155,
8,
329,
779,
351,
4554,
393,
1398,
5050,
13,
198,
220,
220,
220,
220,
220,
220,
220,
11259,
262,
1672,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
2011,
9487,
7,
15252,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
36996,
13,
23870,
62,
261,
62,
853,
2886,
7,
14933,
10223,
2625,
21943,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
530,
7,
944,
11,
257,
11,
275,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
257,
1343,
275,
628,
220,
220,
220,
220,
220,
220,
220,
383,
12940,
1994,
2029,
329,
7559,
3666,
9487,
22446,
505,
7,
18,
11,
604,
8,
15506,
481,
198,
220,
220,
220,
220,
220,
220,
220,
757,
4439,
262,
976,
12940,
1994,
286,
7559,
1820,
1324,
13,
31391,
25,
505,
91,
21943,
91,
18,
604,
15506,
532,
198,
220,
220,
220,
220,
220,
220,
220,
262,
1438,
7559,
944,
15506,
318,
26684,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
7559,
14933,
10223,
15506,
11507,
318,
11902,
11,
290,
318,
973,
198,
220,
220,
220,
220,
220,
220,
220,
7685,
284,
595,
4131,
328,
4985,
734,
5499,
286,
262,
976,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
1626,
262,
976,
8265,
11,
355,
460,
3051,
618,
11705,
803,
198,
220,
220,
220,
220,
220,
220,
220,
4554,
393,
1398,
5050,
355,
2174,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
2011,
9487,
7,
15252,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
36996,
13,
23870,
62,
261,
62,
853,
2886,
7,
14933,
10223,
11639,
9655,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
3870,
19261,
2065,
7,
944,
11,
2124,
11,
331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13538,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
2011,
6395,
9487,
7,
15252,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
36996,
13,
23870,
62,
261,
62,
853,
2886,
7,
14933,
10223,
11639,
44,
4503,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
3870,
19261,
2065,
7,
944,
11,
2124,
11,
331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13538,
628,
220,
220,
220,
220,
220,
220,
220,
23302,
11,
262,
7559,
14933,
10223,
15506,
11507,
595,
4131,
328,
12632,
198,
220,
220,
220,
220,
220,
220,
220,
1022,
7559,
82,
296,
19261,
2065,
15506,
319,
7559,
3666,
9487,
15506,
290,
7559,
3666,
6395,
9487,
15506,
13,
198,
220,
220,
220,
220,
220,
220,
220,
11361,
1398,
14305,
12933,
4306,
2948,
198,
220,
220,
220,
220,
220,
220,
220,
262,
11705,
1352,
422,
1719,
9359,
286,
262,
7559,
3666,
9487,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
290,
7559,
3666,
6395,
9487,
15506,
3891,
11,
355,
262,
2163,
318,
2722,
198,
220,
220,
220,
220,
220,
220,
220,
416,
262,
11705,
1352,
878,
340,
4329,
281,
4554,
2446,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
2163,
1994,
5270,
460,
307,
5000,
6928,
198,
220,
220,
220,
220,
220,
220,
220,
319,
257,
583,
12,
36996,
4308,
1262,
262,
7559,
8818,
62,
2539,
62,
8612,
1352,
15506,
198,
220,
220,
220,
220,
220,
220,
220,
4578,
1944,
319,
1058,
20786,
25,
44646,
15883,
62,
36996,
63,
290,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
44646,
30562,
47371,
44646,
1002,
26235,
284,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
20786,
25,
44646,
8818,
62,
2539,
62,
8612,
1352,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
25745,
25,
11902,
4731,
4578,
543,
481,
307,
198,
220,
220,
220,
220,
220,
220,
220,
220,
4920,
355,
636,
286,
262,
12940,
1994,
13,
220,
220,
770,
743,
307,
2622,
198,
220,
220,
220,
220,
220,
220,
220,
220,
284,
595,
4131,
328,
4985,
5499,
286,
262,
976,
1438,
1626,
262,
976,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
2393,
11,
884,
355,
883,
198,
220,
220,
220,
220,
220,
220,
220,
220,
3917,
351,
6097,
532,
3465,
326,
262,
11705,
1352,
2346,
198,
220,
220,
220,
220,
220,
220,
220,
220,
460,
470,
766,
262,
2560,
1398,
319,
257,
2163,
355,
262,
1398,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
852,
6875,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
28385,
62,
2435,
25,
611,
407,
6045,
11,
481,
20957,
262,
3487,
198,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
640,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
1737,
307,
7368,
355,
257,
869,
540,
11,
2263,
645,
7159,
11,
326,
198,
220,
220,
220,
220,
220,
220,
220,
220,
5860,
257,
1988,
284,
307,
973,
355,
262,
7559,
1069,
10514,
62,
2435,
15506,
13,
770,
869,
540,
198,
220,
220,
220,
220,
220,
220,
220,
220,
481,
307,
1444,
8797,
262,
24789,
2163,
2346,
318,
1444,
11,
287,
198,
220,
220,
220,
220,
220,
220,
220,
220,
40918,
393,
50122,
13,
6660,
11,
428,
460,
307,
973,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
5004,
257,
1635,
67,
28995,
9,
28385,
640,
329,
262,
39986,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1255,
13,
220,
17934,
779,
2663,
2291,
366,
23870,
262,
1255,
1566,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
886,
286,
262,
1110,
11,
1285,
393,
640,
2278,
1,
290,
366,
23870,
1566,
257,
1728,
3128,
198,
220,
220,
220,
220,
220,
220,
220,
220,
393,
640,
8318,
1911,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
40985,
3712,
657,
13,
20,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7559,
1069,
10514,
62,
2435,
15506,
743,
307,
3804,
355,
257,
869,
540,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
815,
62,
23870,
62,
22184,
25,
3804,
284,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
19,
13,
18,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
284,
62,
2536,
25,
869,
540,
11,
481,
307,
1444,
319,
1123,
2163,
4578,
198,
220,
220,
220,
220,
220,
220,
220,
220,
287,
1502,
284,
10385,
284,
257,
4731,
13,
220,
2896,
13185,
284,
7559,
2536,
3419,
15506,
13,
220,
1002,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
18178,
1729,
12,
292,
979,
72,
28000,
1098,
7159,
319,
11361,
