I am done

rl/Lib/site-packages/tensorboard/compat/__init__.py

@@ -0,0 +1,70 @@
+# 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.
+
+"""Compatibility interfaces for TensorBoard.
+
+This module provides logic for importing variations on the TensorFlow
+APIs, as lazily loaded imports to help avoid circular dependency issues
+and defer the search and loading of the module until necessary.
+"""
+
+
+import tensorboard.lazy as _lazy
+
+
+@_lazy.lazy_load("tensorboard.compat.tf")
+def tf():
+    """Provide the root module of a TF-like API for use within TensorBoard.
+
+    By default this is equivalent to `import tensorflow as tf`, but it can be used
+    in combination with //tensorboard/compat:tensorflow (to fall back to a stub TF
+    API implementation if the real one is not available) or with
+    //tensorboard/compat:no_tensorflow (to force unconditional use of the stub).
+
+    Returns:
+      The root module of a TF-like API, if available.
+
+    Raises:
+      ImportError: if a TF-like API is not available.
+    """
+    try:
+        from tensorboard.compat import notf  # noqa: F401
+    except ImportError:
+        try:
+            import tensorflow
+
+            return tensorflow
+        except ImportError:
+            pass
+    from tensorboard.compat import tensorflow_stub
+
+    return tensorflow_stub
+
+
+@_lazy.lazy_load("tensorboard.compat.tf2")
+def tf2():
+    """Provide the root module of a TF-2.0 API for use within TensorBoard.
+
+    Returns:
+      The root module of a TF-2.0 API, if available.
+
+    Raises:
+      ImportError: if a TF-2.0 API is not available.
+    """
+    # Resolve the lazy `tf` compat API from earlier in this file and try to find
+    # tf.compat.v2. Don't check tf.__version__ since this is not always reliable
+    # if TF was built with tf_api_version!=2.
+    if hasattr(tf, "compat") and hasattr(tf.compat, "v2"):
+        return tf.compat.v2
+    raise ImportError("cannot import tensorflow 2.0 API")

rl/Lib/site-packages/tensorboard/compat/proto/allocation_description_pb2.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/allocation_description.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'\n5tensorboard/compat/proto/allocation_description.proto\x12\x0btensorboard\"\xa3\x01\n\x15\x41llocationDescription\x12\x17\n\x0frequested_bytes\x18\x01 \x01(\x03\x12\x17\n\x0f\x61llocated_bytes\x18\x02 \x01(\x03\x12\x16\n\x0e\x61llocator_name\x18\x03 \x01(\t\x12\x15\n\rallocation_id\x18\x04 \x01(\x03\x12\x1c\n\x14has_single_reference\x18\x05 \x01(\x08\x12\x0b\n\x03ptr\x18\x06 \x01(\x04\x42\x9b\x01\n\x18org.tensorflow.frameworkB\x1b\x41llocationDescriptionProtosP\x01Z]github.com/tensorflow/tensorflow/tensorflow/go/core/framework/allocation_description_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_ALLOCATIONDESCRIPTION = DESCRIPTOR.message_types_by_name['AllocationDescription']
+AllocationDescription = _reflection.GeneratedProtocolMessageType('AllocationDescription', (_message.Message,), {
+  'DESCRIPTOR' : _ALLOCATIONDESCRIPTION,
+  '__module__' : 'tensorboard.compat.proto.allocation_description_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AllocationDescription)
+  })
+_sym_db.RegisterMessage(AllocationDescription)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\033AllocationDescriptionProtosP\001Z]github.com/tensorflow/tensorflow/tensorflow/go/core/framework/allocation_description_go_proto\370\001\001'
+  _ALLOCATIONDESCRIPTION._serialized_start=71
+  _ALLOCATIONDESCRIPTION._serialized_end=234
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/api_def_pb2.py

@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/api_def.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()
+
+
+from tensorboard.compat.proto import attr_value_pb2 as tensorboard_dot_compat_dot_proto_dot_attr__value__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n&tensorboard/compat/proto/api_def.proto\x12\x0btensorboard\x1a)tensorboard/compat/proto/attr_value.proto\"\xe7\x05\n\x06\x41piDef\x12\x15\n\rgraph_op_name\x18\x01 \x01(\t\x12\x1b\n\x13\x64\x65precation_message\x18\x0c \x01(\t\x12\x1b\n\x13\x64\x65precation_version\x18\r \x01(\x05\x12\x32\n\nvisibility\x18\x02 \x01(\x0e\x32\x1e.tensorboard.ApiDef.Visibility\x12.\n\x08\x65ndpoint\x18\x03 \x03(\x0b\x32\x1c.tensorboard.ApiDef.Endpoint\x12\'\n\x06in_arg\x18\x04 \x03(\x0b\x32\x17.tensorboard.ApiDef.Arg\x12(\n\x07out_arg\x18\x05 \x03(\x0b\x32\x17.tensorboard.ApiDef.Arg\x12\x11\n\targ_order\x18\x0b \x03(\t\x12&\n\x04\x61ttr\x18\x06 \x03(\x0b\x32\x18.tensorboard.ApiDef.Attr\x12\x0f\n\x07summary\x18\x07 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x08 \x01(\t\x12\x1a\n\x12\x64\x65scription_prefix\x18\t \x01(\t\x12\x1a\n\x12\x64\x65scription_suffix\x18\n \x01(\t\x1aI\n\x08\x45ndpoint\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x12\n\ndeprecated\x18\x03 \x01(\x08\x12\x1b\n\x13\x64\x65precation_version\x18\x04 \x01(\x05\x1a;\n\x03\x41rg\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x11\n\trename_to\x18\x02 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x03 \x01(\t\x1ak\n\x04\x41ttr\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x11\n\trename_to\x18\x02 \x01(\t\x12-\n\rdefault_value\x18\x03 \x01(\x0b\x32\x16.tensorboard.AttrValue\x12\x13\n\x0b\x64\x65scription\x18\x04 \x01(\t\"G\n\nVisibility\x12\x16\n\x12\x44\x45\x46\x41ULT_VISIBILITY\x10\x00\x12\x0b\n\x07VISIBLE\x10\x01\x12\x08\n\x04SKIP\x10\x02\x12\n\n\x06HIDDEN\x10\x03\"*\n\x07\x41piDefs\x12\x1f\n\x02op\x18\x01 \x03(\x0b\x32\x13.tensorboard.ApiDefB}\n\x18org.tensorflow.frameworkB\x0c\x41piDefProtosP\x01ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/api_def_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_APIDEF = DESCRIPTOR.message_types_by_name['ApiDef']
+_APIDEF_ENDPOINT = _APIDEF.nested_types_by_name['Endpoint']
+_APIDEF_ARG = _APIDEF.nested_types_by_name['Arg']
+_APIDEF_ATTR = _APIDEF.nested_types_by_name['Attr']
+_APIDEFS = DESCRIPTOR.message_types_by_name['ApiDefs']
+_APIDEF_VISIBILITY = _APIDEF.enum_types_by_name['Visibility']
+ApiDef = _reflection.GeneratedProtocolMessageType('ApiDef', (_message.Message,), {
+
+  'Endpoint' : _reflection.GeneratedProtocolMessageType('Endpoint', (_message.Message,), {
+    'DESCRIPTOR' : _APIDEF_ENDPOINT,
+    '__module__' : 'tensorboard.compat.proto.api_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.ApiDef.Endpoint)
+    })
+  ,
+
+  'Arg' : _reflection.GeneratedProtocolMessageType('Arg', (_message.Message,), {
+    'DESCRIPTOR' : _APIDEF_ARG,
+    '__module__' : 'tensorboard.compat.proto.api_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.ApiDef.Arg)
+    })
+  ,
+
+  'Attr' : _reflection.GeneratedProtocolMessageType('Attr', (_message.Message,), {
+    'DESCRIPTOR' : _APIDEF_ATTR,
+    '__module__' : 'tensorboard.compat.proto.api_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.ApiDef.Attr)
+    })
+  ,
+  'DESCRIPTOR' : _APIDEF,
+  '__module__' : 'tensorboard.compat.proto.api_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ApiDef)
+  })
+_sym_db.RegisterMessage(ApiDef)
+_sym_db.RegisterMessage(ApiDef.Endpoint)
+_sym_db.RegisterMessage(ApiDef.Arg)
+_sym_db.RegisterMessage(ApiDef.Attr)
+
+ApiDefs = _reflection.GeneratedProtocolMessageType('ApiDefs', (_message.Message,), {
+  'DESCRIPTOR' : _APIDEFS,
+  '__module__' : 'tensorboard.compat.proto.api_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ApiDefs)
+  })
+_sym_db.RegisterMessage(ApiDefs)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\014ApiDefProtosP\001ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/api_def_go_proto\370\001\001'
+  _APIDEF._serialized_start=99
+  _APIDEF._serialized_end=842
+  _APIDEF_ENDPOINT._serialized_start=526
+  _APIDEF_ENDPOINT._serialized_end=599
+  _APIDEF_ARG._serialized_start=601
+  _APIDEF_ARG._serialized_end=660
+  _APIDEF_ATTR._serialized_start=662
+  _APIDEF_ATTR._serialized_end=769
+  _APIDEF_VISIBILITY._serialized_start=771
+  _APIDEF_VISIBILITY._serialized_end=842
+  _APIDEFS._serialized_start=844
+  _APIDEFS._serialized_end=886
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/attr_value_pb2.py

@@ -0,0 +1,80 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/attr_value.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()
+
+
+from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n)tensorboard/compat/proto/attr_value.proto\x12\x0btensorboard\x1a%tensorboard/compat/proto/tensor.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xaf\x04\n\tAttrValue\x12\x0b\n\x01s\x18\x02 \x01(\x0cH\x00\x12\x0b\n\x01i\x18\x03 \x01(\x03H\x00\x12\x0b\n\x01\x66\x18\x04 \x01(\x02H\x00\x12\x0b\n\x01\x62\x18\x05 \x01(\x08H\x00\x12%\n\x04type\x18\x06 \x01(\x0e\x32\x15.tensorboard.DataTypeH\x00\x12.\n\x05shape\x18\x07 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProtoH\x00\x12*\n\x06tensor\x18\x08 \x01(\x0b\x32\x18.tensorboard.TensorProtoH\x00\x12\x30\n\x04list\x18\x01 \x01(\x0b\x32 .tensorboard.AttrValue.ListValueH\x00\x12)\n\x04\x66unc\x18\n \x01(\x0b\x32\x19.tensorboard.NameAttrListH\x00\x12\x15\n\x0bplaceholder\x18\t \x01(\tH\x00\x1a\xed\x01\n\tListValue\x12\t\n\x01s\x18\x02 \x03(\x0c\x12\r\n\x01i\x18\x03 \x03(\x03\x42\x02\x10\x01\x12\r\n\x01\x66\x18\x04 \x03(\x02\x42\x02\x10\x01\x12\r\n\x01\x62\x18\x05 \x03(\x08\x42\x02\x10\x01\x12\'\n\x04type\x18\x06 \x03(\x0e\x32\x15.tensorboard.DataTypeB\x02\x10\x01\x12,\n\x05shape\x18\x07 \x03(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12(\n\x06tensor\x18\x08 \x03(\x0b\x32\x18.tensorboard.TensorProto\x12\'\n\x04\x66unc\x18\t \x03(\x0b\x32\x19.tensorboard.NameAttrListB\x07\n\x05value\"\x94\x01\n\x0cNameAttrList\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x31\n\x04\x61ttr\x18\x02 \x03(\x0b\x32#.tensorboard.NameAttrList.AttrEntry\x1a\x43\n\tAttrEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12%\n\x05value\x18\x02 \x01(\x0b\x32\x16.tensorboard.AttrValue:\x02\x38\x01\x42\x83\x01\n\x18org.tensorflow.frameworkB\x0f\x41ttrValueProtosP\x01ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/attr_value_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_ATTRVALUE = DESCRIPTOR.message_types_by_name['AttrValue']
+_ATTRVALUE_LISTVALUE = _ATTRVALUE.nested_types_by_name['ListValue']
+_NAMEATTRLIST = DESCRIPTOR.message_types_by_name['NameAttrList']
+_NAMEATTRLIST_ATTRENTRY = _NAMEATTRLIST.nested_types_by_name['AttrEntry']
+AttrValue = _reflection.GeneratedProtocolMessageType('AttrValue', (_message.Message,), {
+
+  'ListValue' : _reflection.GeneratedProtocolMessageType('ListValue', (_message.Message,), {
+    'DESCRIPTOR' : _ATTRVALUE_LISTVALUE,
+    '__module__' : 'tensorboard.compat.proto.attr_value_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.AttrValue.ListValue)
+    })
+  ,
+  'DESCRIPTOR' : _ATTRVALUE,
+  '__module__' : 'tensorboard.compat.proto.attr_value_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AttrValue)
+  })
+_sym_db.RegisterMessage(AttrValue)
+_sym_db.RegisterMessage(AttrValue.ListValue)
+
+NameAttrList = _reflection.GeneratedProtocolMessageType('NameAttrList', (_message.Message,), {
+
+  'AttrEntry' : _reflection.GeneratedProtocolMessageType('AttrEntry', (_message.Message,), {
+    'DESCRIPTOR' : _NAMEATTRLIST_ATTRENTRY,
+    '__module__' : 'tensorboard.compat.proto.attr_value_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.NameAttrList.AttrEntry)
+    })
+  ,
+  'DESCRIPTOR' : _NAMEATTRLIST,
+  '__module__' : 'tensorboard.compat.proto.attr_value_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NameAttrList)
+  })
+_sym_db.RegisterMessage(NameAttrList)
+_sym_db.RegisterMessage(NameAttrList.AttrEntry)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\017AttrValueProtosP\001ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/attr_value_go_proto\370\001\001'
+  _ATTRVALUE_LISTVALUE.fields_by_name['i']._options = None
+  _ATTRVALUE_LISTVALUE.fields_by_name['i']._serialized_options = b'\020\001'
+  _ATTRVALUE_LISTVALUE.fields_by_name['f']._options = None
+  _ATTRVALUE_LISTVALUE.fields_by_name['f']._serialized_options = b'\020\001'
+  _ATTRVALUE_LISTVALUE.fields_by_name['b']._options = None
+  _ATTRVALUE_LISTVALUE.fields_by_name['b']._serialized_options = b'\020\001'
+  _ATTRVALUE_LISTVALUE.fields_by_name['type']._options = None
+  _ATTRVALUE_LISTVALUE.fields_by_name['type']._serialized_options = b'\020\001'
+  _NAMEATTRLIST_ATTRENTRY._options = None
+  _NAMEATTRLIST_ATTRENTRY._serialized_options = b'8\001'
+  _ATTRVALUE._serialized_start=181
+  _ATTRVALUE._serialized_end=740
+  _ATTRVALUE_LISTVALUE._serialized_start=494
+  _ATTRVALUE_LISTVALUE._serialized_end=731
+  _NAMEATTRLIST._serialized_start=743
+  _NAMEATTRLIST._serialized_end=891
+  _NAMEATTRLIST_ATTRENTRY._serialized_start=824
+  _NAMEATTRLIST_ATTRENTRY._serialized_end=891
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/cluster_pb2.py

