I am done

rl/Lib/site-packages/tensorboard/plugins/custom_scalar/custom_scalars_plugin.py

@@ -0,0 +1,321 @@
+# 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 Custom Scalars plugin.
+
+This plugin lets the user create scalars plots with custom run-tag combinations
+by specifying regular expressions.
+
+See `http_api.md` in this directory for specifications of the routes for
+this plugin.
+"""
+
+import re
+
+from werkzeug import wrappers
+
+from tensorboard import plugin_util
+from tensorboard.backend import http_util
+from tensorboard.compat import tf
+from tensorboard.data import provider
+from tensorboard.plugins import base_plugin
+from tensorboard.plugins.custom_scalar import layout_pb2
+from tensorboard.plugins.custom_scalar import metadata
+from tensorboard.plugins.scalar import metadata as scalars_metadata
+from tensorboard.plugins.scalar import scalars_plugin
+
+
+# The name of the property in the response for whether the regex is valid.
+_REGEX_VALID_PROPERTY = "regex_valid"
+
+# The name of the property in the response for the payload (tag to ScalarEvents
+# mapping).
+_TAG_TO_EVENTS_PROPERTY = "tag_to_events"
+
+# The number of seconds to wait in between checks for the config file specifying
+# layout.
+_CONFIG_FILE_CHECK_THROTTLE = 60
+
+
+class CustomScalarsPlugin(base_plugin.TBPlugin):
+    """CustomScalars Plugin for TensorBoard."""
+
+    plugin_name = metadata.PLUGIN_NAME
+
+    def __init__(self, context):
+        """Instantiates ScalarsPlugin via TensorBoard core.
+
+        Args:
+          context: A base_plugin.TBContext instance.
+        """
+        self._logdir = context.logdir
+        self._data_provider = context.data_provider
+        self._plugin_name_to_instance = context.plugin_name_to_instance
+
+    def _get_scalars_plugin(self):
+        """Tries to get the scalars plugin.
+
+        Returns:
+          The scalars plugin. Or None if it is not yet registered.
+        """
+        if scalars_metadata.PLUGIN_NAME in self._plugin_name_to_instance:
+            # The plugin is registered.
+            return self._plugin_name_to_instance[scalars_metadata.PLUGIN_NAME]
+        # The plugin is not yet registered.
+        return None
+
+    def get_plugin_apps(self):
+        return {
+            "/download_data": self.download_data_route,
+            "/layout": self.layout_route,
+            "/scalars": self.scalars_route,
+        }
+
+    def is_active(self):
+        """Plugin is active if there is a custom layout for the dashboard."""
+        return False  # `list_plugins` as called by TB core suffices
+
+    def frontend_metadata(self):
+        return base_plugin.FrontendMetadata(
+            element_name="tf-custom-scalar-dashboard",
+            tab_name="Custom Scalars",
+        )
+
+    @wrappers.Request.application
+    def download_data_route(self, request):
+        ctx = plugin_util.context(request.environ)
+        run = request.args.get("run")
+        tag = request.args.get("tag")
+        experiment = plugin_util.experiment_id(request.environ)
+        response_format = request.args.get("format")
+        try:
+            body, mime_type = self.download_data_impl(
+                ctx, run, tag, experiment, response_format
+            )
+        except ValueError as e:
+            return http_util.Respond(
+                request=request,
+                content=str(e),
+                content_type="text/plain",
+                code=400,
+            )
+        return http_util.Respond(request, body, mime_type)
+
+    def download_data_impl(self, ctx, run, tag, experiment, response_format):
+        """Provides a response for downloading scalars data for a data series.
+
+        Args:
+          ctx: A tensorboard.context.RequestContext value.
+          run: The run.
+          tag: The specific tag.
+          experiment: An experiment ID, as a possibly-empty `str`.
+          response_format: A string. One of the values of the OutputFormat enum
+            of the scalar plugin.
+
+        Raises:
+          ValueError: If the scalars plugin is not registered.
+
+        Returns:
+          2 entities:
+            - A JSON object response body.
+            - A mime type (string) for the response.
+        """
+        scalars_plugin_instance = self._get_scalars_plugin()
+        if not scalars_plugin_instance:
+            raise ValueError(
+                (
+                    "Failed to respond to request for /download_data. "
+                    "The scalars plugin is oddly not registered."
+                )
+            )
+
+        body, mime_type = scalars_plugin_instance.scalars_impl(
+            ctx, tag, run, experiment, response_format
+        )
+        return body, mime_type
+
+    @wrappers.Request.application
+    def scalars_route(self, request):
+        """Given a tag regex and single run, return ScalarEvents.
+
+        This route takes 2 GET params:
+        run: A run string to find tags for.
+        tag: A string that is a regex used to find matching tags.
+        The response is a JSON object:
+        {
+          // Whether the regular expression is valid. Also false if empty.
+          regexValid: boolean,
+
+          // An object mapping tag name to a list of ScalarEvents.
+          payload: Object<string, ScalarEvent[]>,
+        }
+        """
+        ctx = plugin_util.context(request.environ)
+        tag_regex_string = request.args.get("tag")
+        run = request.args.get("run")
+        experiment = plugin_util.experiment_id(request.environ)
+        mime_type = "application/json"
+
+        try:
+            body = self.scalars_impl(ctx, run, tag_regex_string, experiment)
+        except ValueError as e:
+            return http_util.Respond(
