x_train
和y_train
是我的模型的输入和输出,其形状分别为(6508, 500, 5), (6508, 5)
。你知道吗
模型是这样的:
model = Sequential()
model.add(LSTM(units=96, return_sequences=True, input_shape=x_train.shape[1:]))
model.add(Dropout(0.2))
model.add(LSTM(units=96, return_sequences=True))
model.add(Dropout(0.2))
model.add(LSTM(units=96))
model.add(Dropout(0.2))
model.add(Dense(units=5))
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['mse'])
model.fit(x_train, y_train, epochs=epochs, batch_size=batch_size)
模型摘要:
Model: "sequential_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
lstm_1 (LSTM) (None, 500, 96) 39168
_________________________________________________________________
dropout_1 (Dropout) (None, 500, 96) 0
_________________________________________________________________
lstm_2 (LSTM) (None, 500, 96) 74112
_________________________________________________________________
dropout_2 (Dropout) (None, 500, 96) 0
_________________________________________________________________
lstm_3 (LSTM) (None, 96) 74112
_________________________________________________________________
dropout_3 (Dropout) (None, 96) 0
_________________________________________________________________
dense_1 (Dense) (None, 5) 485
=================================================================
Total params: 187,877
Trainable params: 187,877
Non-trainable params: 0
问题是lstm_1
需要输入形状(500,2),而我的数据形状是(500,5):
ValueError: Error when checking input: expected lstm_1_input to have shape (500, 2) but got array with shape (500, 5)
我打印图层的形状:
for layer in model.layers:
print(layer.input_shape, end='\t')
# (None, 500, 5) (None, 500, 96) (None, 500, 96) (None, 500, 96) (None, 500, 96) (None, 96) (None, 96)
它为lstm_1
打印(None, 500, 5)
,所以我无法找出问题所在。你知道吗
Keras==2.3.0
tf==1.14.0
更新:
使用keras==2.2.5
或tf.keras
解决了这个问题。你知道吗
为了社区的利益,在回答部分提到解决方案。你知道吗
用
tf.keras
代替keras
解决了这个问题。你知道吗相关问题 更多 >
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