TensorFlowでkeras その11

2165 ワード
FizzBuzz Keras2.0 TensorFlow1.2 FizzBuzz テキストリンク

概要

TensorFlowでkerasやってみた。
fizzbuzz学習してみた。

写真

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
from tensorflow.contrib.keras.python.keras.layers import Dense, Activation
from tensorflow.contrib.keras.python.keras.models import Model

def binary_encode(i, num_digits):
    return np.array([i >> d & 1 for d in range(num_digits)])

def fizz_buzz_encode(i):
    if i % 15 == 0:
        return np.array([0, 0, 0, 1])
    elif i % 5  == 0:
        return np.array([0, 0, 1, 0])
    elif i % 3  == 0:
        return np.array([0, 1, 0, 0])
    else:
        return np.array([1, 0, 0, 0])

def fizz_buzz(i, prediction):
    return [str(i), "fizz", "buzz", "fizzbuzz"][prediction]

NUM_DIGITS = 10
trX = np.array([binary_encode(i, NUM_DIGITS) for i in range(101, 2 ** NUM_DIGITS)])
trY = np.array([fizz_buzz_encode(i) for i in range(101, 2 ** NUM_DIGITS)])

model = Sequential()
model.add(Dense(128, input_dim = 10))
model.add(Activation('tanh'))
model.add(Dense(4, input_dim = 128))
model.add(Activation('softmax'))
model.compile(loss = 'categorical_crossentropy', optimizer = 'adam', metrics = ['accuracy'])
model.fit(trX, trY, epochs = 3600, batch_size = 128)
f = open('fizzbuzz2.json', 'w')
f.write(model.to_json())
model.save('fizzbuzz2.hdf5')
print ("save model")

numbers = np.arange(1, 101)
teX = np.array([binary_encode(i, NUM_DIGITS) for i in range(1, 101)])
teY = np.array([fizz_buzz_encode(i) for i in range(1, 101)])
score = model.evaluate(teX, teY, verbose = 0)
print ('Test loss    : {:>.4f}'.format(score[0]))
print ('Test accuracy: {:>.4f}'.format(score[1]))