+                request=request,
+                content=str(e),
+                content_type="text/plain",
+                code=400,
+            )
+
+        # Produce the response.
+        return http_util.Respond(request, body, mime_type)
+
+    def scalars_impl(self, ctx, run, tag_regex_string, experiment):
+        """Given a tag regex and single run, return ScalarEvents.
+
+        Args:
+          ctx: A tensorboard.context.RequestContext value.
+          run: A run string.
+          tag_regex_string: A regular expression that captures portions of tags.
+
+        Raises:
+          ValueError: if the scalars plugin is not registered.
+
+        Returns:
+          A dictionary that is the JSON-able response.
+        """
+        if not tag_regex_string:
+            # The user provided no regex.
+            return {
+                _REGEX_VALID_PROPERTY: False,
+                _TAG_TO_EVENTS_PROPERTY: {},
+            }
+
+        # Construct the regex.
+        try:
+            regex = re.compile(tag_regex_string)
+        except re.error:
+            return {
+                _REGEX_VALID_PROPERTY: False,
+                _TAG_TO_EVENTS_PROPERTY: {},
+            }
+
+        # Fetch the tags for the run. Filter for tags that match the regex.
+        run_to_data = self._data_provider.list_scalars(
+            ctx,
+            experiment_id=experiment,
+            plugin_name=scalars_metadata.PLUGIN_NAME,
+            run_tag_filter=provider.RunTagFilter(runs=[run]),
+        )
+
+        tag_to_data = None
+        try:
+            tag_to_data = run_to_data[run]
+        except KeyError:
+            # The run could not be found. Perhaps a configuration specified a run that
+            # TensorBoard has not read from disk yet.
+            payload = {}
+
+        if tag_to_data:
+            scalars_plugin_instance = self._get_scalars_plugin()
+            if not scalars_plugin_instance:
+                raise ValueError(
+                    (
+                        "Failed to respond to request for /scalars. "
+                        "The scalars plugin is oddly not registered."
+                    )
+                )
+
+            form = scalars_plugin.OutputFormat.JSON
+            payload = {
+                tag: scalars_plugin_instance.scalars_impl(
+                    ctx, tag, run, experiment, form
+                )[0]
+                for tag in tag_to_data.keys()
+                if regex.match(tag)
+            }
+
+        return {
+            _REGEX_VALID_PROPERTY: True,
+            _TAG_TO_EVENTS_PROPERTY: payload,
+        }
+
+    @wrappers.Request.application
+    def layout_route(self, request):
+        """Fetches the custom layout specified by the config file in the logdir.
+
+        If more than 1 run contains a layout, this method merges the layouts by
+        merging charts within individual categories. If 2 categories with the same
+        name are found, the charts within are merged. The merging is based on the
+        order of the runs to which the layouts are written.
+
+        The response is a JSON object mirroring properties of the Layout proto if a
+        layout for any run is found.
+
+        The response is an empty object if no layout could be found.
+        """
+        ctx = plugin_util.context(request.environ)
+        experiment = plugin_util.experiment_id(request.environ)
+        body = self.layout_impl(ctx, experiment)
+        return http_util.Respond(request, body, "application/json")
+
+    def layout_impl(self, ctx, experiment):
+        # Keep a mapping between and category so we do not create duplicate
+        # categories.
+        title_to_category = {}
+
+        merged_layout = None
+        data = self._data_provider.read_tensors(
+            ctx,
+            experiment_id=experiment,
+            plugin_name=metadata.PLUGIN_NAME,
+            run_tag_filter=provider.RunTagFilter(
+                tags=[metadata.CONFIG_SUMMARY_TAG]
+            ),
+            downsample=1,
+        )
+        for run in sorted(data):
+            points = data[run][metadata.CONFIG_SUMMARY_TAG]
+            content = points[0].numpy.item()
+            layout_proto = layout_pb2.Layout()
+            layout_proto.ParseFromString(tf.compat.as_bytes(content))
+
+            if merged_layout:
+                # Append the categories within this layout to the merged layout.
+                for category in layout_proto.category:
+                    if category.title in title_to_category:
+                        # A category with this name has been seen before. Do not create a
+                        # new one. Merge their charts, skipping any duplicates.
+                        title_to_category[category.title].chart.extend(
+                            [
+                                c
+                                for c in category.chart
+                                if c
+                                not in title_to_category[category.title].chart
+                            ]
+                        )
+                    else:
+                        # This category has not been seen before.
+                        merged_layout.category.add().MergeFrom(category)
+                        title_to_category[category.title] = category
+            else:
+                # This is the first layout encountered.
+                merged_layout = layout_proto
+                for category in layout_proto.category:
+                    title_to_category[category.title] = category
+
+        if merged_layout:
+            return plugin_util.proto_to_json(merged_layout)
+        else:
+            # No layout was found.
+            return {}

