103 lines
3.5 KiB
Python
103 lines
3.5 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 __future__ import absolute_import
|
||
|
|
from __future__ import division
|
||
|
|
from __future__ import print_function
|
||
|
|
|
||
|
|
from werkzeug import wrappers
|
||
|
|
|
||
|
|
from tensorboard.backend import http_util
|
||
|
|
from tensorboard.plugins import base_plugin
|
||
|
|
from tensorboard.plugins.distribution import compressor
|
||
|
|
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 = 'distributions'
|
||
|
|
|
||
|
|
# 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)
|
||
|
|
self._multiplexer = context.multiplexer
|
||
|
|
|
||
|
|
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 distributions_impl(self, tag, run):
|
||
|
|
"""Result of the form `(body, mime_type)`, or `ValueError`."""
|
||
|
|
(histograms, mime_type) = self._histograms_plugin.histograms_impl(
|
||
|
|
tag, run, 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):
|
||
|
|
return self._histograms_plugin.index_impl()
|
||
|
|
|
||
|
|
@wrappers.Request.application
|
||
|
|
def tags_route(self, request):
|
||
|
|
index = self.index_impl()
|
||
|
|
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."""
|
||
|
|
tag = request.args.get('tag')
|
||
|
|
run = request.args.get('run')
|
||
|
|
try:
|
||
|
|
(body, mime_type) = self.distributions_impl(tag, run)
|
||
|
|
code = 200
|
||
|
|
except ValueError as e:
|
||
|
|
(body, mime_type) = (str(e), 'text/plain')
|
||
|
|
code = 400
|
||
|
|
return http_util.Respond(request, body, mime_type, code=code)
|