Comments (3)
thushv89
commented on July 23, 2024
Hi,
Though it is allowed in TensorFlow implementation, because of the way the computations are designed in this layer, it is not possible. In short the issue is that, when there's two None dimensions (batch and time dimensions), I cannot use any reshaping within the attention layer as it is currently using.
I'll need to do some research on this topic, there might be a way to achieve this, but with degraded performance.
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thushv89
commented on July 23, 2024
@moazshorbagy This support is available now.
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moazshorbagy
commented on July 23, 2024
@thushv89 Thank you, that's awesome.
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Related Issues (20)
- None Input Shape HOT 3
- Installation failed HOT 1
- TypeError: The added layer must be an instance of class Layer. HOT 2
- AttributeError: 'tuple' object has no attribute '_keras_mask' HOT 1
- AttentionLayer does not support model.save() and load_model() HOT 2
- The vocab size definition for English and French Tokenizers is incorrect HOT 1
- AttributeError: 'tuple' object has no attribute 'layer' HOT 3
- state HOT 1
- Failed to convert object of type HOT 3
- Minor issues - but nothing's broken HOT 12
- TypeError: object of type 'Concatenate' has no len() HOT 3
- Bahdanau attention HOT 2
- Help Required
- Very important!!!! HOT 2
- Masking Support
- I got this error: 'tuple' object has no attribute '_keras_shape' any help please?
- ValueError: The first argument to `Layer.call` must always be passed. HOT 1
- Getting "TypeError: Exception encountered when calling layer "tf.keras.backend.rnn" (type TFOpLambda)" when I employ the Attention Layer HOT 11
- "tf.keras.backend.rnn"
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