rl/Lib/site-packages/tensorboard/plugins/custom_scalar/layout_pb2.py

@@ -0,0 +1,85 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/plugins/custom_scalar/layout.proto
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import message as _message
+from google.protobuf import reflection as _reflection
+from google.protobuf import symbol_database as _symbol_database
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n.tensorboard/plugins/custom_scalar/layout.proto\x12\x0btensorboard\"\x8d\x01\n\x05\x43hart\x12\r\n\x05title\x18\x01 \x01(\t\x12\x37\n\tmultiline\x18\x02 \x01(\x0b\x32\".tensorboard.MultilineChartContentH\x00\x12\x31\n\x06margin\x18\x03 \x01(\x0b\x32\x1f.tensorboard.MarginChartContentH\x00\x42\t\n\x07\x63ontent\"$\n\x15MultilineChartContent\x12\x0b\n\x03tag\x18\x01 \x03(\t\"\x83\x01\n\x12MarginChartContent\x12\x36\n\x06series\x18\x01 \x03(\x0b\x32&.tensorboard.MarginChartContent.Series\x1a\x35\n\x06Series\x12\r\n\x05value\x18\x01 \x01(\t\x12\r\n\x05lower\x18\x02 \x01(\t\x12\r\n\x05upper\x18\x03 \x01(\t\"L\n\x08\x43\x61tegory\x12\r\n\x05title\x18\x01 \x01(\t\x12!\n\x05\x63hart\x18\x02 \x03(\x0b\x32\x12.tensorboard.Chart\x12\x0e\n\x06\x63losed\x18\x03 \x01(\x08\"B\n\x06Layout\x12\x0f\n\x07version\x18\x01 \x01(\x05\x12\'\n\x08\x63\x61tegory\x18\x02 \x03(\x0b\x32\x15.tensorboard.Categoryb\x06proto3')
+
+
+
+_CHART = DESCRIPTOR.message_types_by_name['Chart']
+_MULTILINECHARTCONTENT = DESCRIPTOR.message_types_by_name['MultilineChartContent']
+_MARGINCHARTCONTENT = DESCRIPTOR.message_types_by_name['MarginChartContent']
+_MARGINCHARTCONTENT_SERIES = _MARGINCHARTCONTENT.nested_types_by_name['Series']
+_CATEGORY = DESCRIPTOR.message_types_by_name['Category']
+_LAYOUT = DESCRIPTOR.message_types_by_name['Layout']
+Chart = _reflection.GeneratedProtocolMessageType('Chart', (_message.Message,), {
+  'DESCRIPTOR' : _CHART,
+  '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.Chart)
+  })
+_sym_db.RegisterMessage(Chart)
+
+MultilineChartContent = _reflection.GeneratedProtocolMessageType('MultilineChartContent', (_message.Message,), {
+  'DESCRIPTOR' : _MULTILINECHARTCONTENT,
+  '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.MultilineChartContent)
+  })
+_sym_db.RegisterMessage(MultilineChartContent)
+
+MarginChartContent = _reflection.GeneratedProtocolMessageType('MarginChartContent', (_message.Message,), {
+
+  'Series' : _reflection.GeneratedProtocolMessageType('Series', (_message.Message,), {
+    'DESCRIPTOR' : _MARGINCHARTCONTENT_SERIES,
+    '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.MarginChartContent.Series)
+    })
+  ,
+  'DESCRIPTOR' : _MARGINCHARTCONTENT,
+  '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.MarginChartContent)
+  })
+_sym_db.RegisterMessage(MarginChartContent)
+_sym_db.RegisterMessage(MarginChartContent.Series)
+
+Category = _reflection.GeneratedProtocolMessageType('Category', (_message.Message,), {
+  'DESCRIPTOR' : _CATEGORY,
+  '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.Category)
+  })
+_sym_db.RegisterMessage(Category)
+
+Layout = _reflection.GeneratedProtocolMessageType('Layout', (_message.Message,), {
+  'DESCRIPTOR' : _LAYOUT,
+  '__module__' : 'tensorboard.plugins.custom_scalar.layout_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.Layout)
+  })
+_sym_db.RegisterMessage(Layout)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  _CHART._serialized_start=64
+  _CHART._serialized_end=205
+  _MULTILINECHARTCONTENT._serialized_start=207
+  _MULTILINECHARTCONTENT._serialized_end=243
+  _MARGINCHARTCONTENT._serialized_start=246
+  _MARGINCHARTCONTENT._serialized_end=377
+  _MARGINCHARTCONTENT_SERIES._serialized_start=324
+  _MARGINCHARTCONTENT_SERIES._serialized_end=377
+  _CATEGORY._serialized_start=379
+  _CATEGORY._serialized_end=455
+  _LAYOUT._serialized_start=457
+  _LAYOUT._serialized_end=523
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/plugins/custom_scalar/metadata.py

