82 lines
2.9 KiB
Python
82 lines
2.9 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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"""Internal information about the pr_curves plugin."""
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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 tensorflow as tf
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from tensorboard.plugins.pr_curve import plugin_data_pb2
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PLUGIN_NAME = 'pr_curves'
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# Indices for obtaining various values from the tensor stored in a summary.
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TRUE_POSITIVES_INDEX = 0
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FALSE_POSITIVES_INDEX = 1
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TRUE_NEGATIVES_INDEX = 2
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FALSE_NEGATIVES_INDEX = 3
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PRECISION_INDEX = 4
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RECALL_INDEX = 5
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# The most recent value for the `version` field of the
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# `PrCurvePluginData` proto.
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PROTO_VERSION = 0
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def create_summary_metadata(display_name, description, num_thresholds):
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"""Create a `tf.SummaryMetadata` proto for pr_curves plugin data.
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Arguments:
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display_name: The display name used in TensorBoard.
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description: The description to show in TensorBoard.
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num_thresholds: The number of thresholds to use for PR curves.
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Returns:
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A `tf.SummaryMetadata` protobuf object.
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"""
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pr_curve_plugin_data = plugin_data_pb2.PrCurvePluginData(
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version=PROTO_VERSION, num_thresholds=num_thresholds)
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content = pr_curve_plugin_data.SerializeToString()
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return tf.SummaryMetadata(
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display_name=display_name,
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summary_description=description,
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plugin_data=tf.SummaryMetadata.PluginData(plugin_name=PLUGIN_NAME,
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content=content))
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def parse_plugin_metadata(content):
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"""Parse summary metadata to a Python object.
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Arguments:
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content: The `content` field of a `SummaryMetadata` proto
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corresponding to the pr_curves plugin.
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Returns:
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A `PrCurvesPlugin` protobuf object.
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"""
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result = plugin_data_pb2.PrCurvePluginData()
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# TODO(@jart): Instead of converting to bytes, assert that the input
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# is a bytestring, and raise a ValueError otherwise...but only after
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# converting `PluginData`'s `content` field to have type `bytes`
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# instead of `string`.
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result.ParseFromString(tf.compat.as_bytes(content))
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if result.version == 0:
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return result
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else:
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tf.logging.warn(
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'Unknown metadata version: %s. The latest version known to '
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'this build of TensorBoard is %s; perhaps a newer build is '
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'available?', result.version, PROTO_VERSION)
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return result
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