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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorboardX import SummaryWriter
import numpy as np
import pytest
import unittest
import tensorboardX.beholder as beholder_lib
import tensorboardX.beholder.file_system_tools as fio
from collections import namedtuple
class BeholderTest(unittest.TestCase):
def test_beholder(self):
LOG_DIRECTORY = '/tmp/beholder-demo'
tensor_and_name = namedtuple('tensor_and_name', 'tensor, name')
fake_param = [tensor_and_name(np.random.randn(128, 768, 3), 'test' + str(i)) for i in range(5)]
arrays = [tensor_and_name(np.random.randn(128, 768, 3), 'test' + str(i)) for i in range(5)]
beholder = beholder_lib.Beholder(logdir=LOG_DIRECTORY)
beholder.update(
trainable=fake_param,
arrays=arrays,
frame=np.random.randn(128, 128),
)
def test_beholder_video(self):
LOG_DIRECTORY = '/tmp/beholder-demo-recording'
tensor_and_name = namedtuple('tensor_and_name', 'tensor, name')
fake_param = [tensor_and_name(np.random.randn(128, 768, 3), 'test' + str(i)) for i in range(5)]
arrays = [tensor_and_name(np.random.randn(128, 768, 3), 'test' + str(i)) for i in range(5)]
beholder = beholder_lib.Beholder(logdir=LOG_DIRECTORY)
pkl = fio.read_pickle(LOG_DIRECTORY + '/plugins/beholder/config.pkl')
pkl['is_recording'] = True
fio.write_pickle(pkl, LOG_DIRECTORY + '/plugins/beholder/config.pkl')
for i in range(3):
if i == 2:
pkl = fio.read_pickle(LOG_DIRECTORY + '/plugins/beholder/config.pkl')
pkl['is_recording'] = False
fio.write_pickle(pkl, LOG_DIRECTORY + '/plugins/beholder/config.pkl')
beholder.update(
trainable=fake_param,
arrays=arrays,
frame=np.random.randn(128, 128),
)
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