Comments (2)
@kwon3969 we consider inputs with shape (batch_size, time_steps, input_dim)
. The attention weights (after softmax) have shape (batch_size, time_steps)
. The input_dim
is no longer here. You can only know where the attention is on the time_steps
axis. And not at the input level. This attention mechanism is too simple to give you this information. Does it answer your question?
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Related Issues (20)
- pip install and numpy, keras packages are forced to be uninstalled HOT 1
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