@@ -0,0 +1,58 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/cluster.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/compat/proto/cluster.proto\x12\x0btensorboard\"s\n\x06JobDef\x12\x0c\n\x04name\x18\x01 \x01(\t\x12-\n\x05tasks\x18\x02 \x03(\x0b\x32\x1e.tensorboard.JobDef.TasksEntry\x1a,\n\nTasksEntry\x12\x0b\n\x03key\x18\x01 \x01(\x05\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\".\n\nClusterDef\x12 \n\x03job\x18\x01 \x03(\x0b\x32\x13.tensorboard.JobDefB\x87\x01\n\x1aorg.tensorflow.distruntimeB\rClusterProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_JOBDEF = DESCRIPTOR.message_types_by_name['JobDef']
+_JOBDEF_TASKSENTRY = _JOBDEF.nested_types_by_name['TasksEntry']
+_CLUSTERDEF = DESCRIPTOR.message_types_by_name['ClusterDef']
+JobDef = _reflection.GeneratedProtocolMessageType('JobDef', (_message.Message,), {
+
+  'TasksEntry' : _reflection.GeneratedProtocolMessageType('TasksEntry', (_message.Message,), {
+    'DESCRIPTOR' : _JOBDEF_TASKSENTRY,
+    '__module__' : 'tensorboard.compat.proto.cluster_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.JobDef.TasksEntry)
+    })
+  ,
+  'DESCRIPTOR' : _JOBDEF,
+  '__module__' : 'tensorboard.compat.proto.cluster_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.JobDef)
+  })
+_sym_db.RegisterMessage(JobDef)
+_sym_db.RegisterMessage(JobDef.TasksEntry)
+
+ClusterDef = _reflection.GeneratedProtocolMessageType('ClusterDef', (_message.Message,), {
+  'DESCRIPTOR' : _CLUSTERDEF,
+  '__module__' : 'tensorboard.compat.proto.cluster_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ClusterDef)
+  })
+_sym_db.RegisterMessage(ClusterDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\032org.tensorflow.distruntimeB\rClusterProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _JOBDEF_TASKSENTRY._options = None
+  _JOBDEF_TASKSENTRY._serialized_options = b'8\001'
+  _JOBDEF._serialized_start=55
+  _JOBDEF._serialized_end=170
+  _JOBDEF_TASKSENTRY._serialized_start=126
+  _JOBDEF_TASKSENTRY._serialized_end=170
+  _CLUSTERDEF._serialized_start=172
+  _CLUSTERDEF._serialized_end=218
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/coordination_config_pb2.py

@@ -0,0 +1,45 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/coordination_config.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'\n2tensorboard/compat/proto/coordination_config.proto\x12\x0btensorboard\"1\n\x0e\x43oordinatedJob\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x11\n\tnum_tasks\x18\x02 \x01(\x05\"\xd1\x03\n\x19\x43oordinationServiceConfig\x12\x14\n\x0cservice_type\x18\x01 \x01(\t\x12\x16\n\x0eservice_leader\x18\x02 \x01(\t\x12\x1b\n\x13\x65nable_health_check\x18\x03 \x01(\x08\x12&\n\x1e\x63luster_register_timeout_in_ms\x18\x04 \x01(\x03\x12\x1f\n\x17heartbeat_timeout_in_ms\x18\x05 \x01(\x03\x12\x39\n\x14\x63oordinated_job_list\x18\n \x03(\x0b\x32\x1b.tensorboard.CoordinatedJob\x12&\n\x1eshutdown_barrier_timeout_in_ms\x18\x07 \x01(\x03\x12*\n\"agent_destruction_without_shutdown\x18\x08 \x01(\x08\x12\x18\n\x10recoverable_jobs\x18\t \x03(\t\x12*\n\"allow_new_incarnation_to_reconnect\x18\x0b \x01(\x08\x12\x15\n\rforce_disable\x18\x0c \x01(\x08\x12.\n&poll_for_error_from_service_at_startup\x18\r \x01(\x08J\x04\x08\x06\x10\x07\x42WZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_protob\x06proto3')
+
+
+
+_COORDINATEDJOB = DESCRIPTOR.message_types_by_name['CoordinatedJob']
+_COORDINATIONSERVICECONFIG = DESCRIPTOR.message_types_by_name['CoordinationServiceConfig']
+CoordinatedJob = _reflection.GeneratedProtocolMessageType('CoordinatedJob', (_message.Message,), {
+  'DESCRIPTOR' : _COORDINATEDJOB,
+  '__module__' : 'tensorboard.compat.proto.coordination_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CoordinatedJob)
+  })
+_sym_db.RegisterMessage(CoordinatedJob)
+
+CoordinationServiceConfig = _reflection.GeneratedProtocolMessageType('CoordinationServiceConfig', (_message.Message,), {
+  'DESCRIPTOR' : _COORDINATIONSERVICECONFIG,
+  '__module__' : 'tensorboard.compat.proto.coordination_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CoordinationServiceConfig)
+  })
+_sym_db.RegisterMessage(CoordinationServiceConfig)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto'
+  _COORDINATEDJOB._serialized_start=67
+  _COORDINATEDJOB._serialized_end=116
+  _COORDINATIONSERVICECONFIG._serialized_start=119
+  _COORDINATIONSERVICECONFIG._serialized_end=584
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/cost_graph_pb2.py

@@ -0,0 +1,87 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/cost_graph.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()
+
+
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n)tensorboard/compat/proto/cost_graph.proto\x12\x0btensorboard\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xd0\x06\n\x0c\x43ostGraphDef\x12,\n\x04node\x18\x01 \x03(\x0b\x32\x1e.tensorboard.CostGraphDef.Node\x12\x36\n\x04\x63ost\x18\x02 \x03(\x0b\x32(.tensorboard.CostGraphDef.AggregatedCost\x1a\xa6\x05\n\x04Node\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06\x64\x65vice\x18\x02 \x01(\t\x12\n\n\x02id\x18\x03 \x01(\x05\x12<\n\ninput_info\x18\x04 \x03(\x0b\x32(.tensorboard.CostGraphDef.Node.InputInfo\x12>\n\x0boutput_info\x18\x05 \x03(\x0b\x32).tensorboard.CostGraphDef.Node.OutputInfo\x12\x1d\n\x15temporary_memory_size\x18\x06 \x01(\x03\x12\x1e\n\x16persistent_memory_size\x18\x0c \x01(\x03\x12!\n\x15host_temp_memory_size\x18\n \x01(\x03\x42\x02\x18\x01\x12#\n\x17\x64\x65vice_temp_memory_size\x18\x0b \x01(\x03\x42\x02\x18\x01\x12)\n\x1d\x64\x65vice_persistent_memory_size\x18\x10 \x01(\x03\x42\x02\x18\x01\x12\x14\n\x0c\x63ompute_cost\x18\t \x01(\x03\x12\x14\n\x0c\x63ompute_time\x18\x0e \x01(\x03\x12\x13\n\x0bmemory_time\x18\x0f \x01(\x03\x12\x10\n\x08is_final\x18\x07 \x01(\x08\x12\x15\n\rcontrol_input\x18\x08 \x03(\x05\x12\x12\n\ninaccurate\x18\x11 \x01(\x08\x1a;\n\tInputInfo\x12\x16\n\x0epreceding_node\x18\x01 \x01(\x05\x12\x16\n\x0epreceding_port\x18\x02 \x01(\x05\x1a\x88\x01\n\nOutputInfo\x12\x0c\n\x04size\x18\x01 \x01(\x03\x12\x18\n\x10\x61lias_input_port\x18\x02 \x01(\x03\x12,\n\x05shape\x18\x03 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12$\n\x05\x64type\x18\x04 \x01(\x0e\x32\x15.tensorboard.DataType\x1a\x31\n\x0e\x41ggregatedCost\x12\x0c\n\x04\x63ost\x18\x01 \x01(\x02\x12\x11\n\tdimension\x18\x02 \x01(\tB\x83\x01\n\x18org.tensorflow.frameworkB\x0f\x43ostGraphProtosP\x01ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/cost_graph_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_COSTGRAPHDEF = DESCRIPTOR.message_types_by_name['CostGraphDef']
+_COSTGRAPHDEF_NODE = _COSTGRAPHDEF.nested_types_by_name['Node']
+_COSTGRAPHDEF_NODE_INPUTINFO = _COSTGRAPHDEF_NODE.nested_types_by_name['InputInfo']
+_COSTGRAPHDEF_NODE_OUTPUTINFO = _COSTGRAPHDEF_NODE.nested_types_by_name['OutputInfo']
+_COSTGRAPHDEF_AGGREGATEDCOST = _COSTGRAPHDEF.nested_types_by_name['AggregatedCost']
+CostGraphDef = _reflection.GeneratedProtocolMessageType('CostGraphDef', (_message.Message,), {
+
+  'Node' : _reflection.GeneratedProtocolMessageType('Node', (_message.Message,), {
+
+    'InputInfo' : _reflection.GeneratedProtocolMessageType('InputInfo', (_message.Message,), {
+      'DESCRIPTOR' : _COSTGRAPHDEF_NODE_INPUTINFO,
+      '__module__' : 'tensorboard.compat.proto.cost_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.CostGraphDef.Node.InputInfo)
+      })
+    ,
+
+    'OutputInfo' : _reflection.GeneratedProtocolMessageType('OutputInfo', (_message.Message,), {
+      'DESCRIPTOR' : _COSTGRAPHDEF_NODE_OUTPUTINFO,
+      '__module__' : 'tensorboard.compat.proto.cost_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.CostGraphDef.Node.OutputInfo)
+      })
+    ,
+    'DESCRIPTOR' : _COSTGRAPHDEF_NODE,
+    '__module__' : 'tensorboard.compat.proto.cost_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CostGraphDef.Node)
+    })
+  ,
+
+  'AggregatedCost' : _reflection.GeneratedProtocolMessageType('AggregatedCost', (_message.Message,), {
+    'DESCRIPTOR' : _COSTGRAPHDEF_AGGREGATEDCOST,
+    '__module__' : 'tensorboard.compat.proto.cost_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CostGraphDef.AggregatedCost)
+    })
+  ,
+  'DESCRIPTOR' : _COSTGRAPHDEF,
+  '__module__' : 'tensorboard.compat.proto.cost_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CostGraphDef)
+  })
+_sym_db.RegisterMessage(CostGraphDef)
+_sym_db.RegisterMessage(CostGraphDef.Node)
+_sym_db.RegisterMessage(CostGraphDef.Node.InputInfo)
+_sym_db.RegisterMessage(CostGraphDef.Node.OutputInfo)
+_sym_db.RegisterMessage(CostGraphDef.AggregatedCost)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\017CostGraphProtosP\001ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/cost_graph_go_proto\370\001\001'
+  _COSTGRAPHDEF_NODE.fields_by_name['host_temp_memory_size']._options = None
+  _COSTGRAPHDEF_NODE.fields_by_name['host_temp_memory_size']._serialized_options = b'\030\001'
+  _COSTGRAPHDEF_NODE.fields_by_name['device_temp_memory_size']._options = None
+  _COSTGRAPHDEF_NODE.fields_by_name['device_temp_memory_size']._serialized_options = b'\030\001'
+  _COSTGRAPHDEF_NODE.fields_by_name['device_persistent_memory_size']._options = None
+  _COSTGRAPHDEF_NODE.fields_by_name['device_persistent_memory_size']._serialized_options = b'\030\001'
+  _COSTGRAPHDEF._serialized_start=142
+  _COSTGRAPHDEF._serialized_end=990
+  _COSTGRAPHDEF_NODE._serialized_start=261
+  _COSTGRAPHDEF_NODE._serialized_end=939
+  _COSTGRAPHDEF_NODE_INPUTINFO._serialized_start=741
+  _COSTGRAPHDEF_NODE_INPUTINFO._serialized_end=800
+  _COSTGRAPHDEF_NODE_OUTPUTINFO._serialized_start=803
+  _COSTGRAPHDEF_NODE_OUTPUTINFO._serialized_end=939
+  _COSTGRAPHDEF_AGGREGATEDCOST._serialized_start=941
+  _COSTGRAPHDEF_AGGREGATEDCOST._serialized_end=990
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/cpp_shape_inference_pb2.py

