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vq_vae.py is getting failed while running with Keras 3 (in both cases - without any changes and with keras 3 backend agnostic changes) because of tensorflow_probability. It seems tensorflow_probability is not compatible with Keras 3.
AttributeError: module 'tensorflow._api.v2.compat.v2.__internal__' has no attribute 'register_load_context_function'. Did you mean: 'register_call_context_function'?
Standalone code to reproduce the issue or tutorial link
Simply running vq_vae.py with Keras 3 will produce this error.
Relevant log output
No response
The text was updated successfully, but these errors were encountered:
Vector-Quantized Variational Autoencoders is not migrated to Keras 3 yet, if you're interested in contributing to the migration, please feel free to create a PR. Thanks!
Vector-Quantized Variational Autoencoders is not migrated to Keras 3 yet, if you're interested in contributing to the migration, please feel free to create a PR. Thanks!
Yes, I was working on that only but since it is throwing error for Tensorflow-probability, I raised this issue. I think Tensorflow-probability is not compatible with Keras 3 and it is required for this example. Please let me know if you have any workaround for this.
Issue Type
Bug
Source
source
Keras Version
Keras 3.5.0
Custom Code
No
OS Platform and Distribution
Mac OS Sonoma 14.6.1
Python version
3.10.9
GPU model and memory
No response
Current Behavior?
vq_vae.py is getting failed while running with Keras 3 (in both cases - without any changes and with keras 3 backend agnostic changes) because of tensorflow_probability. It seems tensorflow_probability is not compatible with Keras 3.
AttributeError: module 'tensorflow._api.v2.compat.v2.__internal__' has no attribute 'register_load_context_function'. Did you mean: 'register_call_context_function'?
Standalone code to reproduce the issue or tutorial link
Relevant log output
No response
The text was updated successfully, but these errors were encountered: