85 lines
3.6 KiB
Python
85 lines
3.6 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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"""Collection of first-party plugins.
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This module exists to isolate tensorboard.program from the potentially
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heavyweight build dependencies for first-party plugins. This way people
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doing custom builds of TensorBoard have the option to only pay for the
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dependencies they want.
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This module also grants the flexibility to those doing custom builds, to
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automatically inherit the centrally-maintained list of standard plugins,
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for less repetition.
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"""
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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 logging
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import os
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import tensorflow as tf
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from tensorboard.plugins import base_plugin
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from tensorboard.plugins.audio import audio_plugin
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from tensorboard.plugins.beholder import beholder_plugin
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from tensorboard.plugins.core import core_plugin
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from tensorboard.plugins.custom_scalar import custom_scalars_plugin
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from tensorboard.plugins.distribution import distributions_plugin
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from tensorboard.plugins.graph import graphs_plugin
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from tensorboard.plugins.debugger import debugger_plugin_loader
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from tensorboard.plugins.histogram import histograms_plugin
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from tensorboard.plugins.image import images_plugin
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from tensorboard.plugins.pr_curve import pr_curves_plugin
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from tensorboard.plugins.profile import profile_plugin
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from tensorboard.plugins.projector import projector_plugin
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from tensorboard.plugins.scalar import scalars_plugin
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from tensorboard.plugins.text import text_plugin
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logger = logging.getLogger(__name__)
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PLUGIN_LOADERS = [
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core_plugin.CorePluginLoader(),
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base_plugin.BasicLoader(beholder_plugin.BeholderPlugin),
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base_plugin.BasicLoader(scalars_plugin.ScalarsPlugin),
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base_plugin.BasicLoader(custom_scalars_plugin.CustomScalarsPlugin),
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base_plugin.BasicLoader(images_plugin.ImagesPlugin),
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base_plugin.BasicLoader(audio_plugin.AudioPlugin),
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base_plugin.BasicLoader(graphs_plugin.GraphsPlugin),
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base_plugin.BasicLoader(distributions_plugin.DistributionsPlugin),
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base_plugin.BasicLoader(histograms_plugin.HistogramsPlugin),
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base_plugin.BasicLoader(pr_curves_plugin.PrCurvesPlugin),
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base_plugin.BasicLoader(projector_plugin.ProjectorPlugin),
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base_plugin.BasicLoader(text_plugin.TextPlugin),
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profile_plugin.ProfilePluginLoader(),
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debugger_plugin_loader.DebuggerPluginLoader(),
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]
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def get_assets_zip_provider():
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"""Opens stock TensorBoard web assets collection.
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Returns:
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Returns function that returns a newly opened file handle to zip file
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containing static assets for stock TensorBoard, or None if webfiles.zip
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could not be found. The value the callback returns must be closed. The
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paths inside the zip file are considered absolute paths on the web server.
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"""
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path = os.path.join(tf.resource_loader.get_data_files_path(), 'webfiles.zip')
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if not os.path.exists(path):
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logger.warning('webfiles.zip static assets not found: %s', path)
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return None
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return lambda: open(path, 'rb')
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