55 lines
1.8 KiB
Python
55 lines
1.8 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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"""Enumerate dataset transformations."""
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from tensorflow.python.util import deprecation
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from tensorflow.python.util.tf_export import tf_export
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@deprecation.deprecated(None, "Use `tf.data.Dataset.enumerate()`.")
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@tf_export("data.experimental.enumerate_dataset")
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def enumerate_dataset(start=0):
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"""A transformation that enumerates the elements of a dataset.
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It is similar to python's `enumerate`.
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For example:
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```python
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# NOTE: The following examples use `{ ... }` to represent the
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# contents of a dataset.
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a = { 1, 2, 3 }
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b = { (7, 8), (9, 10) }
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# The nested structure of the `datasets` argument determines the
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# structure of elements in the resulting dataset.
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a.apply(tf.data.experimental.enumerate_dataset(start=5))
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=> { (5, 1), (6, 2), (7, 3) }
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b.apply(tf.data.experimental.enumerate_dataset())
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=> { (0, (7, 8)), (1, (9, 10)) }
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```
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Args:
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start: A `tf.int64` scalar `tf.Tensor`, representing the start value for
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enumeration.
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Returns:
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A `Dataset` transformation function, which can be passed to
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`tf.data.Dataset.apply`.
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"""
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def _apply_fn(dataset):
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return dataset.enumerate(start)
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return _apply_fn
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