Input 0 is incompatible with layer lstm_1: expected ndim=3, found ndim=4

Here’s the code I’ve written:

model.add(LSTM(150,
               input_shape=(64, 7, 339),
               return_sequences=False))
model.add(Dropout(0.2))

model.add(LSTM(
    200,
    return_sequences=True))
model.add(Dropout(0.2))

model.add(LSTM(
    150,
    return_sequences=True))
model.add(Dropout(0.2))

model.add(Dense(
    output_dim=1))
model.add(Activation('sigmoid'))

start = time.time()
model.compile(loss='mse', optimizer='rmsprop')
print('compilation time : ', time.time() - start)

model.fit(
    trainX,
    trainY_Buy,
    batch_size=64,
    nb_epoch=10,
    verbose=1,
    validation_split=0.05)

the error i’m getting is this: ValueError: Input 0 is incompatible with layer lstm_1: expected ndim=3, found ndim=4 on this line: model.add(LSTM(150, input_shape=(64, 7, 339), return_sequences=False))

my X shape is: (492, 7, 339) my Y shape is: (492,)

anyone have any ideas on what I’m doing wrong?

[td2014]

@ajanaliz . You may need to turn “return_sequences=True” in the first layer. Maybe that will solve it. I hope that works. Thanks.

[td2014]

@ajanaliz . I took a quick look, and I believe that you need to remove the leading “64” from the input shape of the LSTM layer --> input_shape=(64, 7, 339), --> input_shape=(7, 339). Keras’ convention is that the batch dimension (number of examples (not the same as timesteps)) is typically omitted in the input_shape arguments. The batching (number of examples per batch) is handled in the fit call. I hope that helps. Thanks.