@@ -0,0 +1,36 @@
+# 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.
+# ==============================================================================
+"""Information on the custom scalars plugin."""
+
+
+from tensorboard.compat.proto import summary_pb2
+
+# A special tag named used for the summary that stores the layout.
+CONFIG_SUMMARY_TAG = "custom_scalars__config__"
+
+PLUGIN_NAME = "custom_scalars"
+
+
+def create_summary_metadata():
+    """Create a `SummaryMetadata` proto for custom scalar plugin data.
+
+    Returns:
+      A `summary_pb2.SummaryMetadata` protobuf object.
+    """
+    return summary_pb2.SummaryMetadata(
+        plugin_data=summary_pb2.SummaryMetadata.PluginData(
+            plugin_name=PLUGIN_NAME
+        )
+    )

rl/Lib/site-packages/tensorboard/plugins/custom_scalar/summary.py

@@ -0,0 +1,80 @@
+# 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.
+# ==============================================================================
+"""Contains summaries related to laying out the custom scalars dashboard."""
+
+
+from tensorboard.plugins.custom_scalar import layout_pb2
+from tensorboard.plugins.custom_scalar import metadata
+
+
+def op(scalars_layout, collections=None):
+    """Creates a summary that contains a layout.
+
+    When users navigate to the custom scalars dashboard, they will see a layout
+    based on the proto provided to this function.
+
+    Args:
+      scalars_layout: The scalars_layout_pb2.Layout proto that specifies the
+          layout.
+      collections: Optional list of graph collections keys. The new
+          summary op is added to these collections. Defaults to
+          `[Graph Keys.SUMMARIES]`.
+
+    Returns:
+      A tensor summary op that writes the layout to disk.
+    """
+    # TODO(nickfelt): remove on-demand imports once dep situation is fixed.
+    import tensorflow.compat.v1 as tf
+
+    assert isinstance(scalars_layout, layout_pb2.Layout)
+    summary_metadata = metadata.create_summary_metadata()
+    return tf.summary.tensor_summary(
+        name=metadata.CONFIG_SUMMARY_TAG,
+        tensor=tf.constant(scalars_layout.SerializeToString(), dtype=tf.string),
+        collections=collections,
+        summary_metadata=summary_metadata,
+    )
+
+
+def pb(scalars_layout):
+    """Creates a summary that contains a layout.
+
+    When users navigate to the custom scalars dashboard, they will see a layout
+    based on the proto provided to this function.
+
+    Args:
+      scalars_layout: The scalars_layout_pb2.Layout proto that specifies the
+          layout.
+
+    Returns:
+      A summary proto containing the layout.
+    """
+    # TODO(nickfelt): remove on-demand imports once dep situation is fixed.
+    import tensorflow.compat.v1 as tf
+
+    assert isinstance(scalars_layout, layout_pb2.Layout)
+    tensor = tf.make_tensor_proto(
+        scalars_layout.SerializeToString(), dtype=tf.string
+    )
+    tf_summary_metadata = tf.SummaryMetadata.FromString(
+        metadata.create_summary_metadata().SerializeToString()
+    )
+    summary = tf.Summary()
+    summary.value.add(
+        tag=metadata.CONFIG_SUMMARY_TAG,
+        metadata=tf_summary_metadata,
+        tensor=tensor,
+    )
+    return summary