58 lines
2.3 KiB
Python
58 lines
2.3 KiB
Python
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# 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.zip`."""
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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.ops import gen_dataset_ops
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def _zip(datasets, name): # pylint: disable=redefined-builtin
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return _ZipDataset(datasets, name)
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class _ZipDataset(dataset_ops.DatasetV2):
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"""A `Dataset` that zips its inputs together."""
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def __init__(self, datasets, name=None):
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"""See `Dataset.zip()` for details."""
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for ds in nest.flatten(datasets):
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if not isinstance(ds, dataset_ops.DatasetV2):
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if isinstance(ds, list):
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raise TypeError("Invalid `datasets`. `datasets` is expected to be a "
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"(nested) structure of `tf.data.Dataset` objects. "
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"Python `list` is not supported and you should use "
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"`tuple` instead.")
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else:
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raise TypeError(f"Invalid `datasets`. `datasets` is expected to be a "
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f"(nested) structure of `tf.data.Dataset` objects "
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f"but encountered object of type {type(ds)}.")
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self._datasets = datasets
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self._structure = nest.pack_sequence_as(
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self._datasets,
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[ds.element_spec for ds in nest.flatten(self._datasets)])
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self._name = name
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variant_tensor = gen_dataset_ops.zip_dataset(
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[ds._variant_tensor for ds in nest.flatten(self._datasets)],
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**self._common_args)
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super().__init__(variant_tensor)
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def _inputs(self):
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return nest.flatten(self._datasets)
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@property
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def element_spec(self):
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return self._structure
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