Comments (3)
thushv89
commented on July 3, 2024
Hi @sagar-spkt ,
Can you elaborate on what sort of masking you are referring to?
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adrian-dalessandro
commented on July 3, 2024
Hey @thushv89,
there problem that @sagar-spkt is referring to is masking with respect to LSTM sequence length. It's the way Keras lets you control the input of variable length sequences.
You can read about it here: https://www.tensorflow.org/guide/keras/masking_and_padding#supporting_masking_in_your_custom_layers
It's actually not too difficult to implement at the layer level.
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thushv89
commented on July 3, 2024
Thanks. I'll have a look into this this week. I was busy with some other work and really didn't have time to look into this repo.
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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
- Support for using None in sequence length HOT 3
- 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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