![]() a function with no parameters now automatically has input_signature=).Īdditionally, we have added experimental.extension_type.as_dict() to convert tf.experimental.ExtensionTypes to Python dicts. Additionally, we have improved type constraining logic ( input_signature) for better error messages and consistency (e.g. We now detect incompatible tf.function input types (such as mismatched functools.wraps calls). WYSIWYG: decorated and non-decorated behavior is identical, even for complex uses like wrapping ( functools.wraps) and partial application ( functools.partial). Tf.function now uses the Python inspect library to consistently mimic the decorated function’s signature. ![]() Read more about fingerprinting in the RFC and check out the read_fingerprint API and Fingerprint class. ![]() Multiple fingerprints are derived from the model content, allowing you to compare the structure, graph, signatures, and weights across models. Models saved with tf.saved_model.save now come with a fingerprint file containing hashes to uniquely identify the SavedModel. TensorFlow Core SavedModel Fingerprinting
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