# 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 __future__ import absolute_import from __future__ import division from __future__ import print_function 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)