362,
13,
87,
11,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
7559,
46903,
1098,
3419,
15506,
3170,
259,
460,
307,
31601,
11,
475,
3465,
428,
481,
198,
220,
220,
220,
220,
220,
220,
220,
220,
4439,
28000,
1098,
12940,
8251,
543,
743,
2421,
1994,
582,
40799,
878,
198,
220,
220,
220,
220,
220,
220,
220,
220,
8978,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
2163,
62,
2539,
62,
8612,
1352,
25,
257,
2163,
326,
481,
4439,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
366,
23870,
1994,
1911,
770,
2163,
481,
22754,
18654,
262,
530,
17839,
319,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
44646,
30562,
47371,
63,
2346,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
20,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
766,
14508,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
41684,
62,
261,
62,
853,
2886,
63,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
63,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
62,
271,
62,
13345,
540,
796,
8330,
13,
13345,
540,
7,
1069,
10514,
62,
2435,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2163,
62,
2539,
62,
8612,
1352,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
62,
2539,
62,
8612,
1352,
796,
2116,
13,
8818,
62,
2539,
62,
8612,
1352,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
11705,
1352,
628,
220,
220,
220,
825,
12940,
62,
41684,
62,
261,
62,
853,
2886,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
25745,
28,
14202,
11,
28385,
62,
2435,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
815,
62,
23870,
62,
22184,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
355,
11600,
28,
25101,
11,
284,
62,
2536,
28,
5589,
265,
13,
8841,
62,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
62,
41684,
62,
2539,
62,
8612,
1352,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
32,
2163,
11705,
1352,
326,
481,
12940,
3294,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
3815,
422,
262,
2163,
1262,
257,
8379,
286,
8251,
10944,
422,
262,
198,
220,
220,
220,
220,
220,
220,
220,
2163,
2346,
290,
262,
7159,
3804,
284,
340,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
2446,
318,
262,
366,
48101,
1994,
1,
45304,
284,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
63,
2446,
13,
628,
220,
220,
220,
220,
220,
220,
220,
17934,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2488,
11246,
36996,
13,
23870,
62,
41684,
62,
261,
62,
853,
2886,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
825,
7716,
62,
18927,
46491,
13083,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3870,
276,
265,
5754,
13,
22766,
7,
2539,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
287,
8251,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
383,
24789,
2163,
460,
307,
1444,
7685,
13,
220,
383,
11705,
1352,
198,
220,
220,
220,
220,
220,
220,
220,
481,
4439,
257,
1351,
286,
12940,
8251,
1262,
257,
9030,
2092,
284,
198,
220,
220,
220,
220,
220,
220,
220,
326,
286,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
47671,
19771,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
286,
262,
2163,
351,
262,
11902,
25745,
290,
351,
262,
198,
220,
220,
220,
220,
220,
220,
220,
4731,
1296,
286,
1123,
1994,
13,
220,
632,
481,
788,
5725,
262,
12940,
1262,
198,
220,
220,
220,
220,
220,
220,
220,
262,
976,
9030,
355,
326,
286,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
41684,
63,
198,
220,
220,
220,
220,
220,
220,
220,
284,
19818,
477,
1459,
3815,
26,
262,
6198,
3804,
8251,
198,
220,
220,
220,
220,
220,
220,
220,
11188,
284,
883,
3815,
543,
3588,
470,
7560,
393,
761,
198,
220,
220,
220,
220,
220,
220,
220,
27597,
481,
307,
16030,
656,
257,
649,
4578,
1351,
11,
290,
198,
220,
220,
220,
220,
220,
220,
220,
262,
24789,
2163,
318,
788,
1444,
351,
326,
24637,
286,
198,
220,
220,
220,
220,
220,
220,
220,
7159,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
4504,
1255,
318,
257,
1351,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
7716,
62,
18927,
7203,
2539,
16,
1600,
366,
2539,
17,
1600,
366,
2539,
18,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
383,
11705,
1352,
20947,
1838,
779,
286,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
62,
41684,
63,
2446,
284,
1895,
262,
198,
220,
220,
220,
220,
220,
220,
220,
12940,
290,
4006,
453,
869,
262,
2163,
13,
220,
4091,
326,
198,
220,
220,
220,
220,
220,
220,
220,
2446,
329,
3224,
17211,
3307,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12101,
262,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
63,
2446,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
41684,
62,
261,
62,
853,
2886,
63,
2499,
691,
351,
198,
220,
220,
220,
220,
220,
220,
220,
257,
2060,
2163,
9877,
11,
530,
543,
2753,
257,
2829,
1351,
286,
198,
220,
220,
220,
220,
220,
220,
220,
8251,
355,
7159,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4525,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
47671,
262,
24789,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
318,
635,
2810,
351,
257,
7559,
2617,
3419,
15506,
2446,
11,
543,
994,
18178,
257,
198,
220,
220,
220,
220,
220,
220,
220,
16855,
286,
8251,
290,
3815,
284,
900,
287,
262,
12940,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7716,
62,
18927,
13,
2617,
7,
4895,
74,
16,
1298,
366,
8367,
16,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
74,
17,
1298,
366,
8367,
17,
1600,
366,
74,
18,
1298,
366,
8367,
18,
20662,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2644,
272,
7559,
259,
12102,
378,
3419,
15506,
2446,
11,
543,
468,
262,
1245,
286,
34817,
198,
220,
220,
220,
220,
220,
220,
220,
262,
1813,
8379,
286,
8251,
1262,
262,
976,
9030,
355,
326,
286,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
33678,
62,
41684,