@@ -0,0 +1,70 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/cpp_shape_inference.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()
+
+
+from tensorboard.compat.proto import full_type_pb2 as tensorboard_dot_compat_dot_proto_dot_full__type__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n2tensorboard/compat/proto/cpp_shape_inference.proto\x12\x0btensorboard\x1a(tensorboard/compat/proto/full_type.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xa1\x03\n\x17\x43ppShapeInferenceResult\x12,\n\x05shape\x18\x01 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12\x44\n\x0bhandle_data\x18\x04 \x01(\x0b\x32/.tensorboard.CppShapeInferenceResult.HandleData\x1a\x96\x01\n\x12HandleShapeAndType\x12,\n\x05shape\x18\x01 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12$\n\x05\x64type\x18\x02 \x01(\x0e\x32\x15.tensorboard.DataType\x12&\n\x04type\x18\x04 \x01(\x0b\x32\x18.tensorboard.FullTypeDefJ\x04\x08\x03\x10\x04\x1am\n\nHandleData\x12\x0e\n\x06is_set\x18\x01 \x01(\x08\x12O\n\x0eshape_and_type\x18\x02 \x03(\x0b\x32\x37.tensorboard.CppShapeInferenceResult.HandleShapeAndTypeJ\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04\"e\n\x1d\x43ppShapeInferenceInputsNeeded\x12\x1c\n\x14input_tensors_needed\x18\x01 \x03(\x05\x12&\n\x1einput_tensors_as_shapes_needed\x18\x02 \x03(\x05\x42\x61Z\\github.com/tensorflow/tensorflow/tensorflow/go/python/framework/cpp_shape_inference_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_CPPSHAPEINFERENCERESULT = DESCRIPTOR.message_types_by_name['CppShapeInferenceResult']
+_CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE = _CPPSHAPEINFERENCERESULT.nested_types_by_name['HandleShapeAndType']
+_CPPSHAPEINFERENCERESULT_HANDLEDATA = _CPPSHAPEINFERENCERESULT.nested_types_by_name['HandleData']
+_CPPSHAPEINFERENCEINPUTSNEEDED = DESCRIPTOR.message_types_by_name['CppShapeInferenceInputsNeeded']
+CppShapeInferenceResult = _reflection.GeneratedProtocolMessageType('CppShapeInferenceResult', (_message.Message,), {
+
+  'HandleShapeAndType' : _reflection.GeneratedProtocolMessageType('HandleShapeAndType', (_message.Message,), {
+    'DESCRIPTOR' : _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE,
+    '__module__' : 'tensorboard.compat.proto.cpp_shape_inference_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CppShapeInferenceResult.HandleShapeAndType)
+    })
+  ,
+
+  'HandleData' : _reflection.GeneratedProtocolMessageType('HandleData', (_message.Message,), {
+    'DESCRIPTOR' : _CPPSHAPEINFERENCERESULT_HANDLEDATA,
+    '__module__' : 'tensorboard.compat.proto.cpp_shape_inference_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CppShapeInferenceResult.HandleData)
+    })
+  ,
+  'DESCRIPTOR' : _CPPSHAPEINFERENCERESULT,
+  '__module__' : 'tensorboard.compat.proto.cpp_shape_inference_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CppShapeInferenceResult)
+  })
+_sym_db.RegisterMessage(CppShapeInferenceResult)
+_sym_db.RegisterMessage(CppShapeInferenceResult.HandleShapeAndType)
+_sym_db.RegisterMessage(CppShapeInferenceResult.HandleData)
+
+CppShapeInferenceInputsNeeded = _reflection.GeneratedProtocolMessageType('CppShapeInferenceInputsNeeded', (_message.Message,), {
+  'DESCRIPTOR' : _CPPSHAPEINFERENCEINPUTSNEEDED,
+  '__module__' : 'tensorboard.compat.proto.cpp_shape_inference_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CppShapeInferenceInputsNeeded)
+  })
+_sym_db.RegisterMessage(CppShapeInferenceInputsNeeded)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'Z\\github.com/tensorflow/tensorflow/tensorflow/go/python/framework/cpp_shape_inference_go_proto\370\001\001'
+  _CPPSHAPEINFERENCERESULT._serialized_start=193
+  _CPPSHAPEINFERENCERESULT._serialized_end=610
+  _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE._serialized_start=337
+  _CPPSHAPEINFERENCERESULT_HANDLESHAPEANDTYPE._serialized_end=487
+  _CPPSHAPEINFERENCERESULT_HANDLEDATA._serialized_start=489
+  _CPPSHAPEINFERENCERESULT_HANDLEDATA._serialized_end=598
+  _CPPSHAPEINFERENCEINPUTSNEEDED._serialized_start=612
+  _CPPSHAPEINFERENCEINPUTSNEEDED._serialized_end=713
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/debug_pb2.py

@@ -0,0 +1,65 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/debug.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/compat/proto/debug.proto\x12\x0btensorboard\"\x8e\x01\n\x10\x44\x65\x62ugTensorWatch\x12\x11\n\tnode_name\x18\x01 \x01(\t\x12\x13\n\x0boutput_slot\x18\x02 \x01(\x05\x12\x11\n\tdebug_ops\x18\x03 \x03(\t\x12\x12\n\ndebug_urls\x18\x04 \x03(\t\x12+\n#tolerate_debug_op_creation_failures\x18\x05 \x01(\x08\"\x82\x01\n\x0c\x44\x65\x62ugOptions\x12>\n\x17\x64\x65\x62ug_tensor_watch_opts\x18\x04 \x03(\x0b\x32\x1d.tensorboard.DebugTensorWatch\x12\x13\n\x0bglobal_step\x18\n \x01(\x03\x12\x1d\n\x15reset_disk_byte_usage\x18\x0b \x01(\x08\"j\n\x12\x44\x65\x62uggedSourceFile\x12\x0c\n\x04host\x18\x01 \x01(\t\x12\x11\n\tfile_path\x18\x02 \x01(\t\x12\x15\n\rlast_modified\x18\x03 \x01(\x03\x12\r\n\x05\x62ytes\x18\x04 \x01(\x03\x12\r\n\x05lines\x18\x05 \x03(\t\"L\n\x13\x44\x65\x62uggedSourceFiles\x12\x35\n\x0csource_files\x18\x01 \x03(\x0b\x32\x1f.tensorboard.DebuggedSourceFileB\x83\x01\n\x18org.tensorflow.frameworkB\x0b\x44\x65\x62ugProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_DEBUGTENSORWATCH = DESCRIPTOR.message_types_by_name['DebugTensorWatch']
+_DEBUGOPTIONS = DESCRIPTOR.message_types_by_name['DebugOptions']
+_DEBUGGEDSOURCEFILE = DESCRIPTOR.message_types_by_name['DebuggedSourceFile']
+_DEBUGGEDSOURCEFILES = DESCRIPTOR.message_types_by_name['DebuggedSourceFiles']
+DebugTensorWatch = _reflection.GeneratedProtocolMessageType('DebugTensorWatch', (_message.Message,), {
+  'DESCRIPTOR' : _DEBUGTENSORWATCH,
+  '__module__' : 'tensorboard.compat.proto.debug_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DebugTensorWatch)
+  })
+_sym_db.RegisterMessage(DebugTensorWatch)
+
+DebugOptions = _reflection.GeneratedProtocolMessageType('DebugOptions', (_message.Message,), {
+  'DESCRIPTOR' : _DEBUGOPTIONS,
+  '__module__' : 'tensorboard.compat.proto.debug_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DebugOptions)
+  })
+_sym_db.RegisterMessage(DebugOptions)
+
+DebuggedSourceFile = _reflection.GeneratedProtocolMessageType('DebuggedSourceFile', (_message.Message,), {
+  'DESCRIPTOR' : _DEBUGGEDSOURCEFILE,
+  '__module__' : 'tensorboard.compat.proto.debug_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DebuggedSourceFile)
+  })
+_sym_db.RegisterMessage(DebuggedSourceFile)
+
+DebuggedSourceFiles = _reflection.GeneratedProtocolMessageType('DebuggedSourceFiles', (_message.Message,), {
+  'DESCRIPTOR' : _DEBUGGEDSOURCEFILES,
+  '__module__' : 'tensorboard.compat.proto.debug_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DebuggedSourceFiles)
+  })
+_sym_db.RegisterMessage(DebuggedSourceFiles)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\013DebugProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _DEBUGTENSORWATCH._serialized_start=54
+  _DEBUGTENSORWATCH._serialized_end=196
+  _DEBUGOPTIONS._serialized_start=199
+  _DEBUGOPTIONS._serialized_end=329
+  _DEBUGGEDSOURCEFILE._serialized_start=331
+  _DEBUGGEDSOURCEFILE._serialized_end=437
+  _DEBUGGEDSOURCEFILES._serialized_start=439
+  _DEBUGGEDSOURCEFILES._serialized_end=515
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/event_pb2.py

@@ -0,0 +1,149 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/event.proto
+"""Generated protocol buffer code."""
+from google.protobuf.internal import enum_type_wrapper
+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()
+
+
+from tensorboard.compat.proto import summary_pb2 as tensorboard_dot_compat_dot_proto_dot_summary__pb2
+try:
+  tensorboard_dot_compat_dot_proto_dot_histogram__pb2 = tensorboard_dot_compat_dot_proto_dot_summary__pb2.tensorboard_dot_compat_dot_proto_dot_histogram__pb2
+except AttributeError:
+  tensorboard_dot_compat_dot_proto_dot_histogram__pb2 = tensorboard_dot_compat_dot_proto_dot_summary__pb2.tensorboard.compat.proto.histogram_pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n$tensorboard/compat/proto/event.proto\x12\x0btensorboard\x1a&tensorboard/compat/proto/summary.proto\"\xf9\x02\n\x05\x45vent\x12\x11\n\twall_time\x18\x01 \x01(\x01\x12\x0c\n\x04step\x18\x02 \x01(\x03\x12\x16\n\x0c\x66ile_version\x18\x03 \x01(\tH\x00\x12\x13\n\tgraph_def\x18\x04 \x01(\x0cH\x00\x12\'\n\x07summary\x18\x05 \x01(\x0b\x32\x14.tensorboard.SummaryH\x00\x12\x32\n\x0blog_message\x18\x06 \x01(\x0b\x32\x17.tensorboard.LogMessageB\x02\x18\x01H\x00\x12.\n\x0bsession_log\x18\x07 \x01(\x0b\x32\x17.tensorboard.SessionLogH\x00\x12=\n\x13tagged_run_metadata\x18\x08 \x01(\x0b\x32\x1e.tensorboard.TaggedRunMetadataH\x00\x12\x18\n\x0emeta_graph_def\x18\t \x01(\x0cH\x00\x12\x34\n\x0fsource_metadata\x18\n \x01(\x0b\x32\x1b.tensorboard.SourceMetadataB\x06\n\x04what\" \n\x0eSourceMetadata\x12\x0e\n\x06writer\x18\x01 \x01(\t\"\xa2\x01\n\nLogMessage\x12,\n\x05level\x18\x01 \x01(\x0e\x32\x1d.tensorboard.LogMessage.Level\x12\x0f\n\x07message\x18\x02 \x01(\t\"Q\n\x05Level\x12\x0b\n\x07UNKNOWN\x10\x00\x12\r\n\tDEBUGGING\x10\n\x12\x08\n\x04INFO\x10\x14\x12\x08\n\x04WARN\x10\x1e\x12\t\n\x05\x45RROR\x10(\x12\t\n\x05\x46\x41TAL\x10\x32\x1a\x02\x18\x01:\x02\x18\x01\"\xb7\x01\n\nSessionLog\x12\x35\n\x06status\x18\x01 \x01(\x0e\x32%.tensorboard.SessionLog.SessionStatus\x12\x17\n\x0f\x63heckpoint_path\x18\x02 \x01(\t\x12\x0b\n\x03msg\x18\x03 \x01(\t\"L\n\rSessionStatus\x12\x16\n\x12STATUS_UNSPECIFIED\x10\x00\x12\t\n\x05START\x10\x01\x12\x08\n\x04STOP\x10\x02\x12\x0e\n\nCHECKPOINT\x10\x03\"6\n\x11TaggedRunMetadata\x12\x0b\n\x03tag\x18\x01 \x01(\t\x12\x14\n\x0crun_metadata\x18\x02 \x01(\x0c\"$\n\x0eWatchdogConfig\x12\x12\n\ntimeout_ms\x18\x01 \x01(\x03\"&\n\x11RequestedExitCode\x12\x11\n\texit_code\x18\x01 \x01(\x05\"\xb9\x01\n\x16WorkerHeartbeatRequest\x12\x36\n\rshutdown_mode\x18\x01 \x01(\x0e\x32\x1f.tensorboard.WorkerShutdownMode\x12\x34\n\x0fwatchdog_config\x18\x02 \x01(\x0b\x32\x1b.tensorboard.WatchdogConfig\x12\x31\n\texit_code\x18\x03 \x01(\x0b\x32\x1e.tensorboard.RequestedExitCode\"\x85\x01\n\x17WorkerHeartbeatResponse\x12\x30\n\rhealth_status\x18\x01 \x01(\x0e\x32\x19.tensorboard.WorkerHealth\x12&\n\nworker_log\x18\x02 \x03(\x0b\x32\x12.tensorboard.Event\x12\x10\n\x08hostname\x18\x03 \x01(\t*[\n\x0cWorkerHealth\x12\x06\n\x02OK\x10\x00\x12\x1c\n\x18RECEIVED_SHUTDOWN_SIGNAL\x10\x01\x12\x12\n\x0eINTERNAL_ERROR\x10\x02\x12\x11\n\rSHUTTING_DOWN\x10\x03*k\n\x12WorkerShutdownMode\x12\x0b\n\x07\x44\x45\x46\x41ULT\x10\x00\x12\x12\n\x0eNOT_CONFIGURED\x10\x01\x12\x18\n\x14WAIT_FOR_COORDINATOR\x10\x02\x12\x1a\n\x16SHUTDOWN_AFTER_TIMEOUT\x10\x03\x42p\n\x13org.tensorflow.utilB\x0b\x45ventProtosP\x01ZGgithub.com/tensorflow/tensorflow/tensorflow/go/core/util/event_go_proto\xf8\x01\x01\x62\x06proto3')
+
+_WORKERHEALTH = DESCRIPTOR.enum_types_by_name['WorkerHealth']
+WorkerHealth = enum_type_wrapper.EnumTypeWrapper(_WORKERHEALTH)
+_WORKERSHUTDOWNMODE = DESCRIPTOR.enum_types_by_name['WorkerShutdownMode']
+WorkerShutdownMode = enum_type_wrapper.EnumTypeWrapper(_WORKERSHUTDOWNMODE)
+OK = 0
+RECEIVED_SHUTDOWN_SIGNAL = 1
+INTERNAL_ERROR = 2
+SHUTTING_DOWN = 3
+DEFAULT = 0
+NOT_CONFIGURED = 1
+WAIT_FOR_COORDINATOR = 2
+SHUTDOWN_AFTER_TIMEOUT = 3
+
+
+_EVENT = DESCRIPTOR.message_types_by_name['Event']
+_SOURCEMETADATA = DESCRIPTOR.message_types_by_name['SourceMetadata']
+_LOGMESSAGE = DESCRIPTOR.message_types_by_name['LogMessage']
+_SESSIONLOG = DESCRIPTOR.message_types_by_name['SessionLog']
+_TAGGEDRUNMETADATA = DESCRIPTOR.message_types_by_name['TaggedRunMetadata']
+_WATCHDOGCONFIG = DESCRIPTOR.message_types_by_name['WatchdogConfig']
+_REQUESTEDEXITCODE = DESCRIPTOR.message_types_by_name['RequestedExitCode']
+_WORKERHEARTBEATREQUEST = DESCRIPTOR.message_types_by_name['WorkerHeartbeatRequest']
+_WORKERHEARTBEATRESPONSE = DESCRIPTOR.message_types_by_name['WorkerHeartbeatResponse']
+_LOGMESSAGE_LEVEL = _LOGMESSAGE.enum_types_by_name['Level']
+_SESSIONLOG_SESSIONSTATUS = _SESSIONLOG.enum_types_by_name['SessionStatus']
+Event = _reflection.GeneratedProtocolMessageType('Event', (_message.Message,), {
+  'DESCRIPTOR' : _EVENT,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.Event)
+  })
+_sym_db.RegisterMessage(Event)
+
+SourceMetadata = _reflection.GeneratedProtocolMessageType('SourceMetadata', (_message.Message,), {
+  'DESCRIPTOR' : _SOURCEMETADATA,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SourceMetadata)
+  })
+_sym_db.RegisterMessage(SourceMetadata)
+
+LogMessage = _reflection.GeneratedProtocolMessageType('LogMessage', (_message.Message,), {
+  'DESCRIPTOR' : _LOGMESSAGE,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.LogMessage)
+  })
+_sym_db.RegisterMessage(LogMessage)
+
+SessionLog = _reflection.GeneratedProtocolMessageType('SessionLog', (_message.Message,), {
+  'DESCRIPTOR' : _SESSIONLOG,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SessionLog)
+  })
+_sym_db.RegisterMessage(SessionLog)
+
+TaggedRunMetadata = _reflection.GeneratedProtocolMessageType('TaggedRunMetadata', (_message.Message,), {
+  'DESCRIPTOR' : _TAGGEDRUNMETADATA,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TaggedRunMetadata)
+  })
+_sym_db.RegisterMessage(TaggedRunMetadata)
+
+WatchdogConfig = _reflection.GeneratedProtocolMessageType('WatchdogConfig', (_message.Message,), {
+  'DESCRIPTOR' : _WATCHDOGCONFIG,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.WatchdogConfig)
+  })
+_sym_db.RegisterMessage(WatchdogConfig)
+
+RequestedExitCode = _reflection.GeneratedProtocolMessageType('RequestedExitCode', (_message.Message,), {
+  'DESCRIPTOR' : _REQUESTEDEXITCODE,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.RequestedExitCode)
+  })
+_sym_db.RegisterMessage(RequestedExitCode)
+
+WorkerHeartbeatRequest = _reflection.GeneratedProtocolMessageType('WorkerHeartbeatRequest', (_message.Message,), {
+  'DESCRIPTOR' : _WORKERHEARTBEATREQUEST,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.WorkerHeartbeatRequest)
+  })
+_sym_db.RegisterMessage(WorkerHeartbeatRequest)
+
+WorkerHeartbeatResponse = _reflection.GeneratedProtocolMessageType('WorkerHeartbeatResponse', (_message.Message,), {
+  'DESCRIPTOR' : _WORKERHEARTBEATRESPONSE,
+  '__module__' : 'tensorboard.compat.proto.event_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.WorkerHeartbeatResponse)
+  })
+_sym_db.RegisterMessage(WorkerHeartbeatResponse)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\023org.tensorflow.utilB\013EventProtosP\001ZGgithub.com/tensorflow/tensorflow/tensorflow/go/core/util/event_go_proto\370\001\001'
+  _EVENT.fields_by_name['log_message']._options = None
+  _EVENT.fields_by_name['log_message']._serialized_options = b'\030\001'
+  _LOGMESSAGE_LEVEL._options = None
+  _LOGMESSAGE_LEVEL._serialized_options = b'\030\001'
+  _LOGMESSAGE._options = None
+  _LOGMESSAGE._serialized_options = b'\030\001'
+  _WORKERHEALTH._serialized_start=1316
+  _WORKERHEALTH._serialized_end=1407
+  _WORKERSHUTDOWNMODE._serialized_start=1409
+  _WORKERSHUTDOWNMODE._serialized_end=1516
+  _EVENT._serialized_start=94
+  _EVENT._serialized_end=471
+  _SOURCEMETADATA._serialized_start=473
+  _SOURCEMETADATA._serialized_end=505
+  _LOGMESSAGE._serialized_start=508
+  _LOGMESSAGE._serialized_end=670
+  _LOGMESSAGE_LEVEL._serialized_start=585
+  _LOGMESSAGE_LEVEL._serialized_end=666
+  _SESSIONLOG._serialized_start=673
+  _SESSIONLOG._serialized_end=856
+  _SESSIONLOG_SESSIONSTATUS._serialized_start=780
+  _SESSIONLOG_SESSIONSTATUS._serialized_end=856
+  _TAGGEDRUNMETADATA._serialized_start=858
+  _TAGGEDRUNMETADATA._serialized_end=912
+  _WATCHDOGCONFIG._serialized_start=914
+  _WATCHDOGCONFIG._serialized_end=950
+  _REQUESTEDEXITCODE._serialized_start=952
+  _REQUESTEDEXITCODE._serialized_end=990
+  _WORKERHEARTBEATREQUEST._serialized_start=993
+  _WORKERHEARTBEATREQUEST._serialized_end=1178
+  _WORKERHEARTBEATRESPONSE._serialized_start=1181
+  _WORKERHEARTBEATRESPONSE._serialized_end=1314
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/full_type_pb2.py

