When using the keras feature model.summary() it shows me the tensor shapes of my model which is very nice!
Unfortunately, when using a encoder LSTM, called with the keras.layers.LSTM constructor with the property return_states=True, the summary is not displayed in its full form. It looks something like this:
Layer (type) Output Shape Param # Connected to
==================================================================================================
input (InputLayer) (None, 34, 30) 0
__________________________________________________________________________________________________
encoder (LSTM) [(None, 34, 30), (No 7320 input[0][0]
__________________________________________________________________________________________________
lambda_8 (Lambda) (None, 34, 15) 0 encoder[0][0]
__________________________________________________________________________________________________
decoder (LSTM) (None, 34, 30) 5520 lambda_8[0][0]
encoder[0][1]
encoder[0][2]
==================================================================================================
Total params: 12,840
Trainable params: 12,840
Non-trainable params: 0
__________________________________________________________________________________________________
As you can see the output shape of the encoder is cut off and only the first of the three shapes is visible. Is there a way to display it, maybe a fix or even a workaround? :)
Found a workaround:
print(encoder.output_shape)
>> [(None, 34, 30), (None, 30), (None, 30)]