ai-content-maker/.venv/Lib/site-packages/tensorboard/plugins/distribution/distributions_plugin.py

118 lines
4.2 KiB
Python

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""The TensorBoard Distributions (a.k.a. compressed histograms) plugin.
See `http_api.md` in this directory for specifications of the routes for
this plugin.
"""
from werkzeug import wrappers
from tensorboard import plugin_util
from tensorboard.backend import http_util
from tensorboard.plugins import base_plugin
from tensorboard.plugins.distribution import compressor
from tensorboard.plugins.distribution import metadata
from tensorboard.plugins.histogram import histograms_plugin
class DistributionsPlugin(base_plugin.TBPlugin):
"""Distributions Plugin for TensorBoard.
This supports both old-style summaries (created with TensorFlow ops
that output directly to the `histo` field of the proto) and new-
style summaries (as created by the
`tensorboard.plugins.histogram.summary` module).
"""
plugin_name = metadata.PLUGIN_NAME
# Use a round number + 1 since sampling includes both start and end steps,
# so N+1 samples corresponds to dividing the step sequence into N intervals.
SAMPLE_SIZE = 501
def __init__(self, context):
"""Instantiates DistributionsPlugin via TensorBoard core.
Args:
context: A base_plugin.TBContext instance.
"""
self._histograms_plugin = histograms_plugin.HistogramsPlugin(context)
def get_plugin_apps(self):
return {
"/distributions": self.distributions_route,
"/tags": self.tags_route,
}
def is_active(self):
"""This plugin is active iff any run has at least one histogram tag.
(The distributions plugin uses the same data source as the
histogram plugin.)
"""
return self._histograms_plugin.is_active()
def data_plugin_names(self):
return (self._histograms_plugin.plugin_name,)
def frontend_metadata(self):
return base_plugin.FrontendMetadata(
element_name="tf-distribution-dashboard",
)
def distributions_impl(self, ctx, tag, run, experiment):
"""Result of the form `(body, mime_type)`.
Raises:
tensorboard.errors.PublicError: On invalid request.
"""
(histograms, mime_type) = self._histograms_plugin.histograms_impl(
ctx, tag, run, experiment=experiment, downsample_to=self.SAMPLE_SIZE
)
return (
[self._compress(histogram) for histogram in histograms],
mime_type,
)
def _compress(self, histogram):
(wall_time, step, buckets) = histogram
converted_buckets = compressor.compress_histogram(buckets)
return [wall_time, step, converted_buckets]
def index_impl(self, ctx, experiment):
return self._histograms_plugin.index_impl(ctx, experiment=experiment)
@wrappers.Request.application
def tags_route(self, request):
ctx = plugin_util.context(request.environ)
experiment = plugin_util.experiment_id(request.environ)
index = self.index_impl(ctx, experiment=experiment)
return http_util.Respond(request, index, "application/json")
@wrappers.Request.application
def distributions_route(self, request):
"""Given a tag and single run, return an array of compressed
histograms."""
ctx = plugin_util.context(request.environ)
experiment = plugin_util.experiment_id(request.environ)
tag = request.args.get("tag")
run = request.args.get("run")
(body, mime_type) = self.distributions_impl(
ctx, tag, run, experiment=experiment
)
return http_util.Respond(request, body, mime_type)