@@ -0,0 +1,74 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/full_type.proto
+"""Generated protocol buffer code."""
+from google.protobuf.internal import enum_type_wrapper
+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/compat/proto/full_type.proto\x12\x0btensorboard\"\x81\x01\n\x0b\x46ullTypeDef\x12(\n\x07type_id\x18\x01 \x01(\x0e\x32\x17.tensorboard.FullTypeId\x12&\n\x04\x61rgs\x18\x02 \x03(\x0b\x32\x18.tensorboard.FullTypeDef\x12\x0b\n\x01s\x18\x03 \x01(\tH\x00\x12\x0b\n\x01i\x18\x04 \x01(\x03H\x00\x42\x06\n\x04\x61ttr*\xda\x04\n\nFullTypeId\x12\r\n\tTFT_UNSET\x10\x00\x12\x0b\n\x07TFT_VAR\x10\x01\x12\x0b\n\x07TFT_ANY\x10\x02\x12\x0f\n\x0bTFT_PRODUCT\x10\x03\x12\r\n\tTFT_NAMED\x10\x04\x12\x10\n\x0cTFT_FOR_EACH\x10\x14\x12\x10\n\x0cTFT_CALLABLE\x10\x64\x12\x0f\n\nTFT_TENSOR\x10\xe8\x07\x12\x0e\n\tTFT_ARRAY\x10\xe9\x07\x12\x11\n\x0cTFT_OPTIONAL\x10\xea\x07\x12\x10\n\x0bTFT_LITERAL\x10\xeb\x07\x12\x10\n\x0bTFT_ENCODED\x10\xec\x07\x12\x15\n\x10TFT_SHAPE_TENSOR\x10\xed\x07\x12\r\n\x08TFT_BOOL\x10\xc8\x01\x12\x0e\n\tTFT_UINT8\x10\xc9\x01\x12\x0f\n\nTFT_UINT16\x10\xca\x01\x12\x0f\n\nTFT_UINT32\x10\xcb\x01\x12\x0f\n\nTFT_UINT64\x10\xcc\x01\x12\r\n\x08TFT_INT8\x10\xcd\x01\x12\x0e\n\tTFT_INT16\x10\xce\x01\x12\x0e\n\tTFT_INT32\x10\xcf\x01\x12\x0e\n\tTFT_INT64\x10\xd0\x01\x12\r\n\x08TFT_HALF\x10\xd1\x01\x12\x0e\n\tTFT_FLOAT\x10\xd2\x01\x12\x0f\n\nTFT_DOUBLE\x10\xd3\x01\x12\x11\n\x0cTFT_BFLOAT16\x10\xd7\x01\x12\x12\n\rTFT_COMPLEX64\x10\xd4\x01\x12\x13\n\x0eTFT_COMPLEX128\x10\xd5\x01\x12\x0f\n\nTFT_STRING\x10\xd6\x01\x12\x10\n\x0bTFT_DATASET\x10\xf6N\x12\x0f\n\nTFT_RAGGED\x10\xf7N\x12\x11\n\x0cTFT_ITERATOR\x10\xf8N\x12\x13\n\x0eTFT_MUTEX_LOCK\x10\xdaO\x12\x17\n\x12TFT_LEGACY_VARIANT\x10\xdbOB\x81\x01\n\x18org.tensorflow.frameworkB\x0e\x46ullTypeProtosP\x01ZPgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/full_type_go_proto\xf8\x01\x01\x62\x06proto3')
+
+_FULLTYPEID = DESCRIPTOR.enum_types_by_name['FullTypeId']
+FullTypeId = enum_type_wrapper.EnumTypeWrapper(_FULLTYPEID)
+TFT_UNSET = 0
+TFT_VAR = 1
+TFT_ANY = 2
+TFT_PRODUCT = 3
+TFT_NAMED = 4
+TFT_FOR_EACH = 20
+TFT_CALLABLE = 100
+TFT_TENSOR = 1000
+TFT_ARRAY = 1001
+TFT_OPTIONAL = 1002
+TFT_LITERAL = 1003
+TFT_ENCODED = 1004
+TFT_SHAPE_TENSOR = 1005
+TFT_BOOL = 200
+TFT_UINT8 = 201
+TFT_UINT16 = 202
+TFT_UINT32 = 203
+TFT_UINT64 = 204
+TFT_INT8 = 205
+TFT_INT16 = 206
+TFT_INT32 = 207
+TFT_INT64 = 208
+TFT_HALF = 209
+TFT_FLOAT = 210
+TFT_DOUBLE = 211
+TFT_BFLOAT16 = 215
+TFT_COMPLEX64 = 212
+TFT_COMPLEX128 = 213
+TFT_STRING = 214
+TFT_DATASET = 10102
+TFT_RAGGED = 10103
+TFT_ITERATOR = 10104
+TFT_MUTEX_LOCK = 10202
+TFT_LEGACY_VARIANT = 10203
+
+
+_FULLTYPEDEF = DESCRIPTOR.message_types_by_name['FullTypeDef']
+FullTypeDef = _reflection.GeneratedProtocolMessageType('FullTypeDef', (_message.Message,), {
+  'DESCRIPTOR' : _FULLTYPEDEF,
+  '__module__' : 'tensorboard.compat.proto.full_type_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.FullTypeDef)
+  })
+_sym_db.RegisterMessage(FullTypeDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\016FullTypeProtosP\001ZPgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/full_type_go_proto\370\001\001'
+  _FULLTYPEID._serialized_start=190
+  _FULLTYPEID._serialized_end=792
+  _FULLTYPEDEF._serialized_start=58
+  _FULLTYPEDEF._serialized_end=187
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/function_pb2.py

