71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
# Copyright 2018 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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"""StatsOptions to configure stats aggregation options for `tf.data` pipelines.
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"""
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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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from tensorflow.python.data.experimental.ops import stats_aggregator
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from tensorflow.python.data.util import options
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from tensorflow.python.util.tf_export import tf_export
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@tf_export("data.experimental.StatsOptions")
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class StatsOptions(options.OptionsBase):
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"""Represents options for collecting dataset stats using `StatsAggregator`.
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You can set the stats options of a dataset through the `experimental_stats`
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property of `tf.data.Options`; the property is an instance of
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`tf.data.experimental.StatsOptions`. For example, to collect latency stats
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on all dataset edges, use the following pattern:
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```python
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aggregator = tf.data.experimental.StatsAggregator()
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options = tf.data.Options()
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options.experimental_stats.aggregator = aggregator
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options.experimental_stats.latency_all_edges = True
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dataset = dataset.with_options(options)
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```
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"""
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aggregator = options.create_option(
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name="aggregator",
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ty=(stats_aggregator.StatsAggregatorV2,
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stats_aggregator.StatsAggregatorV1),
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docstring=
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"Associates the given statistics aggregator with the dataset pipeline.")
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prefix = options.create_option(
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name="prefix",
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ty=str,
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docstring=
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"Prefix to prepend all statistics recorded for the input `dataset` with.",
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default_factory=lambda: "")
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counter_prefix = options.create_option(
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name="counter_prefix",
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ty=str,
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docstring="Prefix for the statistics recorded as counter.",
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default_factory=lambda: "")
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latency_all_edges = options.create_option(
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name="latency_all_edges",
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ty=bool,
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docstring=
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"Whether to add latency measurements on all edges. Defaults to False.")
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