1# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15"""Enumerate dataset transformations."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import numpy as np
21
22from tensorflow.python.data.ops import dataset_ops
23from tensorflow.python.framework import dtypes
24
25
26def enumerate_dataset(start=0):
27  """A transformation that enumerate the elements of a dataset.
28
29  It is Similar to python's `enumerate`.
30  For example:
31
32  ```python
33  # NOTE: The following examples use `{ ... }` to represent the
34  # contents of a dataset.
35  a = { 1, 2, 3 }
36  b = { (7, 8), (9, 10) }
37
38  # The nested structure of the `datasets` argument determines the
39  # structure of elements in the resulting dataset.
40  a.apply(tf.contrib.data.enumerate(start=5)) == { (5, 1), (6, 2), (7, 3) }
41  b.apply(tf.contrib.data.enumerate()) == { (0, (7, 8)), (1, (9, 10)) }
42  ```
43
44  Args:
45    start: A `tf.int64` scalar `tf.Tensor`, representing the start
46      value for enumeration.
47
48  Returns:
49    A `Dataset` transformation function, which can be passed to
50    @{tf.data.Dataset.apply}.
51  """
52
53  def _apply_fn(dataset):
54    max_value = np.iinfo(dtypes.int64.as_numpy_dtype).max
55    return dataset_ops.Dataset.zip((dataset_ops.Dataset.range(start, max_value),
56                                    dataset))
57
58  return _apply_fn
59