Question

我正在尝试复制example on Keras's website：

# as the first layer in a Sequential model
model = Sequential()
model.add(LSTM(32, input_shape=(10, 64)))
# now model.output_shape == (None, 32)
# note: `None` is the batch dimension.

# for subsequent layers, no need to specify the input size:
model.add(LSTM(16))

但是当我运行以下内容时：

# only lines I've added: 
from keras.models import Sequential    
from keras.layers import Dense, LSTM  

# all else is the same: 
model = Sequential()
model.add(LSTM(32, input_shape=(10, 64)))
model.add(LSTM(16))

但是，我得到以下内容：
ValueError: Input 0 is incompatible with layer lstm_4: expected ndim=3, found ndim=2

版本：

Keras:      '2.0.5'  
Python:     '3.4.3'  
Tensorflow: '1.2.1'

Answer 1

LSTM图层作为默认选项必须仅返回序列的最后一个输出。这就是为什么你的数据失去其顺序性质的原因。为了改变这种尝试：

model.add(LSTM(32, input_shape=(10, 64), return_sequences=True))

是什么让LSTM返回整个预测序列。

Keras Layer LSTM中的输入不兼容

1 个答案: