Comments (1)
Sum02dean
commented on May 19, 2024
I believe that I should apply an attention layer to each of the encoder states, prior to concatenation. However, the question of how to tie the encoding attention to the decoding states remains hm.
from keras-attention.
Related Issues (20)
- Can I visualize features selected from image sequence data HOT 1
- Instability during training
- Working with real output HOT 1
- Vanishing Gradient Problem Occurred During Training HOT 4
- Attention Decoder for OutputDimension in tens of thousands. HOT 2
- Attention probabilites HOT 1
- How to apply beam search ? HOT 3
- Significance of resetting states
- Concatenate two AttentionDecoders raise ValueError HOT 1
- An operation has `None` for gradient
- ValueError and TypeError in the custom_recurrents.py
- attention mode
- how to use pre-trained word embedding
- Variable Input and Output Sequnce Time Series Data
- How do I pass the output of AttentionDecoder to an RNN layer. HOT 4
- Bad results HOT 1
- cannot import name 'Layer' from 'keras.engine' HOT 1
- cannot import name 'Recurrent' from 'keras.layers.recurrent' HOT 7
- Recurrent layer is no longer supported by keras
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from keras-attention.