63,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7716,
62,
18927,
13,
259,
12102,
378,
7203,
74,
16,
1600,
366,
74,
17,
1600,
366,
74,
18,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
2644,
64,
7559,
5420,
3447,
3419,
15506,
2446,
11,
543,
481,
869,
262,
6282,
198,
220,
220,
220,
220,
220,
220,
220,
2163,
11,
12940,
262,
649,
3815,
11,
290,
1441,
606,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
7716,
62,
18927,
13,
5420,
3447,
7203,
74,
16,
1600,
366,
74,
17,
1600,
366,
74,
18,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
2644,
392,
257,
7559,
1136,
3419,
15506,
2446,
11,
543,
481,
1441,
3815,
198,
220,
220,
220,
220,
220,
220,
220,
1912,
319,
262,
1813,
7159,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3815,
796,
7716,
62,
18927,
13,
1136,
7203,
74,
16,
1600,
366,
74,
17,
1600,
366,
74,
18,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
18,
10687,
7559,
1136,
3419,
15506,
2446,
284,
24789,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
40117,
3804,
284,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
41684,
62,
261,
62,
853,
2886,
63,
198,
220,
220,
220,
220,
220,
220,
220,
423,
262,
976,
3616,
355,
883,
3804,
284,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
44646,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
25745,
25,
11902,
4731,
4578,
543,
481,
307,
198,
220,
220,
220,
220,
220,
220,
220,
220,
4920,
355,
636,
286,
1123,
12940,
1994,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
28385,
62,
2435,
25,
611,
407,
6045,
11,
481,
20957,
262,
3487,
198,
220,
220,
220,
220,
220,
220,
220,
220,
28385,
640,
13,
220,
1737,
307,
3804,
355,
281,
18253,
393,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
869,
540,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
815,
62,
23870,
62,
22184,
25,
3804,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
62,
41684,
44646,
770,
2163,
318,
1813,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
355,
4504,
416,
262,
13172,
11,
290,
691,
611,
340,
5860,
6407,
481,
198,
220,
220,
220,
220,
220,
220,
220,
220,
326,
1988,
307,
4624,
287,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
355,
11600,
25,
611,
7559,
17821,
15506,
11,
262,
24789,
2163,
815,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
663,
1255,
355,
257,
22155,
286,
8251,
3784,
27160,
11,
290,
262,
2457,
1255,
198,
220,
220,
220,
220,
220,
220,
220,
220,
286,
4585,
262,
24789,
2163,
481,
635,
307,
257,
22155,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1002,
1364,
379,
663,
4277,
1988,
286,
7559,
25101,
15506,
11,
262,
24789,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
220,
815,
1441,
663,
1255,
355,
257,
1351,
286,
3815,
11,
290,
262,
2457,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1255,
286,
4585,
262,
24789,
2163,
481,
635,
307,
257,
1351,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
1649,
7559,
292,
11600,
855,
17821,
15506,
611,
262,
22155,
4504,
416,
262,
24789,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
318,
4814,
8251,
11,
883,
8251,
481,
407,
307,
39986,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
284,
62,
2536,
25,
869,
540,
11,
481,
307,
1444,
319,
1123,
2163,
4578,
198,
220,
220,
220,
220,
220,
220,
220,
220,
287,
1502,
284,
10385,
284,
257,
4731,
13,
220,
2896,
13185,
284,
7559,
2536,
3419,
15506,
13,
220,
1002,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
18178,
1729,
12,
292,
979,
72,
28000,
1098,
7159,
319,
11361,
362,
13,
87,
11,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
7559,
46903,
1098,
3419,
15506,
3170,
259,
460,
307,
31601,
11,
475,
3465,
428,
481,
198,
220,
220,
220,
220,
220,
220,
220,
220,
4439,
28000,
1098,
12940,
8251,
543,
743,
2421,
1994,
582,
40799,
878,
198,
220,
220,
220,
220,
220,
220,
220,
220,
8978,
262,
12940,
13,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
1058,
17143,
2163,
62,
41684,
62,
2539,
62,
8612,
1352,
25,
257,
2163,
326,
481,
4439,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1351,
286,
8251,
13,
770,
2163,
481,
22754,
18654,
262,
530,
17839,
319,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
44646,
30562,
47371,
63,
2346,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
11485,
2196,
29373,
3712,
657,
13,
20,
13,
20,
628,
220,
220,
220,
220,
220,
220,
220,
11485,
766,
14508,
3712,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
23870,
62,
261,
62,
853,
2886,
63,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
76,
2788,
25,
44646,
30562,
47371,
13,
1136,
62,
273,
62,
17953,
62,
41684,
63,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
28385,
62,
2435,
62,
271,
62,
13345,
540,
796,
8330,
13,
13345,
540,
7,
1069,
10514,
62,
2435,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2163,
62,
41684,
62,
2539,
62,
8612,
1352,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2163,
62,
41684,
62,
2539,
62,
8612,
1352,
796,
2116,
13,
8818,
62,
41684,
62,
2539,
62,
8612,
1352,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
11705,
1352,
628,
198,
4299,
787,
62,
36996,
46491,
853,
11,
12429,
46265,
2599,
198,
220,
220,
220,
37227,
49933,
9386,
257,
649,
1058,
4871,
25,
44646,
30562,
47371,
44646,
628,
220,
220,
220,
16888,
11,
1058,
20786,
25,
44646,
15883,
62,
36996,
63,
318,
257,
38836,
48476,
740,
198,
220,
220,
220,
284,
1058,
4871,
25,
44646,
30562,
47371,
44646,
220,
4091,
326,
1398,
329,
198,
220,
220,
220,
23772,
7159,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
34088,
47371,
46491,
853,
11,
12429,
46265,
8,
198
] | 2.491484 | 10,216 |
# -*- coding: utf-8 -*-
"""
Module projectparallelprogrammeren.codesimulatie
=================================================================
Deze module simuleert alles.
