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farizrahman4u / seq2seq

Sequence to Sequence Learning with Keras
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A question of dimension of encoded_seq #194

Open lhl881210 opened 7 years ago

lhl881210 commented 7 years ago

Hi, @abhaikollara and @farizrahman4u

I fund the output of encoded is encoded_seq = dense2(encoded_seq), where 'dense2 = Dense(output_dim)'.

In my opinion，the dimension of encoded_seq maybe is hidden_dim.

For example, when input_dim=100, hidden_dim=200, output_dim=4, if dense2 = Dense(output_dim), then the changes of dimensionality will be 100->200->4->200->4. In this case, maybe the decoder will over-learn easily. So, maybe dense2= Dense(hidden_dim) is better in this case.

Maybe I am not quite correct, but I want to know your thinking.

Thanks.

Ekraam commented 7 years ago

My understanding is that dense2 = Dense(output_dim) simply facilitates the transfer of encoder output to the decoder with correct dimensions - since decoder possibly has different dimensions. That said you're right, the encoder output should be of hidden_dim since it is the final hidden state which represents the embedding. The encoder is supposed to end at the layer before dense2. I think the confusion results from the fact that the output of dense2 is later called encoded_seq.