Keras框架（一）：RNN實現mnist分類

由於在使用Tensorflow過程中，老是會碰到Keras框架寫的模型，所以就稍稍學習了哈Keras框架。

主要內容：RNN對mnist數據集進行分類

主要框架：Keras

主要代碼：

# 準備好數據：X_train、X_test、y_train、y_test

model = Sequential()
model.add(SimpleRNN(
    batch_input_shape=(None, TIME_STEPS, INPUT_SIZE),    
    output_dim=CELL_SIZE,
    unroll=True,
))
model.add(Dense(OUTPUT_SIZE))
model.add(Activation('softmax'))

adam = Adam(LR)
model.compile(optimizer=adam,
              loss='categorical_crossentropy',
              metrics=['accuracy'])

for step in range(4001):
    # data shape = (batch_num, steps, inputs/outputs)
    X_batch = X_train[BATCH_INDEX: BATCH_INDEX+BATCH_SIZE, :, :]
    Y_batch = y_train[BATCH_INDEX: BATCH_INDEX+BATCH_SIZE, :]
    cost = model.train_on_batch(X_batch, Y_batch)
    BATCH_INDEX += BATCH_SIZE
    BATCH_INDEX = 0 if BATCH_INDEX >= X_train.shape[0] else BATCH_INDEX

    if step % 500 == 0:
        cost, accuracy = model.evaluate(X_test, y_test, batch_size=y_test.shape[0], verbose=False)
print('test cost: ', cost, 'test accuracy: ', accuracy)