Support of TensorFlow 2.13 #76
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conv_utils module has been moved again in TF 2.13, and can be imported as in TF <= 2.5. The error raised is ImportError, which was added to the try/except clause. ModuleNotFoundError is a subclass of ImportError; it is then removed.
… TF2.13 It seems that (de)serialization of h5 models in TF 2.13 has been changed: custom objects, even with "register_keras_serializable", cannot be loaded. Two solutions are possible: - use "with_custom_object_scope()" to load a model with custom objects. - save model in Keras format and not h5. The second option was chosen because this format is now preferred for saving models.
The power iteration test for Dense was sometimes failing due to a random choice of kernel and initialization vector u. Even if np.random.seed(42) was set at the beginning of the file. To ensure a fully deterministic test (deterministic kernel and initialization u), a random generator np.random.default_rng(42) was created and used to create both kernel and u. The results for Dense test are then deterministic, either for a single test file or for the whole unittest. Note that this is the only test modified; other tests of the file pass, they have not been changed with deterministic initializations.
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thib-s
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Aug 21, 2023
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TensorFlow 2.13 introduces three problems raising errors in unit tests:
conv_utilsfrom Keras, required for our convolutional layers, has been moved (again) in a different Keras folder. Depending on TF version, we import this module from different paths..kerasformat is now preferred, instead of h5 format.