"""
import projectparallelprogrammeren
def simulatie():
"""
Deze functie voert alle versies uit zodat deze vergeleken kunnen worden qua timing.
"""
from importlib import import_module
for i in range(4):
#alle versies van de simulatie importeren en achtereenvolgens uitvoeren.
version = f"montecarlo_v{i}"
montecarlo = import_module(version)
montecarlo.simulatie(100,50) #Deze waarden dienen enkel als test
if __name__ == "__main__":
simulatie()
#eof
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
37811,
198,
26796,
1628,
1845,
29363,
23065,
76,
14226,
13,
40148,
320,
377,
265,
494,
220,
198,
23926,
28,
198,
198,
5005,
2736,
8265,
985,
2261,
861,
477,
274,
13,
198,
198,
37811,
198,
198,
11748,
1628,
1845,
29363,
23065,
76,
14226,
198,
198,
4299,
39698,
265,
494,
33529,
198,
197,
37811,
198,
197,
5005,
2736,
1257,
310,
494,
7608,
861,
28654,
1646,
444,
334,
270,
1976,
375,
265,
390,
2736,
27373,
293,
3464,
479,
20935,
268,
1573,
268,
627,
64,
10576,
13,
198,
197,
37811,
198,
197,
6738,
1330,
8019,
1330,
1330,
62,
21412,
198,
197,
1640,
1312,
287,
2837,
7,
19,
2599,
198,
197,
197,
2,
6765,
1646,
444,
5719,
390,
39698,
265,
494,
1330,
14226,
551,
257,
21474,
567,
268,
10396,
70,
641,
334,
270,
13038,
14226,
13,
198,
197,
197,
9641,
796,
277,
1,
2144,
660,
7718,
5439,
62,
85,
90,
72,
36786,
198,
197,
197,
2144,
660,
7718,
5439,
796,
1330,
62,
21412,
7,
9641,
8,
198,
197,
197,
2144,
660,
7718,
5439,
13,
14323,
377,
265,
494,
7,
3064,
11,
1120,
8,
1303,
5005,
2736,
2082,
5872,
288,
2013,
268,
551,
7750,
435,
82,
1332,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
197,
14323,
377,
265,
494,
3419,
198,
197,
198,
2,
68,
1659,
198
] | 2.780172 | 232 |
#!/usr/bin/env python
from __future__ import unicode_literals
# Allow direct execution
import os
import sys
import unittest
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from haruhi_dl.aes import aes_decrypt, aes_encrypt, aes_cbc_decrypt, aes_cbc_encrypt, aes_decrypt_text
from haruhi_dl.utils import bytes_to_intlist, intlist_to_bytes
import base64
# the encrypted data can be generate with 'devscripts/generate_aes_testdata.py'
if __name__ == '__main__':
unittest.main()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
6738,
11593,
37443,
834,
1330,
28000,
1098,
62,
17201,
874,
198,
198,
2,
22507,
1277,
9706,
198,
11748,
28686,
198,
11748,
25064,
198,
11748,
555,
715,
395,
198,
17597,
13,
6978,
13,
28463,
7,
15,
11,
28686,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
15908,
3672,
7,
418,
13,
6978,
13,
397,
2777,
776,
7,
834,
7753,
834,
35514,
198,
198,
6738,
3971,
84,
5303,
62,
25404,
13,
64,
274,
1330,
257,
274,
62,
12501,
6012,
11,
257,
274,
62,
12685,
6012,
11,
257,
274,
62,
66,
15630,
62,
12501,
6012,
11,
257,
274,
62,
66,
15630,
62,
12685,
6012,
11,
257,
274,
62,
12501,
6012,
62,
5239,
198,
6738,
3971,
84,
5303,
62,
25404,
13,
26791,
1330,
9881,
62,
1462,
62,
600,
4868,
11,
493,
4868,
62,
1462,
62,
33661,
198,
11748,
2779,
2414,
198,
198,
2,
262,
19365,
1366,
460,
307,
7716,
351,
705,
7959,
46521,
14,
8612,
378,
62,
64,
274,
62,
9288,
7890,
13,
9078,
6,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.629442 | 197 |
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
def generate_dropdown_selection():
"return a Div containing the dropdown selection box"
return dcc.Dropdown(
id='dropdown_select_process',
style={"display": "none"},
options=[
{'label': 'Homogeneous Poisson process', 'value': 1},
{'label': 'Inhomogeneous Poisson process', 'value': 2},
{'label': 'Cluster process', 'value': 3},
# {'label': 'Strauss process', 'value': 4}
],
# set the initial value=0 to hide the user input interface
value=0)
def generate_user_input():
"return a Div containing users' input interface"
input_n_toolkits = html.Div(html.Div([html.A('Number of transects:', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=2,
value = 2,
id='input_n_toolkits',
className='col-sm-4'
)
], className='row'), id='input_n_toolkits_container', style={'display': 'none'})
# slider
# input_n_toolkits = html.Div(html.Div([
# html.A("Number of transects",className='col-sm-4'),
# dcc.Slider(min=1,
# max=5,
# step=1,
# value=2,
# marks={i: '{}'.format(i) for i in range(1, 6)},
# id='input_n_toolkits',
# className='col-sm-4')
# ], className='row'), id='input_n_toolkits_container',
# className='row',
# style={'display': 'none'})
input_disease_prevalence = html.Div(html.Div([html.A('disease prevalence: ', id='input_disease_prevalence_tooltip', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=0.1,
value = 0.1,
step=0.1,
min=0,
max=1,
id='input_disease_prevalence',
className='col-sm-4'
)
], className='row'), id='input_disease_prevalence_container', style={'display': 'none'})
input_disease_prevalence_tooltip = dbc.Tooltip('the proportion of corals which get infected by a disease', target='input_disease_prevalence_tooltip')
# text or number input
input_fun_lambda = html.Div(html.Div([html.A('proportion cover function:', className='col-sm-4'), dcc.Input(
id="input_fun_lambda",
type='text',
placeholder="1000 * np.exp(-(((x - 50) / 50) ** 2 + ((y - 50) / 50) ** 2) / 0.5 ** 2)",
value="1000 * np.exp(-(((x - 50) / 50) ** 2 + ((y - 50) / 50) ** 2) / 0.5 ** 2)",
className='col-sm-4'
)],className='row'),id='show_input_fun_lambda',style={'display':'none'})
input_parent_prop = html.Div(html.Div([html.A('parent corals / total corals:', className='col-sm-4'), dcc.Input(
id="input_parent_prop",
type='number',
placeholder=0.01,
value=0.01,
step=0.01,
className='col-sm-4'
)],className='row'),id='show_input_parent_prop',style={'display':'none'})
input_parent_range = html.Div(html.Div([html.A('parent range:', className='col-sm-4'), dcc.Input(
id="input_parent_range",
type='number',
placeholder=5,
value=5,
className='col-sm-4'
)],className='row'),id='show_input_parent_range',style={'display':'none'})
input_strauss_beta = dcc.Input(
id="input_strauss_beta",
type='number',
placeholder="strauss_beta",
style={'display': 'none'}
)
input_strauss_gamma = dcc.Input(
id="input_strauss_gamma",
type='number',
placeholder="strauss_gamma",
style={'display': 'none'}
)
input_strauss_R = dcc.Input(
id="input_strauss_R",
type='number',
placeholder="strauss_R",
style={'display': 'none'}
)
input_transect_length = html.Div(html.Div([html.A('transect width (m): ', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=25,
value=25,
id='dcc_input_transect_length',
className='col-sm-4'
)
], className='row'), id='input_transect_length', style={'display': 'none'})
input_transect_width = html.Div(html.Div([html.A('transect length (m): ', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=6,
value = 6,
id='dcc_input_transect_width',
className='col-sm-4'
)
], className='row'), id='input_transect_width', style={'display': 'none'})
line_intercept_ratio = html.Div(html.Div([html.A('transect width / plot width', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=1/5,
value = 1/5,
step=0.1,
id='dcc_line_intercept_ratio',
className='col-sm-4')
],className='row'), id='line_intercept_ratio', style={'display': 'none'})
coral_size = html.Div(html.Div([html.A('coral size (m^2): ', id='coral_size_tooltip',className='col-sm-4'),
dcc.Input(
type='number',
placeholder=0.0068,
value = 0.0068,
step=0.0001,
id='coral_size',
className='col-sm-4'
)
],className='row' ),
id='coral_size_input',
style={'display': 'none'})
coral_size_tooltip = dbc.Tooltip('the average size of an individual coral, measured in m^3', target='coral_size_tooltip')
coral_size_std = html.Div(html.Div([html.A('coral size standard error: ', id='coral_size_std_tooltip', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=0.001,
value = 0.001,
step=0.001,
id='coral_size_std',
className='col-sm-4'
)], className='row')
, id='coral_size_std_input', style={'display': 'none'})
coral_size_std_tooltip = dbc.Tooltip('the standard deviation of the average size of an individual coral', target='coral_size_std_tooltip')
prop_cover = html.Div(html.Div([html.A('proportion cover: ', className='col-sm-4', id='prop_cover_tooltip'),
dcc.Input(
type='number',
placeholder=0,
value = 0,
step=0.1,
min=0,
max=1,
id='prop_cover',
className='col-sm-4'
)
],className='row'), id='prop_cover_input', style={'display': 'none'})
prop_cover_tooltip = dbc.Tooltip('Proportion cover of coral. If it equals 0, its estimation based on the historical data will be used in the simulation', target='prop_cover_tooltip')
num_of_replications = html.Div(html.Div([html.A('number of replications', className='col-sm-4'),
dcc.Input(
type='number',
placeholder=10,
value = 10,
step=1,
min=1,
id='num_of_replications',
className='col-sm-4'
)
],className='row'), id='number_of_replications_input', style={'display': 'none'})
return html.Div([
input_n_toolkits,
prop_cover,
prop_cover_tooltip,
input_fun_lambda,
coral_size,
coral_size_tooltip,
coral_size_std,
coral_size_std_tooltip,
input_disease_prevalence,
input_disease_prevalence_tooltip,
input_parent_prop,
input_parent_range,
input_strauss_beta,
input_strauss_gamma,
input_strauss_R,
input_transect_length,
input_transect_width,
line_intercept_ratio,
num_of_replications
], id='input_process_parameters') | [
11748,
14470,
62,
7295,
62,
5589,
3906,
355,
288,
535,
198,
11748,
14470,
62,
6494,
62,
5589,
3906,
355,
27711,
198,
11748,
14470,
62,
18769,
26418,
62,
5589,
3906,
355,
288,
15630,
628,
198,
4299,
7716,
62,
14781,
2902,
62,
49283,
33529,
198,
220,
220,
220,
366,
7783,
257,
4777,
7268,
262,
4268,
2902,
6356,
3091,
1,
198,
220,
220,
220,
1441,
288,
535,
13,
26932,
2902,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
14781,
2902,
62,
19738,
62,
14681,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
3918,
28,
4895,
13812,
1298,
366,
23108,
25719,
198,
220,
220,
220,
220,
220,
220,
220,
3689,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
18242,
10354,
705,
28718,
32269,
7695,
30927,
1429,
3256,
705,
8367,
10354,
352,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
18242,
10354,
705,
818,
26452,
32269,
7695,
30927,
1429,
3256,
705,
8367,
10354,
362,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
6,
18242,
10354,
705,
2601,
5819,
1429,
3256,
705,
8367,
10354,
513,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1391,
6,
18242,
10354,
705,
41347,
1046,
1429,
3256,
705,
8367,
10354,
604,
92,
198,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
900,
262,
4238,
1988,
28,
15,
284,
7808,
262,
2836,
5128,
7071,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
