Comments (3)
Same error
I've tried on nmt
model from examples
directory on TF 1.15 and 1.12
Have you figured out why is that and how to solve this?
from attention_keras.
I got the same error while using the attention_layer. Did you guys found the solution to it..??
I am using TF 2.0
please comment back the solution. Thanks..
from attention_keras.
I have found a solution for this problem, If you want to load a model that includes custom layers, custom classes or functions, you can pass them to the loading mechanism via the custom_objects.
I just added the following to my code and it worked:
custom_objects = {
'AttentionLayer': AttentionLayer
}
model = load_model(model_path, custom_objects=custom_objects)
from attention_keras.
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
- 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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