Comments (3)
Thanks for the issue. The VAE example is a little staled. @jxhe will fix this soon.
The memory
argument of TransformerDecoder
is of shape [batch_size, max_memory_length, hidden_dim]
(see the doc) so the decoder can attend to the whole sequence of encoder.
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Sorry the VAE example is a bit out of date, I'm fixing it now. To quickly answer, the output from encoder should be expanded to shape [batch_size, 1, hidden_dim]
as the memory
argument of TransformerDecoder
. A clean way to do this is to set decoder_initial_state_size
argument as [1, hidden_dim]
when defining ReparameterizedStochasticConnector
(see vae_train.py). We will update the vae example soon and show the specific usage.
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Code is now fixed.
So the essential idea is to set max_memory_length=1
in the VAE case.
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