61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
# Copyright 2017 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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"""Datasets for random number generators."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import functools
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from tensorflow.python import tf2
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from tensorflow.python.data.ops import dataset_ops
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from tensorflow.python.data.util import random_seed
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import tensor_spec
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from tensorflow.python.ops import gen_experimental_dataset_ops
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from tensorflow.python.util.tf_export import tf_export
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@tf_export("data.experimental.RandomDataset", v1=[])
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class RandomDatasetV2(dataset_ops.DatasetSource):
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"""A `Dataset` of pseudorandom values."""
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def __init__(self, seed=None):
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"""A `Dataset` of pseudorandom values."""
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self._seed, self._seed2 = random_seed.get_seed(seed)
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variant_tensor = gen_experimental_dataset_ops.random_dataset(
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seed=self._seed, seed2=self._seed2, **self._flat_structure)
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super(RandomDatasetV2, self).__init__(variant_tensor)
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@property
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def element_spec(self):
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return tensor_spec.TensorSpec([], dtypes.int64)
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@tf_export(v1=["data.experimental.RandomDataset"])
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class RandomDatasetV1(dataset_ops.DatasetV1Adapter):
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"""A `Dataset` of pseudorandom values."""
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@functools.wraps(RandomDatasetV2.__init__)
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def __init__(self, seed=None):
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wrapped = RandomDatasetV2(seed)
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super(RandomDatasetV1, self).__init__(wrapped)
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if tf2.enabled():
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RandomDataset = RandomDatasetV2
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else:
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RandomDataset = RandomDatasetV1
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