28,
15,
8,
628,
198,
198,
4299,
7716,
62,
7220,
62,
15414,
33529,
198,
220,
220,
220,
366,
7783,
257,
4777,
7268,
2985,
6,
5128,
7071,
1,
628,
198,
220,
220,
220,
5128,
62,
77,
62,
25981,
74,
896,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
15057,
286,
491,
272,
8831,
82,
25,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
362,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
15414,
62,
77,
62,
25981,
74,
896,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
1398,
5376,
11639,
808,
33809,
4686,
11639,
15414,
62,
77,
62,
25981,
74,
896,
62,
34924,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
1303,
28982,
198,
220,
220,
220,
1303,
5128,
62,
77,
62,
25981,
74,
896,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
27711,
13,
32,
7203,
15057,
286,
491,
272,
8831,
82,
1600,
4871,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
11122,
1304,
7,
1084,
28,
16,
11,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
28,
20,
11,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
16,
11,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
28,
17,
11,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8849,
34758,
72,
25,
705,
90,
92,
4458,
18982,
7,
72,
8,
329,
1312,
287,
2837,
7,
16,
11,
718,
8,
5512,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
15414,
62,
77,
62,
25981,
74,
896,
3256,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
11537,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
1398,
5376,
11639,
808,
33809,
4686,
11639,
15414,
62,
77,
62,
25981,
74,
896,
62,
34924,
3256,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
808,
3256,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
198,
220,
220,
220,
5128,
62,
67,
786,
589,
62,
3866,
2100,
594,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
67,
786,
589,
16815,
25,
46083,
4686,
11639,
15414,
62,
67,
786,
589,
62,
3866,
2100,
594,
62,
25981,
22504,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
15,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
657,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
15414,
62,
67,
786,
589,
62,
3866,
2100,
594,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
1398,
5376,
11639,
808,
33809,
4686,
11639,
15414,
62,
67,
786,
589,
62,
3866,
2100,
594,
62,
34924,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
5128,
62,
67,
786,
589,
62,
3866,
2100,
594,
62,
25981,
22504,
796,
288,
15630,
13,
25391,
22504,
10786,
1169,
9823,
286,
1162,
874,
543,
651,
14112,
416,
257,
4369,
3256,
2496,
11639,
15414,
62,
67,
786,
589,
62,
3866,
2100,
594,
62,
25981,
22504,
11537,
628,
220,
220,
220,
1303,
2420,
393,
1271,
5128,
198,
220,
220,
220,
5128,
62,
12543,
62,
50033,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
1676,
16864,
3002,
2163,
25,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
12543,
62,
50033,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
5239,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
2625,
12825,
1635,
45941,
13,
11201,
32590,
19510,
7,
87,
532,
2026,
8,
1220,
2026,
8,
12429,
362,
1343,
14808,
88,
532,
2026,
8,
1220,
2026,
8,
12429,
362,
8,
1220,
657,
13,
20,
12429,
362,
42501,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
2625,
12825,
1635,
45941,
13,
11201,
32590,
19510,
7,
87,
532,
2026,
8,
1220,
2026,
8,
12429,
362,
1343,
14808,
88,
532,
2026,
8,
1220,
2026,
8,
12429,
362,
8,
1220,
657,
13,
20,
12429,
362,
42501,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
1267,
4357,
4871,
5376,
11639,
808,
33809,
312,
11639,
12860,
62,
15414,
62,
12543,
62,
50033,
3256,
7635,
34758,
6,
13812,
10354,
6,
23108,
6,
30072,
628,
220,
220,
220,
5128,
62,
8000,
62,
22930,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
8000,
1162,
874,
1220,
2472,
1162,
874,
25,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
8000,
62,
22930,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
15,
13,
486,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
28,
15,
13,
486,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
486,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
1267,
4357,
4871,
5376,
11639,
808,
33809,
312,
11639,
12860,
62,
15414,
62,
8000,
62,
22930,
3256,
7635,
34758,
6,
13812,
10354,
6,
23108,
6,
30072,
628,
220,
220,
220,
5128,
62,
8000,
62,
9521,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
8000,
2837,
25,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
8000,
62,
9521,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
28,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
1267,
4357,
4871,
5376,
11639,
808,
33809,
312,
11639,
12860,
62,
15414,
62,
8000,
62,
9521,
3256,
7635,
34758,
6,
13812,
10354,
6,
23108,
6,
30072,
628,
220,
220,
220,
5128,
62,
12044,
1046,
62,
31361,
796,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
12044,
1046,
62,
31361,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
2625,
12044,
1046,
62,
31361,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
92,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
5128,
62,
12044,
1046,
62,
28483,
2611,
796,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
12044,
1046,
62,
28483,
2611,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
2625,
12044,
