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3.TensorBoardを使えるようにする
TensorBoardを起動するためには、事前に学習した結果のログ
が必要なため、第3回の「not.py」にログ出力を仕込みます
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import SGD
import keras.callbacks
model = Sequential( [ Dense( input_dim = 1, units = 1 ), Activation( 'sigmoid' ) ] )
model.compile( loss = 'binary_crossentropy', optimizer = SGD( lr = 0.1 ) )
tensorboard = keras.callbacks.TensorBoard( log_dir = './log', histogram_freq = 1 )
callback_tensorboard = [ tensorboard ]
input = np.array( [ [ 0 ], [ 1 ] ] )
expected = np.array( [ [ 1 ], [ 0 ] ] )
model.fit( input, expected, epochs = 200, batch_size = 1, callbacks = callback_tensorboard,
validation_data = ( input, expected ) )
print()
classes = model.predict_classes( input, batch_size = 1 )
print( '###### classes ######' )
print( classes )
probably = model.predict_proba( input, batch_size = 1 )
print( '###### probably ######' )
print( probably )