<s> import matplotlib . pyplot as plt <EOL> import logging <EOL> logger = logging . getLogger ( __name__ ) <EOL> import os <EOL> import numpy as np <EOL> import theano <EOL> from pynet . datasets . dataset import SingleBlock , DataBlocks <EOL> from pynet . utils . utils import make_one_hot <EOL> class I2R_Posterior_Blocks_ClnDNN_CleanFeat ( DataBlocks ) : <EOL> def __init__ ( self , feature_size , target_size , ** kwargs ) : <EOL> """<STR_LIT>""" <EOL> dir = '<STR_LIT>' <EOL> self . data_paths = [ ( '<STR_LIT>' % ( dir , i ) , '<STR_LIT>' % ( dir , i ) ) for i in xrange ( <NUM_LIT:1> ) ] <EOL> super ( I2R_Posterior_Blocks_ClnDNN_CleanFeat , self ) . __init__ ( feature_size = feature_size , <EOL> target_size = target_size , <EOL> data_paths = self . data_paths , <EOL> ** kwargs ) <EOL> class I2R_Posterior_Blocks_ClnDNN_NoisyFeat ( DataBlocks ) : <EOL> def __init__ ( self , feature_size , target_size , one_hot = True , num_blocks = <NUM_LIT:30> , ** kwargs ) : <EOL> """<STR_LIT>""" <EOL> dir = '<STR_LIT>' <EOL> if one_hot : <EOL> self . data_paths = [ ( '<STR_LIT>' % ( dir , i ) , '<STR_LIT>' % ( dir , i ) ) for i in xrange ( num_blocks ) ] <EOL> else : <EOL> self . data_paths = [ ( '<STR_LIT>' % ( dir , i ) , '<STR_LIT>' % ( dir , i ) ) for i in xrange ( num_blocks ) ] <EOL> super ( I2R_Posterior_Blocks_ClnDNN_NoisyFeat , self ) . __init__ ( feature_size = feature_size , <EOL> target_size = target_size , <EOL> data_paths = self . data_paths , <EOL> ** kwargs ) <EOL> class I2R_Posterior_Gaussian_Noisy_Sample ( SingleBlock ) : <EOL> def __init__ ( self , ** kwargs ) : <EOL> dir = '<STR_LIT>' <EOL> with open ( '<STR_LIT>' % dir ) as yin : <EOL> y = np . load ( yin ) <EOL> y_tmp = [ ] <EOL> for e in y : <EOL> if e > <NUM_LIT> : <EOL> y_tmp . append ( e ) <EOL> y_tmp = np . asarray ( y_tmp ) <EOL> y_tmp = make_one_hot ( y_tmp , <NUM_LIT> ) <EOL> super ( I2R_Posterior_Gaussian_Noisy_Sample , self ) . __init__ ( X = y_tmp , y = y_tmp , ** kwargs ) <EOL> class I2R_Posterior_NoisyFeat_Sample ( SingleBlock ) : <EOL> def __init__ ( self , ** kwargs ) : <EOL> dir = '<STR_LIT>' <EOL> with open ( '<STR_LIT>' % dir ) as yin , open ( '<STR_LIT>' % dir ) as Xin : <EOL> y = np . load ( yin ) <EOL> y = make_one_hot ( y , <NUM_LIT> ) <EOL> X = np . load ( Xin ) <EOL> super ( I2R_Posterior_NoisyFeat_Sample , self ) . __init__ ( X = X , y = y , ** kwargs ) </s>