1046,
62,
28483,
2611,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
92,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
5128,
62,
12044,
1046,
62,
49,
796,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
4686,
2625,
15414,
62,
12044,
1046,
62,
49,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
46076,
2625,
12044,
1046,
62,
49,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
92,
198,
220,
220,
220,
1267,
628,
220,
220,
220,
5128,
62,
2213,
272,
8831,
62,
13664,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
2213,
272,
8831,
9647,
357,
76,
2599,
46083,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
1495,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
28,
1495,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
67,
535,
62,
15414,
62,
2213,
272,
8831,
62,
13664,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
1398,
5376,
11639,
808,
33809,
4686,
11639,
15414,
62,
2213,
272,
8831,
62,
13664,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
628,
220,
220,
220,
5128,
62,
2213,
272,
8831,
62,
10394,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
2213,
272,
8831,
4129,
357,
76,
2599,
46083,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
718,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
67,
535,
62,
15414,
62,
2213,
272,
8831,
62,
10394,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
1398,
5376,
11639,
808,
33809,
4686,
11639,
15414,
62,
2213,
272,
8831,
62,
10394,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
628,
198,
220,
220,
220,
1627,
62,
3849,
984,
62,
10366,
952,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
2213,
272,
8831,
9647,
1220,
7110,
9647,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
16,
14,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
352,
14,
20,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
67,
535,
62,
1370,
62,
3849,
984,
62,
10366,
952,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
4871,
5376,
11639,
808,
33809,
4686,
11639,
1370,
62,
3849,
984,
62,
10366,
952,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
29537,
62,
7857,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
66,
6864,
2546,
357,
76,
61,
17,
2599,
46083,
4686,
11639,
66,
6864,
62,
7857,
62,
25981,
22504,
3256,
4871,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
15,
13,
405,
3104,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
657,
13,
405,
3104,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
18005,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
66,
6864,
62,
7857,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
4871,
5376,
11639,
808,
6,
10612,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
66,
6864,
62,
7857,
62,
15414,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
29537,
62,
7857,
62,
25981,
22504,
796,
288,
15630,
13,
25391,
22504,
10786,
1169,
2811,
2546,
286,
281,
1981,
29537,
11,
8630,
287,
285,
61,
18,
3256,
2496,
11639,
66,
6864,
62,
7857,
62,
25981,
22504,
11537,
628,
220,
220,
220,
29537,
62,
7857,
62,
19282,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
66,
6864,
2546,
3210,
4049,
25,
46083,
4686,
11639,
66,
6864,
62,
7857,
62,
19282,
62,
25981,
22504,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
15,
13,
8298,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
657,
13,
8298,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
8298,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
66,
6864,
62,
7857,
62,
19282,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
4357,
1398,
5376,
11639,
808,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
837,
4686,
11639,
66,
6864,
62,
7857,
62,
19282,
62,
15414,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
29537,
62,
7857,
62,
19282,
62,
25981,
22504,
796,
288,
15630,
13,
25391,
22504,
10786,
1169,
3210,
28833,
286,
262,
2811,
2546,
286,
281,
1981,
29537,
3256,
2496,
11639,
66,
6864,
62,
7857,
62,
19282,
62,
25981,
22504,
11537,
628,
220,
220,
220,
2632,
62,
9631,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
1676,
16864,
3002,
25,
46083,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
3256,
4686,
11639,
22930,
62,
9631,
62,
25981,
22504,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
15,
13,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
22930,
62,
9631,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
4871,
5376,
11639,
808,
33809,
4686,
11639,
22930,
62,
9631,
62,
15414,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
220,
220,
220,
2632,
62,
9631,
62,
25981,
22504,
796,
288,
15630,
13,
25391,
22504,
10786,
2964,
16864,
3002,
286,
29537,
13,
1002,
340,
21767,
657,
11,
663,
31850,
1912,
319,
262,
6754,
1366,
481,
307,
973,
287,
262,
18640,
3256,
2496,
11639,
22930,
62,
9631,
62,
25981,
22504,
11537,
628,
220,
220,
220,
997,
62,
1659,
62,
35666,
3736,
796,
27711,
13,
24095,
7,
6494,
13,
24095,
26933,
6494,
13,
32,
10786,
17618,
286,
2186,
3736,
3256,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
535,
13,
20560,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11639,
17618,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
46076,
28,
940,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