@@ -0,0 +1,157 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/function.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()
+
+
+from tensorboard.compat.proto import attr_value_pb2 as tensorboard_dot_compat_dot_proto_dot_attr__value__pb2
+from tensorboard.compat.proto import node_def_pb2 as tensorboard_dot_compat_dot_proto_dot_node__def__pb2
+from tensorboard.compat.proto import op_def_pb2 as tensorboard_dot_compat_dot_proto_dot_op__def__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\'tensorboard/compat/proto/function.proto\x12\x0btensorboard\x1a)tensorboard/compat/proto/attr_value.proto\x1a\'tensorboard/compat/proto/node_def.proto\x1a%tensorboard/compat/proto/op_def.proto\"\xab\x01\n\x12\x46unctionDefLibrary\x12*\n\x08\x66unction\x18\x01 \x03(\x0b\x32\x18.tensorboard.FunctionDef\x12*\n\x08gradient\x18\x02 \x03(\x0b\x32\x18.tensorboard.GradientDef\x12=\n\x14registered_gradients\x18\x03 \x03(\x0b\x32\x1f.tensorboard.RegisteredGradient\"\xcf\x06\n\x0b\x46unctionDef\x12%\n\tsignature\x18\x01 \x01(\x0b\x32\x12.tensorboard.OpDef\x12\x30\n\x04\x61ttr\x18\x05 \x03(\x0b\x32\".tensorboard.FunctionDef.AttrEntry\x12\x37\n\x08\x61rg_attr\x18\x07 \x03(\x0b\x32%.tensorboard.FunctionDef.ArgAttrEntry\x12Q\n\x16resource_arg_unique_id\x18\x08 \x03(\x0b\x32\x31.tensorboard.FunctionDef.ResourceArgUniqueIdEntry\x12&\n\x08node_def\x18\x03 \x03(\x0b\x32\x14.tensorboard.NodeDef\x12.\n\x03ret\x18\x04 \x03(\x0b\x32!.tensorboard.FunctionDef.RetEntry\x12=\n\x0b\x63ontrol_ret\x18\x06 \x03(\x0b\x32(.tensorboard.FunctionDef.ControlRetEntry\x1a\x43\n\tAttrEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12%\n\x05value\x18\x02 \x01(\x0b\x32\x16.tensorboard.AttrValue:\x02\x38\x01\x1a\x8a\x01\n\x08\x41rgAttrs\x12\x39\n\x04\x61ttr\x18\x01 \x03(\x0b\x32+.tensorboard.FunctionDef.ArgAttrs.AttrEntry\x1a\x43\n\tAttrEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12%\n\x05value\x18\x02 \x01(\x0b\x32\x16.tensorboard.AttrValue:\x02\x38\x01\x1aQ\n\x0c\x41rgAttrEntry\x12\x0b\n\x03key\x18\x01 \x01(\r\x12\x30\n\x05value\x18\x02 \x01(\x0b\x32!.tensorboard.FunctionDef.ArgAttrs:\x02\x38\x01\x1a:\n\x18ResourceArgUniqueIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\r\x12\r\n\x05value\x18\x02 \x01(\r:\x02\x38\x01\x1a*\n\x08RetEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\x1a\x31\n\x0f\x43ontrolRetEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01J\x04\x08\x02\x10\x03\";\n\x0bGradientDef\x12\x15\n\rfunction_name\x18\x01 \x01(\t\x12\x15\n\rgradient_func\x18\x02 \x01(\t\"G\n\x12RegisteredGradient\x12\x15\n\rgradient_func\x18\x01 \x01(\t\x12\x1a\n\x12registered_op_type\x18\x02 \x01(\tB\x80\x01\n\x18org.tensorflow.frameworkB\x0e\x46unctionProtosP\x01ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/function_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_FUNCTIONDEFLIBRARY = DESCRIPTOR.message_types_by_name['FunctionDefLibrary']
+_FUNCTIONDEF = DESCRIPTOR.message_types_by_name['FunctionDef']
+_FUNCTIONDEF_ATTRENTRY = _FUNCTIONDEF.nested_types_by_name['AttrEntry']
+_FUNCTIONDEF_ARGATTRS = _FUNCTIONDEF.nested_types_by_name['ArgAttrs']
+_FUNCTIONDEF_ARGATTRS_ATTRENTRY = _FUNCTIONDEF_ARGATTRS.nested_types_by_name['AttrEntry']
+_FUNCTIONDEF_ARGATTRENTRY = _FUNCTIONDEF.nested_types_by_name['ArgAttrEntry']
+_FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY = _FUNCTIONDEF.nested_types_by_name['ResourceArgUniqueIdEntry']
+_FUNCTIONDEF_RETENTRY = _FUNCTIONDEF.nested_types_by_name['RetEntry']
+_FUNCTIONDEF_CONTROLRETENTRY = _FUNCTIONDEF.nested_types_by_name['ControlRetEntry']
+_GRADIENTDEF = DESCRIPTOR.message_types_by_name['GradientDef']
+_REGISTEREDGRADIENT = DESCRIPTOR.message_types_by_name['RegisteredGradient']
+FunctionDefLibrary = _reflection.GeneratedProtocolMessageType('FunctionDefLibrary', (_message.Message,), {
+  'DESCRIPTOR' : _FUNCTIONDEFLIBRARY,
+  '__module__' : 'tensorboard.compat.proto.function_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.FunctionDefLibrary)
+  })
+_sym_db.RegisterMessage(FunctionDefLibrary)
+
+FunctionDef = _reflection.GeneratedProtocolMessageType('FunctionDef', (_message.Message,), {
+
+  'AttrEntry' : _reflection.GeneratedProtocolMessageType('AttrEntry', (_message.Message,), {
+    'DESCRIPTOR' : _FUNCTIONDEF_ATTRENTRY,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.AttrEntry)
+    })
+  ,
+
+  'ArgAttrs' : _reflection.GeneratedProtocolMessageType('ArgAttrs', (_message.Message,), {
+
+    'AttrEntry' : _reflection.GeneratedProtocolMessageType('AttrEntry', (_message.Message,), {
+      'DESCRIPTOR' : _FUNCTIONDEF_ARGATTRS_ATTRENTRY,
+      '__module__' : 'tensorboard.compat.proto.function_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.ArgAttrs.AttrEntry)
+      })
+    ,
+    'DESCRIPTOR' : _FUNCTIONDEF_ARGATTRS,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.ArgAttrs)
+    })
+  ,
+
+  'ArgAttrEntry' : _reflection.GeneratedProtocolMessageType('ArgAttrEntry', (_message.Message,), {
+    'DESCRIPTOR' : _FUNCTIONDEF_ARGATTRENTRY,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.ArgAttrEntry)
+    })
+  ,
+
+  'ResourceArgUniqueIdEntry' : _reflection.GeneratedProtocolMessageType('ResourceArgUniqueIdEntry', (_message.Message,), {
+    'DESCRIPTOR' : _FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.ResourceArgUniqueIdEntry)
+    })
+  ,
+
+  'RetEntry' : _reflection.GeneratedProtocolMessageType('RetEntry', (_message.Message,), {
+    'DESCRIPTOR' : _FUNCTIONDEF_RETENTRY,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.RetEntry)
+    })
+  ,
+
+  'ControlRetEntry' : _reflection.GeneratedProtocolMessageType('ControlRetEntry', (_message.Message,), {
+    'DESCRIPTOR' : _FUNCTIONDEF_CONTROLRETENTRY,
+    '__module__' : 'tensorboard.compat.proto.function_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef.ControlRetEntry)
+    })
+  ,
+  'DESCRIPTOR' : _FUNCTIONDEF,
+  '__module__' : 'tensorboard.compat.proto.function_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.FunctionDef)
+  })
+_sym_db.RegisterMessage(FunctionDef)
+_sym_db.RegisterMessage(FunctionDef.AttrEntry)
+_sym_db.RegisterMessage(FunctionDef.ArgAttrs)
+_sym_db.RegisterMessage(FunctionDef.ArgAttrs.AttrEntry)
+_sym_db.RegisterMessage(FunctionDef.ArgAttrEntry)
+_sym_db.RegisterMessage(FunctionDef.ResourceArgUniqueIdEntry)
+_sym_db.RegisterMessage(FunctionDef.RetEntry)
+_sym_db.RegisterMessage(FunctionDef.ControlRetEntry)
+
+GradientDef = _reflection.GeneratedProtocolMessageType('GradientDef', (_message.Message,), {
+  'DESCRIPTOR' : _GRADIENTDEF,
+  '__module__' : 'tensorboard.compat.proto.function_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.GradientDef)
+  })
+_sym_db.RegisterMessage(GradientDef)
+
+RegisteredGradient = _reflection.GeneratedProtocolMessageType('RegisteredGradient', (_message.Message,), {
+  'DESCRIPTOR' : _REGISTEREDGRADIENT,
+  '__module__' : 'tensorboard.compat.proto.function_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.RegisteredGradient)
+  })
+_sym_db.RegisterMessage(RegisteredGradient)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\016FunctionProtosP\001ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/function_go_proto\370\001\001'
+  _FUNCTIONDEF_ATTRENTRY._options = None
+  _FUNCTIONDEF_ATTRENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEF_ARGATTRS_ATTRENTRY._options = None
+  _FUNCTIONDEF_ARGATTRS_ATTRENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEF_ARGATTRENTRY._options = None
+  _FUNCTIONDEF_ARGATTRENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY._options = None
+  _FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEF_RETENTRY._options = None
+  _FUNCTIONDEF_RETENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEF_CONTROLRETENTRY._options = None
+  _FUNCTIONDEF_CONTROLRETENTRY._serialized_options = b'8\001'
+  _FUNCTIONDEFLIBRARY._serialized_start=180
+  _FUNCTIONDEFLIBRARY._serialized_end=351
+  _FUNCTIONDEF._serialized_start=354
+  _FUNCTIONDEF._serialized_end=1201
+  _FUNCTIONDEF_ATTRENTRY._serialized_start=749
+  _FUNCTIONDEF_ATTRENTRY._serialized_end=816
+  _FUNCTIONDEF_ARGATTRS._serialized_start=819
+  _FUNCTIONDEF_ARGATTRS._serialized_end=957
+  _FUNCTIONDEF_ARGATTRS_ATTRENTRY._serialized_start=749
+  _FUNCTIONDEF_ARGATTRS_ATTRENTRY._serialized_end=816
+  _FUNCTIONDEF_ARGATTRENTRY._serialized_start=959
+  _FUNCTIONDEF_ARGATTRENTRY._serialized_end=1040
+  _FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY._serialized_start=1042
+  _FUNCTIONDEF_RESOURCEARGUNIQUEIDENTRY._serialized_end=1100
+  _FUNCTIONDEF_RETENTRY._serialized_start=1102
+  _FUNCTIONDEF_RETENTRY._serialized_end=1144
+  _FUNCTIONDEF_CONTROLRETENTRY._serialized_start=1146
+  _FUNCTIONDEF_CONTROLRETENTRY._serialized_end=1195
+  _GRADIENTDEF._serialized_start=1203
+  _GRADIENTDEF._serialized_end=1262
+  _REGISTEREDGRADIENT._serialized_start=1264
+  _REGISTEREDGRADIENT._serialized_end=1335
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/graph_debug_info_pb2.py

@@ -0,0 +1,111 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/graph_debug_info.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/compat/proto/graph_debug_info.proto\x12\x0btensorboard\"\xab\x06\n\x0eGraphDebugInfo\x12\r\n\x05\x66iles\x18\x01 \x03(\t\x12\x41\n\x0c\x66rames_by_id\x18\x04 \x03(\x0b\x32+.tensorboard.GraphDebugInfo.FramesByIdEntry\x12\x41\n\x0ctraces_by_id\x18\x06 \x03(\x0b\x32+.tensorboard.GraphDebugInfo.TracesByIdEntry\x12\x37\n\x06traces\x18\x02 \x03(\x0b\x32\'.tensorboard.GraphDebugInfo.TracesEntry\x12H\n\x10name_to_trace_id\x18\x05 \x03(\x0b\x32..tensorboard.GraphDebugInfo.NameToTraceIdEntry\x1aX\n\x0b\x46ileLineCol\x12\x12\n\nfile_index\x18\x01 \x01(\x05\x12\x0c\n\x04line\x18\x02 \x01(\x05\x12\x0b\n\x03\x63ol\x18\x03 \x01(\x05\x12\x0c\n\x04\x66unc\x18\x04 \x01(\t\x12\x0c\n\x04\x63ode\x18\x05 \x01(\t\x1a\x63\n\nStackTrace\x12?\n\x0e\x66ile_line_cols\x18\x01 \x03(\x0b\x32\'.tensorboard.GraphDebugInfo.FileLineCol\x12\x14\n\x08\x66rame_id\x18\x02 \x03(\x06\x42\x02\x10\x01\x1aZ\n\x0f\x46ramesByIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\x06\x12\x36\n\x05value\x18\x02 \x01(\x0b\x32\'.tensorboard.GraphDebugInfo.FileLineCol:\x02\x38\x01\x1aY\n\x0fTracesByIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\x06\x12\x35\n\x05value\x18\x02 \x01(\x0b\x32&.tensorboard.GraphDebugInfo.StackTrace:\x02\x38\x01\x1aU\n\x0bTracesEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\x35\n\x05value\x18\x02 \x01(\x0b\x32&.tensorboard.GraphDebugInfo.StackTrace:\x02\x38\x01\x1a\x34\n\x12NameToTraceIdEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x06:\x02\x38\x01\x42\x8c\x01\n\x18org.tensorflow.frameworkB\x14GraphDebugInfoProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01')
+
+
+
+_GRAPHDEBUGINFO = DESCRIPTOR.message_types_by_name['GraphDebugInfo']
+_GRAPHDEBUGINFO_FILELINECOL = _GRAPHDEBUGINFO.nested_types_by_name['FileLineCol']
+_GRAPHDEBUGINFO_STACKTRACE = _GRAPHDEBUGINFO.nested_types_by_name['StackTrace']
+_GRAPHDEBUGINFO_FRAMESBYIDENTRY = _GRAPHDEBUGINFO.nested_types_by_name['FramesByIdEntry']
+_GRAPHDEBUGINFO_TRACESBYIDENTRY = _GRAPHDEBUGINFO.nested_types_by_name['TracesByIdEntry']
+_GRAPHDEBUGINFO_TRACESENTRY = _GRAPHDEBUGINFO.nested_types_by_name['TracesEntry']
+_GRAPHDEBUGINFO_NAMETOTRACEIDENTRY = _GRAPHDEBUGINFO.nested_types_by_name['NameToTraceIdEntry']
+GraphDebugInfo = _reflection.GeneratedProtocolMessageType('GraphDebugInfo', (_message.Message,), {
+
+  'FileLineCol' : _reflection.GeneratedProtocolMessageType('FileLineCol', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_FILELINECOL,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.FileLineCol)
+    })
+  ,
+
+  'StackTrace' : _reflection.GeneratedProtocolMessageType('StackTrace', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_STACKTRACE,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.StackTrace)
+    })
+  ,
+
+  'FramesByIdEntry' : _reflection.GeneratedProtocolMessageType('FramesByIdEntry', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_FRAMESBYIDENTRY,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.FramesByIdEntry)
+    })
+  ,
+
+  'TracesByIdEntry' : _reflection.GeneratedProtocolMessageType('TracesByIdEntry', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_TRACESBYIDENTRY,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.TracesByIdEntry)
+    })
+  ,
+
+  'TracesEntry' : _reflection.GeneratedProtocolMessageType('TracesEntry', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_TRACESENTRY,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.TracesEntry)
+    })
+  ,
+
+  'NameToTraceIdEntry' : _reflection.GeneratedProtocolMessageType('NameToTraceIdEntry', (_message.Message,), {
+    'DESCRIPTOR' : _GRAPHDEBUGINFO_NAMETOTRACEIDENTRY,
+    '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo.NameToTraceIdEntry)
+    })
+  ,
+  'DESCRIPTOR' : _GRAPHDEBUGINFO,
+  '__module__' : 'tensorboard.compat.proto.graph_debug_info_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.GraphDebugInfo)
+  })
+_sym_db.RegisterMessage(GraphDebugInfo)
+_sym_db.RegisterMessage(GraphDebugInfo.FileLineCol)
+_sym_db.RegisterMessage(GraphDebugInfo.StackTrace)
+_sym_db.RegisterMessage(GraphDebugInfo.FramesByIdEntry)
+_sym_db.RegisterMessage(GraphDebugInfo.TracesByIdEntry)
+_sym_db.RegisterMessage(GraphDebugInfo.TracesEntry)
+_sym_db.RegisterMessage(GraphDebugInfo.NameToTraceIdEntry)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\024GraphDebugInfoProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _GRAPHDEBUGINFO_STACKTRACE.fields_by_name['frame_id']._options = None
+  _GRAPHDEBUGINFO_STACKTRACE.fields_by_name['frame_id']._serialized_options = b'\020\001'
+  _GRAPHDEBUGINFO_FRAMESBYIDENTRY._options = None
+  _GRAPHDEBUGINFO_FRAMESBYIDENTRY._serialized_options = b'8\001'
+  _GRAPHDEBUGINFO_TRACESBYIDENTRY._options = None
+  _GRAPHDEBUGINFO_TRACESBYIDENTRY._serialized_options = b'8\001'
+  _GRAPHDEBUGINFO_TRACESENTRY._options = None
+  _GRAPHDEBUGINFO_TRACESENTRY._serialized_options = b'8\001'
+  _GRAPHDEBUGINFO_NAMETOTRACEIDENTRY._options = None
+  _GRAPHDEBUGINFO_NAMETOTRACEIDENTRY._serialized_options = b'8\001'
+  _GRAPHDEBUGINFO._serialized_start=65
+  _GRAPHDEBUGINFO._serialized_end=876
+  _GRAPHDEBUGINFO_FILELINECOL._serialized_start=363
+  _GRAPHDEBUGINFO_FILELINECOL._serialized_end=451
+  _GRAPHDEBUGINFO_STACKTRACE._serialized_start=453
+  _GRAPHDEBUGINFO_STACKTRACE._serialized_end=552
+  _GRAPHDEBUGINFO_FRAMESBYIDENTRY._serialized_start=554
+  _GRAPHDEBUGINFO_FRAMESBYIDENTRY._serialized_end=644
+  _GRAPHDEBUGINFO_TRACESBYIDENTRY._serialized_start=646
+  _GRAPHDEBUGINFO_TRACESBYIDENTRY._serialized_end=735
+  _GRAPHDEBUGINFO_TRACESENTRY._serialized_start=737
+  _GRAPHDEBUGINFO_TRACESENTRY._serialized_end=822
+  _GRAPHDEBUGINFO_NAMETOTRACEIDENTRY._serialized_start=824
+  _GRAPHDEBUGINFO_NAMETOTRACEIDENTRY._serialized_end=876
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/graph_pb2.py

