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# 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 Histograms plugin.
See `http_api.md` in this directory for specifications of the routes for
this plugin.
"""
from werkzeug import wrappers
from tensorboard import errors
from tensorboard import plugin_util
from tensorboard.backend import http_util
from tensorboard.data import provider
from tensorboard.plugins import base_plugin
from tensorboard.plugins.histogram import metadata
_DEFAULT_DOWNSAMPLING = 500 # histograms per time series
class HistogramsPlugin(base_plugin.TBPlugin):
"""Histograms 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 = 51
def __init__(self, context):
"""Instantiates HistogramsPlugin via TensorBoard core.
Args:
context: A base_plugin.TBContext instance.
"""
self._downsample_to = (context.sampling_hints or {}).get(
self.plugin_name, _DEFAULT_DOWNSAMPLING
)
self._data_provider = context.data_provider
self._version_checker = plugin_util._MetadataVersionChecker(
data_kind="histogram",
latest_known_version=0,
)
def get_plugin_apps(self):
return {
"/histograms": self.histograms_route,
"/tags": self.tags_route,
}
def is_active(self):
return False # `list_plugins` as called by TB core suffices
def index_impl(self, ctx, experiment):
"""Return {runName: {tagName: {displayName: ..., description:
...}}}."""
mapping = self._data_provider.list_tensors(
ctx,
experiment_id=experiment,
plugin_name=metadata.PLUGIN_NAME,
)
result = {run: {} for run in mapping}
for run, tag_to_content in mapping.items():
for tag, metadatum in tag_to_content.items():
description = plugin_util.markdown_to_safe_html(
metadatum.description
)
md = metadata.parse_plugin_metadata(metadatum.plugin_content)
if not self._version_checker.ok(md.version, run, tag):
continue
result[run][tag] = {
"displayName": metadatum.display_name,
"description": description,
}
return result
def frontend_metadata(self):
return base_plugin.FrontendMetadata(
element_name="tf-histogram-dashboard"
)
def histograms_impl(self, ctx, tag, run, experiment, downsample_to=None):
"""Result of the form `(body, mime_type)`.
At most `downsample_to` events will be returned. If this value is
`None`, then default downsampling will be performed.
Raises:
tensorboard.errors.PublicError: On invalid request.
"""
sample_count = (
downsample_to if downsample_to is not None else self._downsample_to
)
all_histograms = self._data_provider.read_tensors(
ctx,
experiment_id=experiment,
plugin_name=metadata.PLUGIN_NAME,
downsample=sample_count,
run_tag_filter=provider.RunTagFilter(runs=[run], tags=[tag]),
)
histograms = all_histograms.get(run, {}).get(tag, None)
if histograms is None:
raise errors.NotFoundError(
"No histogram tag %r for run %r" % (tag, run)
)
events = [(e.wall_time, e.step, e.numpy.tolist()) for e in histograms]
return (events, "application/json")
@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 histograms_route(self, request):
"""Given a tag and single run, return array of histogram values."""
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.histograms_impl(
ctx, tag, run, experiment=experiment, downsample_to=self.SAMPLE_SIZE
)
return http_util.Respond(request, body, mime_type)
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