838,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2239,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
11639,
22510,
62,
1659,
62,
35666,
3736,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1398,
5376,
11639,
4033,
12,
5796,
12,
19,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
4871,
5376,
11639,
808,
33809,
4686,
11639,
17618,
62,
1659,
62,
35666,
3736,
62,
15414,
3256,
3918,
34758,
6,
13812,
10354,
705,
23108,
6,
30072,
628,
198,
220,
220,
220,
1441,
27711,
13,
24095,
26933,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
77,
62,
25981,
74,
896,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2632,
62,
9631,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2632,
62,
9631,
62,
25981,
22504,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
12543,
62,
50033,
11,
198,
220,
220,
220,
220,
220,
220,
220,
29537,
62,
7857,
11,
198,
220,
220,
220,
220,
220,
220,
220,
29537,
62,
7857,
62,
25981,
22504,
11,
198,
220,
220,
220,
220,
220,
220,
220,
29537,
62,
7857,
62,
19282,
11,
198,
220,
220,
220,
220,
220,
220,
220,
29537,
62,
7857,
62,
19282,
62,
25981,
22504,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
67,
786,
589,
62,
3866,
2100,
594,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
67,
786,
589,
62,
3866,
2100,
594,
62,
25981,
22504,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
8000,
62,
22930,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
8000,
62,
9521,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
12044,
1046,
62,
31361,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
12044,
1046,
62,
28483,
2611,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
12044,
1046,
62,
49,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
2213,
272,
8831,
62,
13664,
11,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
2213,
272,
8831,
62,
10394,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
62,
3849,
984,
62,
10366,
952,
11,
198,
220,
220,
220,
220,
220,
220,
220,
997,
62,
1659,
62,
35666,
3736,
198,
220,
220,
220,
16589,
4686,
11639,
15414,
62,
14681,
62,
17143,
7307,
11537
] | 1.63074 | 6,272 |
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# This test is based on the test suite implemented for Recommenders project
# https://github.com/Microsoft/Recommenders/tree/master/tests
import papermill as pm
import pytest
import scrapbook as sb
from utils_cv.common.data import unzip_url
from utils_cv.detection.data import Urls
# Unless manually modified, python3 should be
# the name of the current jupyter kernel
# that runs on the activated conda environment
KERNEL_NAME = "python3"
OUTPUT_NOTEBOOK = "output.ipynb"
| [
2,
15069,
357,
66,
8,
5413,
10501,
13,
1439,
2489,
10395,
13,
198,
2,
49962,
739,
262,
17168,
13789,
13,
198,
198,
2,
770,
1332,
318,
1912,
319,
262,
1332,
18389,
9177,
329,
19237,
7338,
1628,
198,
2,
3740,
1378,
12567,
13,
785,
14,
15905,
14,
24898,
7338,
14,
21048,
14,
9866,
14,
41989,
198,
198,
11748,
3348,
17805,
355,
9114,
198,
11748,
12972,
9288,
198,
11748,
15881,
2070,
355,
264,
65,
198,
198,
6738,
3384,
4487,
62,
33967,
13,
11321,
13,
7890,
1330,
555,
13344,
62,
6371,
198,
6738,
3384,
4487,
62,
33967,
13,
15255,
3213,
13,
7890,
1330,
8799,
7278,
198,
198,
2,
17486,
14500,
9518,
11,
21015,
18,
815,
307,
198,
2,
262,
1438,
286,
262,
1459,
474,
929,
88,
353,
9720,
198,
2,
326,
4539,
319,
262,
13906,
1779,
64,
2858,
198,
42,
28778,
3698,
62,
20608,
796,
366,
29412,
18,
1,
198,
2606,
7250,
3843,
62,
16580,
39453,
796,
366,
22915,
13,
541,
2047,
65,
1,
628,
628,
628
] | 3.512195 | 164 |
_base_ = [
'../retinanet_r50_fpn_1x_coco.py',
'../../_base_/datasets/hdr_detection_minmax_glob_gamma.py',
]
# optimizer
# lr is set for a batch size of 8
optimizer = dict(type='SGD', lr=0.0005, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None) # dict(grad_clip=dict(max_norm=35, norm_type=2))
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[10])
runner = dict(
type='EpochBasedRunner', max_epochs=20)
| [
62,
8692,
62,
796,
685,
198,
220,
220,
220,
705,
40720,
1186,
259,
272,
316,
62,
81,
1120,
62,
69,
21999,
62,
16,
87,
62,
66,
25634,
13,
9078,
3256,
198,
220,
220,
220,
705,
40720,
40720,
62,
8692,
62,
14,
19608,
292,
1039,
14,
71,
7109,
62,
15255,
3213,
62,
1084,
9806,
62,
4743,
672,
62,
28483,
2611,
13,
9078,
3256,
198,
60,
628,
198,
2,
6436,
7509,
198,
2,
300,
81,
318,
900,
329,
257,
15458,
2546,
286,
807,
198,
40085,
7509,
796,
8633,
7,
4906,
11639,
38475,
35,
3256,
300,
81,
28,
15,
13,
830,
20,
11,
12858,
28,
15,
13,
24,
11,
3463,
62,
12501,
323,
28,
15,
13,
18005,
8,
198,
40085,
7509,
62,
11250,
796,
8633,
7,
9744,
62,
15036,
28,
14202,
8,
1303,
8633,
7,
9744,
62,
15036,
28,
11600,
7,
9806,
62,
27237,
28,
2327,
11,
2593,
62,
4906,
28,
17,
4008,
198,
2,
4673,
2450,
198,
14050,
62,
11250,
796,
8633,
7,
198,
220,
220,
220,
2450,
11639,
9662,
3256,
198,
220,
220,
220,
5814,
929,
11639,
29127,
3256,
198,
220,
220,
220,
5814,
929,
62,
270,
364,
28,
4059,
11,
198,
220,
220,
220,
5814,
929,
62,
10366,
952,
28,
15,
13,
8298,
11,
198,
220,
220,
220,
2239,
41888,
940,
12962,
198,
16737,
796,
8633,
7,
198,
220,
220,
220,
2099,
11639,
13807,
5374,
15001,
49493,
3256,
3509,
62,
538,
5374,
82,
28,
1238,
8,
198
] | 2.21097 | 237 |
Subsets and Splits