@@ -0,0 +1,41 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/graph.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()
+
+
+from tensorboard.compat.proto import function_pb2 as tensorboard_dot_compat_dot_proto_dot_function__pb2
+from tensorboard.compat.proto import graph_debug_info_pb2 as tensorboard_dot_compat_dot_proto_dot_graph__debug__info__pb2
+from tensorboard.compat.proto import node_def_pb2 as tensorboard_dot_compat_dot_proto_dot_node__def__pb2
+from tensorboard.compat.proto import versions_pb2 as tensorboard_dot_compat_dot_proto_dot_versions__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n$tensorboard/compat/proto/graph.proto\x12\x0btensorboard\x1a\'tensorboard/compat/proto/function.proto\x1a/tensorboard/compat/proto/graph_debug_info.proto\x1a\'tensorboard/compat/proto/node_def.proto\x1a\'tensorboard/compat/proto/versions.proto\"\xd1\x01\n\x08GraphDef\x12\"\n\x04node\x18\x01 \x03(\x0b\x32\x14.tensorboard.NodeDef\x12)\n\x08versions\x18\x04 \x01(\x0b\x32\x17.tensorboard.VersionDef\x12\x13\n\x07version\x18\x03 \x01(\x05\x42\x02\x18\x01\x12\x30\n\x07library\x18\x02 \x01(\x0b\x32\x1f.tensorboard.FunctionDefLibrary\x12/\n\ndebug_info\x18\x05 \x01(\x0b\x32\x1b.tensorboard.GraphDebugInfoBz\n\x18org.tensorflow.frameworkB\x0bGraphProtosP\x01ZLgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/graph_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_GRAPHDEF = DESCRIPTOR.message_types_by_name['GraphDef']
+GraphDef = _reflection.GeneratedProtocolMessageType('GraphDef', (_message.Message,), {
+  'DESCRIPTOR' : _GRAPHDEF,
+  '__module__' : 'tensorboard.compat.proto.graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.GraphDef)
+  })
+_sym_db.RegisterMessage(GraphDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\013GraphProtosP\001ZLgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/graph_go_proto\370\001\001'
+  _GRAPHDEF.fields_by_name['version']._options = None
+  _GRAPHDEF.fields_by_name['version']._serialized_options = b'\030\001'
+  _GRAPHDEF._serialized_start=226
+  _GRAPHDEF._serialized_end=435
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/histogram_pb2.py

@@ -0,0 +1,39 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/histogram.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/compat/proto/histogram.proto\x12\x0btensorboard\"\x87\x01\n\x0eHistogramProto\x12\x0b\n\x03min\x18\x01 \x01(\x01\x12\x0b\n\x03max\x18\x02 \x01(\x01\x12\x0b\n\x03num\x18\x03 \x01(\x01\x12\x0b\n\x03sum\x18\x04 \x01(\x01\x12\x13\n\x0bsum_squares\x18\x05 \x01(\x01\x12\x18\n\x0c\x62ucket_limit\x18\x06 \x03(\x01\x42\x02\x10\x01\x12\x12\n\x06\x62ucket\x18\x07 \x03(\x01\x42\x02\x10\x01\x42\\\n\x18org.tensorflow.frameworkP\x01Z;github.com/google/tsl/tsl/go/core/protobuf/summary_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_HISTOGRAMPROTO = DESCRIPTOR.message_types_by_name['HistogramProto']
+HistogramProto = _reflection.GeneratedProtocolMessageType('HistogramProto', (_message.Message,), {
+  'DESCRIPTOR' : _HISTOGRAMPROTO,
+  '__module__' : 'tensorboard.compat.proto.histogram_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.HistogramProto)
+  })
+_sym_db.RegisterMessage(HistogramProto)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkP\001Z;github.com/google/tsl/tsl/go/core/protobuf/summary_go_proto\370\001\001'
+  _HISTOGRAMPROTO.fields_by_name['bucket_limit']._options = None
+  _HISTOGRAMPROTO.fields_by_name['bucket_limit']._serialized_options = b'\020\001'
+  _HISTOGRAMPROTO.fields_by_name['bucket']._options = None
+  _HISTOGRAMPROTO.fields_by_name['bucket']._serialized_options = b'\020\001'
+  _HISTOGRAMPROTO._serialized_start=58
+  _HISTOGRAMPROTO._serialized_end=193
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/meta_graph_pb2.py

