updated ReversibleEmbedding call method to handle proper conversion to tensors.
#2295
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Added checks for invalid inputs
Added tests to check invalid inputs
Fix for model not loading when using numpy behaviour with tensorflow
This was referenced Jun 10, 2025
pctablet505
added
kokoro:force-run
mattdangerw
reviewed
Jun 13, 2025
| # 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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What does this PR do?
Ensures that the
callmethod ofReversibleEmbeddingalways converts its input to a TensorFlow tensor. This change improves compatibility when TensorFlow's NumPy behavior is enabled (tf.experimental.numpy.experimental_enable_numpy_behavior), which can cause type inconsistencies if inputs are not explicitly converted.Why is this needed?
Previously, when NumPy behavior was enabled, the input to
ReversibleEmbeddingcould be a numpy array rather than a tensor, leading to errors during model inference or weight loading. This fix resolves failures such as those observed in keras-hub#2136 and ensures robust operation regardless of backend configuration.Related Issues/PRs
How was this tested?