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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"""Experimental API for gathering statistics from `tf.data` pipelines."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20from tensorflow.python.data.ops import dataset_ops
21from tensorflow.python.framework import dtypes
22from tensorflow.python.framework import ops
23from tensorflow.python.ops import gen_experimental_dataset_ops
24from tensorflow.python.util import deprecation
25from tensorflow.python.util.tf_export import tf_export
26
27
28@deprecation.deprecated(None, "Use `tf.data.experimental.StatsOptions`.")
29def set_stats_aggregator(stats_aggregator, prefix="", counter_prefix=""):
30  """Set the given `stats_aggregator` for aggregating the input dataset stats.
31
32  Args:
33    stats_aggregator: A `tf.contrib.data.StatsAggregator` object.
34    prefix: (Optional) String, all statistics recorded for the input `dataset`
35      will have given `prefix` prepend with the name.
36    counter_prefix: (Optional) String, all statistics recorded as `counters`
37      will have the given `prefix` for the counter. Defaults to "/tensorflow".
38
39  Returns:
40    A `Dataset` transformation function, which can be passed to
41    `tf.data.Dataset.apply`.
42  """
43
44  def _apply_fn(dataset):
45    return dataset_ops._SetStatsAggregatorDataset(  # pylint: disable=protected-access
46        dataset, stats_aggregator, prefix, counter_prefix)
47
48  return _apply_fn
49
50
51@tf_export("data.experimental.bytes_produced_stats")
52def bytes_produced_stats(tag):
53  """Records the number of bytes produced by each element of the input dataset.
54
55  To consume the statistics, associate a `StatsAggregator` with the output
56  dataset.
57
58  Args:
59    tag: String. All statistics recorded by the returned transformation will
60      be associated with the given `tag`.
61
62  Returns:
63    A `Dataset` transformation function, which can be passed to
64    `tf.data.Dataset.apply`.
65  """
66
67  def _apply_fn(dataset):
68    return _StatsDataset(
69        dataset,
70        gen_experimental_dataset_ops.experimental_bytes_produced_stats_dataset,
71        tag)
72
73  return _apply_fn
74
75
76@tf_export("data.experimental.latency_stats")
77def latency_stats(tag):
78  """Records the latency of producing each element of the input dataset.
79
80  To consume the statistics, associate a `StatsAggregator` with the output
81  dataset.
82
83  Args:
84    tag: String. All statistics recorded by the returned transformation will
85      be associated with the given `tag`.
86
87  Returns:
88    A `Dataset` transformation function, which can be passed to
89    `tf.data.Dataset.apply`.
90  """
91
92  def _apply_fn(dataset):
93    return _StatsDataset(
94        dataset,
95        gen_experimental_dataset_ops.experimental_latency_stats_dataset, tag)
96
97  return _apply_fn
98
99
100class _StatsDataset(dataset_ops.UnaryUnchangedStructureDataset):
101  """A `Dataset` that acts as an identity, and also records statistics."""
102
103  def __init__(self, input_dataset, op_function, tag):
104    self._input_dataset = input_dataset
105    self._op_function = op_function
106    self._tag = ops.convert_to_tensor(tag, dtype=dtypes.string)
107    variant_tensor = self._op_function(
108        self._input_dataset._variant_tensor,  # pylint: disable=protected-access
109        self._tag,
110        **dataset_ops.flat_structure(self))
111    super(_StatsDataset, self).__init__(input_dataset, variant_tensor)
112