@@ -0,0 +1,254 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/meta_graph.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()
+
+
+from google.protobuf import any_pb2 as google_dot_protobuf_dot_any__pb2
+from tensorboard.compat.proto import graph_pb2 as tensorboard_dot_compat_dot_proto_dot_graph__pb2
+from tensorboard.compat.proto import op_def_pb2 as tensorboard_dot_compat_dot_proto_dot_op__def__pb2
+from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+from tensorboard.compat.proto import saved_object_graph_pb2 as tensorboard_dot_compat_dot_proto_dot_saved__object__graph__pb2
+from tensorboard.compat.proto import saver_pb2 as tensorboard_dot_compat_dot_proto_dot_saver__pb2
+from tensorboard.compat.proto import struct_pb2 as tensorboard_dot_compat_dot_proto_dot_struct__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n)tensorboard/compat/proto/meta_graph.proto\x12\x0btensorboard\x1a\x19google/protobuf/any.proto\x1a$tensorboard/compat/proto/graph.proto\x1a%tensorboard/compat/proto/op_def.proto\x1a%tensorboard/compat/proto/tensor.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\x1a\x31tensorboard/compat/proto/saved_object_graph.proto\x1a$tensorboard/compat/proto/saver.proto\x1a%tensorboard/compat/proto/struct.proto\"\xb3\x07\n\x0cMetaGraphDef\x12<\n\rmeta_info_def\x18\x01 \x01(\x0b\x32%.tensorboard.MetaGraphDef.MetaInfoDef\x12(\n\tgraph_def\x18\x02 \x01(\x0b\x32\x15.tensorboard.GraphDef\x12(\n\tsaver_def\x18\x03 \x01(\x0b\x32\x15.tensorboard.SaverDef\x12\x44\n\x0e\x63ollection_def\x18\x04 \x03(\x0b\x32,.tensorboard.MetaGraphDef.CollectionDefEntry\x12\x42\n\rsignature_def\x18\x05 \x03(\x0b\x32+.tensorboard.MetaGraphDef.SignatureDefEntry\x12\x31\n\x0e\x61sset_file_def\x18\x06 \x03(\x0b\x32\x19.tensorboard.AssetFileDef\x12\x37\n\x10object_graph_def\x18\x07 \x01(\x0b\x32\x1d.tensorboard.SavedObjectGraph\x1a\xf8\x02\n\x0bMetaInfoDef\x12\x1a\n\x12meta_graph_version\x18\x01 \x01(\t\x12-\n\x10stripped_op_list\x18\x02 \x01(\x0b\x32\x13.tensorboard.OpList\x12&\n\x08\x61ny_info\x18\x03 \x01(\x0b\x32\x14.google.protobuf.Any\x12\x0c\n\x04tags\x18\x04 \x03(\t\x12\x1a\n\x12tensorflow_version\x18\x05 \x01(\t\x12\x1e\n\x16tensorflow_git_version\x18\x06 \x01(\t\x12\x1e\n\x16stripped_default_attrs\x18\x07 \x01(\x08\x12T\n\x10\x66unction_aliases\x18\x08 \x03(\x0b\x32:.tensorboard.MetaGraphDef.MetaInfoDef.FunctionAliasesEntry\x1a\x36\n\x14\x46unctionAliasesEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\x1aP\n\x12\x43ollectionDefEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12)\n\x05value\x18\x02 \x01(\x0b\x32\x1a.tensorboard.CollectionDef:\x02\x38\x01\x1aN\n\x11SignatureDefEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12(\n\x05value\x18\x02 \x01(\x0b\x32\x19.tensorboard.SignatureDef:\x02\x38\x01\"\xe4\x03\n\rCollectionDef\x12\x38\n\tnode_list\x18\x01 \x01(\x0b\x32#.tensorboard.CollectionDef.NodeListH\x00\x12:\n\nbytes_list\x18\x02 \x01(\x0b\x32$.tensorboard.CollectionDef.BytesListH\x00\x12:\n\nint64_list\x18\x03 \x01(\x0b\x32$.tensorboard.CollectionDef.Int64ListH\x00\x12:\n\nfloat_list\x18\x04 \x01(\x0b\x32$.tensorboard.CollectionDef.FloatListH\x00\x12\x36\n\x08\x61ny_list\x18\x05 \x01(\x0b\x32\".tensorboard.CollectionDef.AnyListH\x00\x1a\x19\n\x08NodeList\x12\r\n\x05value\x18\x01 \x03(\t\x1a\x1a\n\tBytesList\x12\r\n\x05value\x18\x01 \x03(\x0c\x1a\x1e\n\tInt64List\x12\x11\n\x05value\x18\x01 \x03(\x03\x42\x02\x10\x01\x1a\x1e\n\tFloatList\x12\x11\n\x05value\x18\x01 \x03(\x02\x42\x02\x10\x01\x1a.\n\x07\x41nyList\x12#\n\x05value\x18\x01 \x03(\x0b\x32\x14.google.protobuf.AnyB\x06\n\x04kind\"\xd7\x03\n\nTensorInfo\x12\x0e\n\x04name\x18\x01 \x01(\tH\x00\x12\x37\n\ncoo_sparse\x18\x04 \x01(\x0b\x32!.tensorboard.TensorInfo.CooSparseH\x00\x12\x43\n\x10\x63omposite_tensor\x18\x05 \x01(\x0b\x32\'.tensorboard.TensorInfo.CompositeTensorH\x00\x12$\n\x05\x64type\x18\x02 \x01(\x0e\x32\x15.tensorboard.DataType\x12\x33\n\x0ctensor_shape\x18\x03 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x1a\x65\n\tCooSparse\x12\x1a\n\x12values_tensor_name\x18\x01 \x01(\t\x12\x1b\n\x13indices_tensor_name\x18\x02 \x01(\t\x12\x1f\n\x17\x64\x65nse_shape_tensor_name\x18\x03 \x01(\t\x1am\n\x0f\x43ompositeTensor\x12-\n\ttype_spec\x18\x01 \x01(\x0b\x32\x1a.tensorboard.TypeSpecProto\x12+\n\ncomponents\x18\x02 \x03(\x0b\x32\x17.tensorboard.TensorInfoB\n\n\x08\x65ncoding\"\xaa\x03\n\x0cSignatureDef\x12\x35\n\x06inputs\x18\x01 \x03(\x0b\x32%.tensorboard.SignatureDef.InputsEntry\x12\x37\n\x07outputs\x18\x02 \x03(\x0b\x32&.tensorboard.SignatureDef.OutputsEntry\x12\x13\n\x0bmethod_name\x18\x03 \x01(\t\x12\x39\n\x08\x64\x65\x66\x61ults\x18\x04 \x03(\x0b\x32\'.tensorboard.SignatureDef.DefaultsEntry\x1a\x46\n\x0bInputsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12&\n\x05value\x18\x02 \x01(\x0b\x32\x17.tensorboard.TensorInfo:\x02\x38\x01\x1aG\n\x0cOutputsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12&\n\x05value\x18\x02 \x01(\x0b\x32\x17.tensorboard.TensorInfo:\x02\x38\x01\x1aI\n\rDefaultsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\'\n\x05value\x18\x02 \x01(\x0b\x32\x18.tensorboard.TensorProto:\x02\x38\x01\"N\n\x0c\x41ssetFileDef\x12,\n\x0btensor_info\x18\x01 \x01(\x0b\x32\x17.tensorboard.TensorInfo\x12\x10\n\x08\x66ilename\x18\x02 \x01(\tB\x87\x01\n\x18org.tensorflow.frameworkB\x0fMetaGraphProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_METAGRAPHDEF = DESCRIPTOR.message_types_by_name['MetaGraphDef']
+_METAGRAPHDEF_METAINFODEF = _METAGRAPHDEF.nested_types_by_name['MetaInfoDef']
+_METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY = _METAGRAPHDEF_METAINFODEF.nested_types_by_name['FunctionAliasesEntry']
+_METAGRAPHDEF_COLLECTIONDEFENTRY = _METAGRAPHDEF.nested_types_by_name['CollectionDefEntry']
+_METAGRAPHDEF_SIGNATUREDEFENTRY = _METAGRAPHDEF.nested_types_by_name['SignatureDefEntry']
+_COLLECTIONDEF = DESCRIPTOR.message_types_by_name['CollectionDef']
+_COLLECTIONDEF_NODELIST = _COLLECTIONDEF.nested_types_by_name['NodeList']
+_COLLECTIONDEF_BYTESLIST = _COLLECTIONDEF.nested_types_by_name['BytesList']
+_COLLECTIONDEF_INT64LIST = _COLLECTIONDEF.nested_types_by_name['Int64List']
+_COLLECTIONDEF_FLOATLIST = _COLLECTIONDEF.nested_types_by_name['FloatList']
+_COLLECTIONDEF_ANYLIST = _COLLECTIONDEF.nested_types_by_name['AnyList']
+_TENSORINFO = DESCRIPTOR.message_types_by_name['TensorInfo']
+_TENSORINFO_COOSPARSE = _TENSORINFO.nested_types_by_name['CooSparse']
+_TENSORINFO_COMPOSITETENSOR = _TENSORINFO.nested_types_by_name['CompositeTensor']
+_SIGNATUREDEF = DESCRIPTOR.message_types_by_name['SignatureDef']
+_SIGNATUREDEF_INPUTSENTRY = _SIGNATUREDEF.nested_types_by_name['InputsEntry']
+_SIGNATUREDEF_OUTPUTSENTRY = _SIGNATUREDEF.nested_types_by_name['OutputsEntry']
+_SIGNATUREDEF_DEFAULTSENTRY = _SIGNATUREDEF.nested_types_by_name['DefaultsEntry']
+_ASSETFILEDEF = DESCRIPTOR.message_types_by_name['AssetFileDef']
+MetaGraphDef = _reflection.GeneratedProtocolMessageType('MetaGraphDef', (_message.Message,), {
+
+  'MetaInfoDef' : _reflection.GeneratedProtocolMessageType('MetaInfoDef', (_message.Message,), {
+
+    'FunctionAliasesEntry' : _reflection.GeneratedProtocolMessageType('FunctionAliasesEntry', (_message.Message,), {
+      'DESCRIPTOR' : _METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY,
+      '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.MetaGraphDef.MetaInfoDef.FunctionAliasesEntry)
+      })
+    ,
+    'DESCRIPTOR' : _METAGRAPHDEF_METAINFODEF,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.MetaGraphDef.MetaInfoDef)
+    })
+  ,
+
+  'CollectionDefEntry' : _reflection.GeneratedProtocolMessageType('CollectionDefEntry', (_message.Message,), {
+    'DESCRIPTOR' : _METAGRAPHDEF_COLLECTIONDEFENTRY,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.MetaGraphDef.CollectionDefEntry)
+    })
+  ,
+
+  'SignatureDefEntry' : _reflection.GeneratedProtocolMessageType('SignatureDefEntry', (_message.Message,), {
+    'DESCRIPTOR' : _METAGRAPHDEF_SIGNATUREDEFENTRY,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.MetaGraphDef.SignatureDefEntry)
+    })
+  ,
+  'DESCRIPTOR' : _METAGRAPHDEF,
+  '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.MetaGraphDef)
+  })
+_sym_db.RegisterMessage(MetaGraphDef)
+_sym_db.RegisterMessage(MetaGraphDef.MetaInfoDef)
+_sym_db.RegisterMessage(MetaGraphDef.MetaInfoDef.FunctionAliasesEntry)
+_sym_db.RegisterMessage(MetaGraphDef.CollectionDefEntry)
+_sym_db.RegisterMessage(MetaGraphDef.SignatureDefEntry)
+
+CollectionDef = _reflection.GeneratedProtocolMessageType('CollectionDef', (_message.Message,), {
+
+  'NodeList' : _reflection.GeneratedProtocolMessageType('NodeList', (_message.Message,), {
+    'DESCRIPTOR' : _COLLECTIONDEF_NODELIST,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef.NodeList)
+    })
+  ,
+
+  'BytesList' : _reflection.GeneratedProtocolMessageType('BytesList', (_message.Message,), {
+    'DESCRIPTOR' : _COLLECTIONDEF_BYTESLIST,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef.BytesList)
+    })
+  ,
+
+  'Int64List' : _reflection.GeneratedProtocolMessageType('Int64List', (_message.Message,), {
+    'DESCRIPTOR' : _COLLECTIONDEF_INT64LIST,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef.Int64List)
+    })
+  ,
+
+  'FloatList' : _reflection.GeneratedProtocolMessageType('FloatList', (_message.Message,), {
+    'DESCRIPTOR' : _COLLECTIONDEF_FLOATLIST,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef.FloatList)
+    })
+  ,
+
+  'AnyList' : _reflection.GeneratedProtocolMessageType('AnyList', (_message.Message,), {
+    'DESCRIPTOR' : _COLLECTIONDEF_ANYLIST,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef.AnyList)
+    })
+  ,
+  'DESCRIPTOR' : _COLLECTIONDEF,
+  '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CollectionDef)
+  })
+_sym_db.RegisterMessage(CollectionDef)
+_sym_db.RegisterMessage(CollectionDef.NodeList)
+_sym_db.RegisterMessage(CollectionDef.BytesList)
+_sym_db.RegisterMessage(CollectionDef.Int64List)
+_sym_db.RegisterMessage(CollectionDef.FloatList)
+_sym_db.RegisterMessage(CollectionDef.AnyList)
+
+TensorInfo = _reflection.GeneratedProtocolMessageType('TensorInfo', (_message.Message,), {
+
+  'CooSparse' : _reflection.GeneratedProtocolMessageType('CooSparse', (_message.Message,), {
+    'DESCRIPTOR' : _TENSORINFO_COOSPARSE,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.TensorInfo.CooSparse)
+    })
+  ,
+
+  'CompositeTensor' : _reflection.GeneratedProtocolMessageType('CompositeTensor', (_message.Message,), {
+    'DESCRIPTOR' : _TENSORINFO_COMPOSITETENSOR,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.TensorInfo.CompositeTensor)
+    })
+  ,
+  'DESCRIPTOR' : _TENSORINFO,
+  '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TensorInfo)
+  })
+_sym_db.RegisterMessage(TensorInfo)
+_sym_db.RegisterMessage(TensorInfo.CooSparse)
+_sym_db.RegisterMessage(TensorInfo.CompositeTensor)
+
+SignatureDef = _reflection.GeneratedProtocolMessageType('SignatureDef', (_message.Message,), {
+
+  'InputsEntry' : _reflection.GeneratedProtocolMessageType('InputsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _SIGNATUREDEF_INPUTSENTRY,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SignatureDef.InputsEntry)
+    })
+  ,
+
+  'OutputsEntry' : _reflection.GeneratedProtocolMessageType('OutputsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _SIGNATUREDEF_OUTPUTSENTRY,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SignatureDef.OutputsEntry)
+    })
+  ,
+
+  'DefaultsEntry' : _reflection.GeneratedProtocolMessageType('DefaultsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _SIGNATUREDEF_DEFAULTSENTRY,
+    '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SignatureDef.DefaultsEntry)
+    })
+  ,
+  'DESCRIPTOR' : _SIGNATUREDEF,
+  '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SignatureDef)
+  })
+_sym_db.RegisterMessage(SignatureDef)
+_sym_db.RegisterMessage(SignatureDef.InputsEntry)
+_sym_db.RegisterMessage(SignatureDef.OutputsEntry)
+_sym_db.RegisterMessage(SignatureDef.DefaultsEntry)
+
+AssetFileDef = _reflection.GeneratedProtocolMessageType('AssetFileDef', (_message.Message,), {
+  'DESCRIPTOR' : _ASSETFILEDEF,
+  '__module__' : 'tensorboard.compat.proto.meta_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AssetFileDef)
+  })
+_sym_db.RegisterMessage(AssetFileDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\017MetaGraphProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY._options = None
+  _METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY._serialized_options = b'8\001'
+  _METAGRAPHDEF_COLLECTIONDEFENTRY._options = None
+  _METAGRAPHDEF_COLLECTIONDEFENTRY._serialized_options = b'8\001'
+  _METAGRAPHDEF_SIGNATUREDEFENTRY._options = None
+  _METAGRAPHDEF_SIGNATUREDEFENTRY._serialized_options = b'8\001'
+  _COLLECTIONDEF_INT64LIST.fields_by_name['value']._options = None
+  _COLLECTIONDEF_INT64LIST.fields_by_name['value']._serialized_options = b'\020\001'
+  _COLLECTIONDEF_FLOATLIST.fields_by_name['value']._options = None
+  _COLLECTIONDEF_FLOATLIST.fields_by_name['value']._serialized_options = b'\020\001'
+  _SIGNATUREDEF_INPUTSENTRY._options = None
+  _SIGNATUREDEF_INPUTSENTRY._serialized_options = b'8\001'
+  _SIGNATUREDEF_OUTPUTSENTRY._options = None
+  _SIGNATUREDEF_OUTPUTSENTRY._serialized_options = b'8\001'
+  _SIGNATUREDEF_DEFAULTSENTRY._options = None
+  _SIGNATUREDEF_DEFAULTSENTRY._serialized_options = b'8\001'
+  _METAGRAPHDEF._serialized_start=413
+  _METAGRAPHDEF._serialized_end=1360
+  _METAGRAPHDEF_METAINFODEF._serialized_start=822
+  _METAGRAPHDEF_METAINFODEF._serialized_end=1198
+  _METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY._serialized_start=1144
+  _METAGRAPHDEF_METAINFODEF_FUNCTIONALIASESENTRY._serialized_end=1198
+  _METAGRAPHDEF_COLLECTIONDEFENTRY._serialized_start=1200
+  _METAGRAPHDEF_COLLECTIONDEFENTRY._serialized_end=1280
+  _METAGRAPHDEF_SIGNATUREDEFENTRY._serialized_start=1282
+  _METAGRAPHDEF_SIGNATUREDEFENTRY._serialized_end=1360
+  _COLLECTIONDEF._serialized_start=1363
+  _COLLECTIONDEF._serialized_end=1847
+  _COLLECTIONDEF_NODELIST._serialized_start=1674
+  _COLLECTIONDEF_NODELIST._serialized_end=1699
+  _COLLECTIONDEF_BYTESLIST._serialized_start=1701
+  _COLLECTIONDEF_BYTESLIST._serialized_end=1727
+  _COLLECTIONDEF_INT64LIST._serialized_start=1729
+  _COLLECTIONDEF_INT64LIST._serialized_end=1759
+  _COLLECTIONDEF_FLOATLIST._serialized_start=1761
+  _COLLECTIONDEF_FLOATLIST._serialized_end=1791
+  _COLLECTIONDEF_ANYLIST._serialized_start=1793
+  _COLLECTIONDEF_ANYLIST._serialized_end=1839
+  _TENSORINFO._serialized_start=1850
+  _TENSORINFO._serialized_end=2321
+  _TENSORINFO_COOSPARSE._serialized_start=2097
+  _TENSORINFO_COOSPARSE._serialized_end=2198
+  _TENSORINFO_COMPOSITETENSOR._serialized_start=2200
+  _TENSORINFO_COMPOSITETENSOR._serialized_end=2309
+  _SIGNATUREDEF._serialized_start=2324
+  _SIGNATUREDEF._serialized_end=2750
+  _SIGNATUREDEF_INPUTSENTRY._serialized_start=2532
+  _SIGNATUREDEF_INPUTSENTRY._serialized_end=2602
+  _SIGNATUREDEF_OUTPUTSENTRY._serialized_start=2604
+  _SIGNATUREDEF_OUTPUTSENTRY._serialized_end=2675
+  _SIGNATUREDEF_DEFAULTSENTRY._serialized_start=2677
+  _SIGNATUREDEF_DEFAULTSENTRY._serialized_end=2750
+  _ASSETFILEDEF._serialized_start=2752
+  _ASSETFILEDEF._serialized_end=2830
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/node_def_pb2.py

@@ -0,0 +1,61 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/node_def.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()
+
+
+from tensorboard.compat.proto import attr_value_pb2 as tensorboard_dot_compat_dot_proto_dot_attr__value__pb2
+from tensorboard.compat.proto import full_type_pb2 as tensorboard_dot_compat_dot_proto_dot_full__type__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\'tensorboard/compat/proto/node_def.proto\x12\x0btensorboard\x1a)tensorboard/compat/proto/attr_value.proto\x1a(tensorboard/compat/proto/full_type.proto\"\x8a\x03\n\x07NodeDef\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\n\n\x02op\x18\x02 \x01(\t\x12\r\n\x05input\x18\x03 \x03(\t\x12\x0e\n\x06\x64\x65vice\x18\x04 \x01(\t\x12,\n\x04\x61ttr\x18\x05 \x03(\x0b\x32\x1e.tensorboard.NodeDef.AttrEntry\x12K\n\x17\x65xperimental_debug_info\x18\x06 \x01(\x0b\x32*.tensorboard.NodeDef.ExperimentalDebugInfo\x12\x33\n\x11\x65xperimental_type\x18\x07 \x01(\x0b\x32\x18.tensorboard.FullTypeDef\x1a\x43\n\tAttrEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12%\n\x05value\x18\x02 \x01(\x0b\x32\x16.tensorboard.AttrValue:\x02\x38\x01\x1aQ\n\x15\x45xperimentalDebugInfo\x12\x1b\n\x13original_node_names\x18\x01 \x03(\t\x12\x1b\n\x13original_func_names\x18\x02 \x03(\tB{\n\x18org.tensorflow.frameworkB\tNodeProtoP\x01ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/node_def_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_NODEDEF = DESCRIPTOR.message_types_by_name['NodeDef']
+_NODEDEF_ATTRENTRY = _NODEDEF.nested_types_by_name['AttrEntry']
+_NODEDEF_EXPERIMENTALDEBUGINFO = _NODEDEF.nested_types_by_name['ExperimentalDebugInfo']
+NodeDef = _reflection.GeneratedProtocolMessageType('NodeDef', (_message.Message,), {
+
+  'AttrEntry' : _reflection.GeneratedProtocolMessageType('AttrEntry', (_message.Message,), {
+    'DESCRIPTOR' : _NODEDEF_ATTRENTRY,
+    '__module__' : 'tensorboard.compat.proto.node_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.NodeDef.AttrEntry)
+    })
+  ,
+
+  'ExperimentalDebugInfo' : _reflection.GeneratedProtocolMessageType('ExperimentalDebugInfo', (_message.Message,), {
+    'DESCRIPTOR' : _NODEDEF_EXPERIMENTALDEBUGINFO,
+    '__module__' : 'tensorboard.compat.proto.node_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.NodeDef.ExperimentalDebugInfo)
+    })
+  ,
+  'DESCRIPTOR' : _NODEDEF,
+  '__module__' : 'tensorboard.compat.proto.node_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NodeDef)
+  })
+_sym_db.RegisterMessage(NodeDef)
+_sym_db.RegisterMessage(NodeDef.AttrEntry)
+_sym_db.RegisterMessage(NodeDef.ExperimentalDebugInfo)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\tNodeProtoP\001ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/node_def_go_proto\370\001\001'
+  _NODEDEF_ATTRENTRY._options = None
+  _NODEDEF_ATTRENTRY._serialized_options = b'8\001'
+  _NODEDEF._serialized_start=142
+  _NODEDEF._serialized_end=536
+  _NODEDEF_ATTRENTRY._serialized_start=386
+  _NODEDEF_ATTRENTRY._serialized_end=453
+  _NODEDEF_EXPERIMENTALDEBUGINFO._serialized_start=455
+  _NODEDEF_EXPERIMENTALDEBUGINFO._serialized_end=536
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/op_def_pb2.py

