43 lines
1.9 KiB
Python
43 lines
1.9 KiB
Python
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""The implementation of `tf.data.Dataset.unique`."""
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from tensorflow.python.data.ops import dataset_ops
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from tensorflow.python.data.util import nest
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from tensorflow.python.framework import dtypes
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from tensorflow.python.ops import gen_experimental_dataset_ops
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def _unique(input_dataset, name): # pylint: disable=unused-private-name
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return _UniqueDataset(input_dataset, name)
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class _UniqueDataset(dataset_ops.UnaryUnchangedStructureDataset):
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"""A dataset containing the unique elements of an input dataset."""
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def __init__(self, input_dataset, name=None):
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"""See `tf.data.Dataset.unique` for details."""
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self._input_dataset = input_dataset
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for ty in nest.flatten(dataset_ops.get_legacy_output_types(input_dataset)):
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if ty not in (dtypes.int32, dtypes.int64, dtypes.string):
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raise TypeError(
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f"`tf.data.Dataset.unique` does not support type {ty} -- only "
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f"`tf.int32`, `tf.int64`, and `tf.string` are supported.")
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self._name = name
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variant_tensor = gen_experimental_dataset_ops.unique_dataset(
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self._input_dataset._variant_tensor, # pylint: disable=protected-access
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**self._common_args)
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super().__init__(input_dataset, variant_tensor)
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