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updated ReversibleEmbedding call method to handle proper conversion to tensors. #2295

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updated ReversibleEmbedding call method to handle proper conversion to tensors. #2295

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af584b4
Update gemma3_causal_lm_preprocessor.py
pctablet505 Apr 17, 2025
dc4ae8c
Update gemma3_causal_lm_preprocessor.py
pctablet505 Apr 17, 2025
07c5c77
Update gemma3_causal_lm_preprocessor_test.py
pctablet505 Apr 17, 2025
3fdc7fd
Update reversible_embedding.py
pctablet505 Jun 10, 2025
fa57e33
Merge branch 'master' of https://github.com/pctablet505/keras-hub
pctablet505 Jun 10, 2025
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7 changes: 6 additions & 1 deletion keras_hub/src/layers/modeling/reversible_embedding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,12 @@ def build(self, inputs_shape=None):
def call(self, inputs, reverse=False):
if reverse:
if self.tie_weights:
kernel = ops.transpose(ops.convert_to_tensor(self.embeddings))
# Ensure embeddings is properly converted to a tensor
embeddings_tensor = self.embeddings
# If it's a Keras variable, get its value
if hasattr(embeddings_tensor, "value"):
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so what's the error here? embeddings_tensor has no value when tf numpy is enabled? what's the error?

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keras-team/keras@9286df3

I am not able to reproduce the error, it has been fixed in the above commit on keras.

embeddings_tensor = embeddings_tensor.value
kernel = ops.transpose(ops.convert_to_tensor(embeddings_tensor))
else:
kernel = self.reverse_embeddings
if self.reverse_dtype is not None:
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