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Results 1 - 3 of 3 for replace_tensors_by_numpy_ndarrays (0.38 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/python/representative_dataset_test.py
{ 'input_tensor': ops.convert_to_tensor(sample), } for sample in samples ] with self.session() as sess: new_repr_ds = repr_dataset.replace_tensors_by_numpy_ndarrays( repr_ds, sess ) # The resulting dataset should not contain any tf.Tensors. self.assertFalse(any(map(_contains_tensor, new_repr_ds)))
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jan 04 07:35:19 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/representative_dataset.py
# numpy ndarray types to be compatible with `make_tensor_proto`. if not context.executing_eagerly(): with session.Session() as sess: repr_ds = replace_tensors_by_numpy_ndarrays(repr_ds, sess) expected_input_keys = self.expected_input_key_map.get( signature_def_key, None ) tfrecord_file_path = self.path_map[signature_def_key]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 14.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/py_function_lib.py
# Replaces the dataset with a new dataset where tf.Tensors are replaced # by their evaluated values. ds = repr_ds_map[signature_def_key] repr_ds_map[signature_def_key] = rd.replace_tensors_by_numpy_ndarrays( ds, sess ) def _create_sample_validator( expected_input_keys: Collection[str], ) -> Callable[[rd.RepresentativeSample], rd.RepresentativeSample]:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 05:32:11 UTC 2024 - 27.4K bytes - Viewed (0)