TensorFlowでkeras その2

概要

TnsorFlowでkerasやってみた。
xorを学習してみた。
save,loadしてみた。

環境

windows 7 sp1 64bit
anaconda3
tensorflow 1.2

サンプルコード

import numpy as np 
from tensorflow.contrib.keras.python.keras.models import Sequential, model_from_json
from tensorflow.contrib.keras.python.keras.layers.core import Dense, Activation
from tensorflow.contrib.keras.python.keras.optimizers import SGD
import os.path

X = np.array([[0, 0], [0, 1.0], [1.0, 0], [1.0, 1.0]])
y = np.array([[1.0], [0], [0], [1.0]])

model = Sequential()
model.add(Dense(8, input_dim = 2))
model.add(Activation('tanh'))
model.add(Dense(1))
model.add(Activation('sigmoid'))
sgd = SGD(lr = 0.1)
model.compile(loss = 'binary_crossentropy', optimizer = sgd)
model.fit(X, y, batch_size = 1, epochs = 300)
model.summary();
print (model.predict_proba(X))

print ('save model')
json_string = model.to_json()
open(os.path.join('./', 'xor_model.json'), 'w').write(json_string)
yaml_string = model.to_yaml()
open(os.path.join('./', 'xor_model.yaml'), 'w').write(yaml_string)
print ('save weights')
model.save_weights(os.path.join('./', 'xor_model.h5'))

model1 = model_from_json(open(os.path.join('./', 'xor_model.json')).read())
model1.load_weights(os.path.join('./', 'xor_model.h5'))
model1.summary();
model1.compile(loss = 'binary_crossentropy', optimizer = 'sgd')
score = model1.evaluate(X, y, verbose = 0)
print (score)
print (model1.predict_proba(X))