Batch Embedding about keras

[fchollet]

Embedding layers work fine with batches (see the imdb_lstm.py example, where batch_size=16). Can you post your model and explain what you were trying to do?

[lemuriandezapada]

Sorry I'm new to this whole reporting thing, so please bear with me :)
I already changed the code I reported here to something else, but if you go to the imdb_lstm.py example and replace:

model.add(LSTM(256, 128))

with

model.add(Dense(256, 128))

you get this error, with batch sizes that are not equal to the second dimension of the dataset. Maybe I'm wrong but removing recurrency shouldn't affect the model's functionality so much.

But if you also go on and replace:

model.add(Embedding(max_features, 256))

with

model.add(Dense(maxlen, 256))

then it works. I suspect it's something about how the embedding layer indexes its vectors. But maybe I'm just missing something. Ideas?

[lemuriandezapada]

Nevermind, I figured it out eventually: moving from embedding/feedforward/recurrent requires a lot of reshape and flatten inbetween.