@@ -0,0 +1,81 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/op_def.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()
+
+
+from tensorboard.compat.proto import attr_value_pb2 as tensorboard_dot_compat_dot_proto_dot_attr__value__pb2
+from tensorboard.compat.proto import full_type_pb2 as tensorboard_dot_compat_dot_proto_dot_full__type__pb2
+from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n%tensorboard/compat/proto/op_def.proto\x12\x0btensorboard\x1a)tensorboard/compat/proto/attr_value.proto\x1a(tensorboard/compat/proto/full_type.proto\x1a.tensorboard/compat/proto/resource_handle.proto\x1a$tensorboard/compat/proto/types.proto\"\xfc\x06\n\x05OpDef\x12\x0c\n\x04name\x18\x01 \x01(\t\x12,\n\tinput_arg\x18\x02 \x03(\x0b\x32\x19.tensorboard.OpDef.ArgDef\x12-\n\noutput_arg\x18\x03 \x03(\x0b\x32\x19.tensorboard.OpDef.ArgDef\x12\x16\n\x0e\x63ontrol_output\x18\x14 \x03(\t\x12(\n\x04\x61ttr\x18\x04 \x03(\x0b\x32\x1a.tensorboard.OpDef.AttrDef\x12/\n\x0b\x64\x65precation\x18\x08 \x01(\x0b\x32\x1a.tensorboard.OpDeprecation\x12\x0f\n\x07summary\x18\x05 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x06 \x01(\t\x12\x16\n\x0eis_commutative\x18\x12 \x01(\x08\x12\x14\n\x0cis_aggregate\x18\x10 \x01(\x08\x12\x13\n\x0bis_stateful\x18\x11 \x01(\x08\x12\"\n\x1a\x61llows_uninitialized_input\x18\x13 \x01(\x08\x12$\n\x1cis_distributed_communication\x18\x15 \x01(\x08\x1a\x9f\x02\n\x06\x41rgDef\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x02 \x01(\t\x12#\n\x04type\x18\x03 \x01(\x0e\x32\x15.tensorboard.DataType\x12\x11\n\ttype_attr\x18\x04 \x01(\t\x12\x13\n\x0bnumber_attr\x18\x05 \x01(\t\x12\x16\n\x0etype_list_attr\x18\x06 \x01(\t\x12\x43\n\x0bhandle_data\x18\x07 \x03(\x0b\x32..tensorboard.ResourceHandleProto.DtypeAndShape\x12\x0e\n\x06is_ref\x18\x10 \x01(\x08\x12\x38\n\x16\x65xperimental_full_type\x18\x11 \x01(\x0b\x32\x18.tensorboard.FullTypeDef\x1a\xbf\x01\n\x07\x41ttrDef\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0c\n\x04type\x18\x02 \x01(\t\x12-\n\rdefault_value\x18\x03 \x01(\x0b\x32\x16.tensorboard.AttrValue\x12\x13\n\x0b\x64\x65scription\x18\x04 \x01(\t\x12\x13\n\x0bhas_minimum\x18\x05 \x01(\x08\x12\x0f\n\x07minimum\x18\x06 \x01(\x03\x12.\n\x0e\x61llowed_values\x18\x07 \x01(\x0b\x32\x16.tensorboard.AttrValue\"5\n\rOpDeprecation\x12\x0f\n\x07version\x18\x01 \x01(\x05\x12\x13\n\x0b\x65xplanation\x18\x02 \x01(\t\"(\n\x06OpList\x12\x1e\n\x02op\x18\x01 \x03(\x0b\x32\x12.tensorboard.OpDefB{\n\x18org.tensorflow.frameworkB\x0bOpDefProtosP\x01ZMgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/op_def_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_OPDEF = DESCRIPTOR.message_types_by_name['OpDef']
+_OPDEF_ARGDEF = _OPDEF.nested_types_by_name['ArgDef']
+_OPDEF_ATTRDEF = _OPDEF.nested_types_by_name['AttrDef']
+_OPDEPRECATION = DESCRIPTOR.message_types_by_name['OpDeprecation']
+_OPLIST = DESCRIPTOR.message_types_by_name['OpList']
+OpDef = _reflection.GeneratedProtocolMessageType('OpDef', (_message.Message,), {
+
+  'ArgDef' : _reflection.GeneratedProtocolMessageType('ArgDef', (_message.Message,), {
+    'DESCRIPTOR' : _OPDEF_ARGDEF,
+    '__module__' : 'tensorboard.compat.proto.op_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.OpDef.ArgDef)
+    })
+  ,
+
+  'AttrDef' : _reflection.GeneratedProtocolMessageType('AttrDef', (_message.Message,), {
+    'DESCRIPTOR' : _OPDEF_ATTRDEF,
+    '__module__' : 'tensorboard.compat.proto.op_def_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.OpDef.AttrDef)
+    })
+  ,
+  'DESCRIPTOR' : _OPDEF,
+  '__module__' : 'tensorboard.compat.proto.op_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.OpDef)
+  })
+_sym_db.RegisterMessage(OpDef)
+_sym_db.RegisterMessage(OpDef.ArgDef)
+_sym_db.RegisterMessage(OpDef.AttrDef)
+
+OpDeprecation = _reflection.GeneratedProtocolMessageType('OpDeprecation', (_message.Message,), {
+  'DESCRIPTOR' : _OPDEPRECATION,
+  '__module__' : 'tensorboard.compat.proto.op_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.OpDeprecation)
+  })
+_sym_db.RegisterMessage(OpDeprecation)
+
+OpList = _reflection.GeneratedProtocolMessageType('OpList', (_message.Message,), {
+  'DESCRIPTOR' : _OPLIST,
+  '__module__' : 'tensorboard.compat.proto.op_def_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.OpList)
+  })
+_sym_db.RegisterMessage(OpList)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\013OpDefProtosP\001ZMgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/op_def_go_proto\370\001\001'
+  _OPDEF._serialized_start=226
+  _OPDEF._serialized_end=1118
+  _OPDEF_ARGDEF._serialized_start=637
+  _OPDEF_ARGDEF._serialized_end=924
+  _OPDEF_ATTRDEF._serialized_start=927
+  _OPDEF_ATTRDEF._serialized_end=1118
+  _OPDEPRECATION._serialized_start=1120
+  _OPDEPRECATION._serialized_end=1173
+  _OPLIST._serialized_start=1175
+  _OPLIST._serialized_end=1215
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/resource_handle_pb2.py

@@ -0,0 +1,48 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/resource_handle.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()
+
+
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n.tensorboard/compat/proto/resource_handle.proto\x12\x0btensorboard\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xa8\x02\n\x13ResourceHandleProto\x12\x0e\n\x06\x64\x65vice\x18\x01 \x01(\t\x12\x11\n\tcontainer\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\x12\x11\n\thash_code\x18\x04 \x01(\x04\x12\x17\n\x0fmaybe_type_name\x18\x05 \x01(\t\x12I\n\x11\x64types_and_shapes\x18\x06 \x03(\x0b\x32..tensorboard.ResourceHandleProto.DtypeAndShape\x1a\x63\n\rDtypeAndShape\x12$\n\x05\x64type\x18\x01 \x01(\x0e\x32\x15.tensorboard.DataType\x12,\n\x05shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProtoJ\x04\x08\x07\x10\x08\x42\x87\x01\n\x18org.tensorflow.frameworkB\x0eResourceHandleP\x01ZVgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/resource_handle_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_RESOURCEHANDLEPROTO = DESCRIPTOR.message_types_by_name['ResourceHandleProto']
+_RESOURCEHANDLEPROTO_DTYPEANDSHAPE = _RESOURCEHANDLEPROTO.nested_types_by_name['DtypeAndShape']
+ResourceHandleProto = _reflection.GeneratedProtocolMessageType('ResourceHandleProto', (_message.Message,), {
+
+  'DtypeAndShape' : _reflection.GeneratedProtocolMessageType('DtypeAndShape', (_message.Message,), {
+    'DESCRIPTOR' : _RESOURCEHANDLEPROTO_DTYPEANDSHAPE,
+    '__module__' : 'tensorboard.compat.proto.resource_handle_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.ResourceHandleProto.DtypeAndShape)
+    })
+  ,
+  'DESCRIPTOR' : _RESOURCEHANDLEPROTO,
+  '__module__' : 'tensorboard.compat.proto.resource_handle_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ResourceHandleProto)
+  })
+_sym_db.RegisterMessage(ResourceHandleProto)
+_sym_db.RegisterMessage(ResourceHandleProto.DtypeAndShape)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\016ResourceHandleP\001ZVgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/resource_handle_go_proto\370\001\001'
+  _RESOURCEHANDLEPROTO._serialized_start=147
+  _RESOURCEHANDLEPROTO._serialized_end=443
+  _RESOURCEHANDLEPROTO_DTYPEANDSHAPE._serialized_start=338
+  _RESOURCEHANDLEPROTO_DTYPEANDSHAPE._serialized_end=437
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/rewriter_config_pb2.py

@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/rewriter_config.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()
+
+
+from tensorboard.compat.proto import attr_value_pb2 as tensorboard_dot_compat_dot_proto_dot_attr__value__pb2
+from tensorboard.compat.proto import verifier_config_pb2 as tensorboard_dot_compat_dot_proto_dot_verifier__config__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n.tensorboard/compat/proto/rewriter_config.proto\x12\x0btensorboard\x1a)tensorboard/compat/proto/attr_value.proto\x1a.tensorboard/compat/proto/verifier_config.proto\";\n\x13\x41utoParallelOptions\x12\x0e\n\x06\x65nable\x18\x01 \x01(\x08\x12\x14\n\x0cnum_replicas\x18\x02 \x01(\x05\"+\n\x16ScopedAllocatorOptions\x12\x11\n\tenable_op\x18\x01 \x03(\t\"\xb2\x16\n\x0eRewriterConfig\x12\x44\n\x15\x63pu_layout_conversion\x18\x32 \x01(\x0e\x32%.tensorboard.RewriterConfig.CpuLayout\x12<\n\x10layout_optimizer\x18\x01 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12<\n\x10\x63onstant_folding\x18\x03 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12>\n\x12shape_optimization\x18\r \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x35\n\tremapping\x18\x0e \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12G\n\x1b\x63ommon_subgraph_elimination\x18\x18 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x43\n\x17\x61rithmetic_optimization\x18\x07 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x43\n\x17\x64\x65pendency_optimization\x18\x08 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12=\n\x11loop_optimization\x18\t \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x41\n\x15\x66unction_optimization\x18\n \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12:\n\x0e\x64\x65\x62ug_stripper\x18\x0b \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x1d\n\x15\x64isable_model_pruning\x18\x02 \x01(\x08\x12I\n\x1dscoped_allocator_optimization\x18\x0f \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x44\n\x18pin_to_host_optimization\x18\x12 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x43\n\x17implementation_selector\x18\x16 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12@\n\x14\x61uto_mixed_precision\x18\x17 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x44\n\x18\x61uto_mixed_precision_mkl\x18\x19 \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12P\n$auto_mixed_precision_onednn_bfloat16\x18\x1f \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x44\n\x18\x61uto_mixed_precision_cpu\x18\x1d \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12\x1e\n\x16\x64isable_meta_optimizer\x18\x13 \x01(\x08\x12\x1d\n\x15\x64isable_tfg_optimizer\x18  \x01(\x08\x12\x41\n\x15use_plugin_optimizers\x18\x1c \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12P\n$experimental_conditional_code_motion\x18\x1e \x01(\x0e\x32\".tensorboard.RewriterConfig.Toggle\x12P\n\x19meta_optimizer_iterations\x18\x0c \x01(\x0e\x32-.tensorboard.RewriterConfig.NumIterationsType\x12\x17\n\x0fmin_graph_nodes\x18\x11 \x01(\x05\x12;\n3experimental_disable_compressed_tensor_optimization\x18\x1a \x01(\x08\x12;\n3experimental_disable_folding_quantization_emulation\x18\x1b \x01(\x08\x12\x43\n\x13memory_optimization\x18\x04 \x01(\x0e\x32&.tensorboard.RewriterConfig.MemOptType\x12/\n\'memory_optimizer_target_node_name_scope\x18\x06 \x01(\t\x12!\n\x19meta_optimizer_timeout_ms\x18\x14 \x01(\x03\x12\x37\n\rauto_parallel\x18\x05 \x01(\x0b\x32 .tensorboard.AutoParallelOptions\x12 \n\x18\x66\x61il_on_optimizer_errors\x18\x15 \x01(\x08\x12\x42\n\x15scoped_allocator_opts\x18\x10 \x01(\x0b\x32#.tensorboard.ScopedAllocatorOptions\x12\x12\n\noptimizers\x18\x64 \x03(\t\x12L\n\x11\x63ustom_optimizers\x18\xc8\x01 \x03(\x0b\x32\x30.tensorboard.RewriterConfig.CustomGraphOptimizer\x12\x45\n\x1finter_optimizer_verifier_config\x18\xac\x02 \x01(\x0b\x32\x1b.tensorboard.VerifierConfig\x12G\n!post_optimization_verifier_config\x18\xad\x02 \x01(\x0b\x32\x1b.tensorboard.VerifierConfig\x1a\xcc\x01\n\x14\x43ustomGraphOptimizer\x12\x0c\n\x04name\x18\x01 \x01(\t\x12Y\n\rparameter_map\x18\x02 \x03(\x0b\x32\x42.tensorboard.RewriterConfig.CustomGraphOptimizer.ParameterMapEntry\x1aK\n\x11ParameterMapEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12%\n\x05value\x18\x02 \x01(\x0b\x32\x16.tensorboard.AttrValue:\x02\x38\x01\"d\n\x06Toggle\x12\x0b\n\x07\x44\x45\x46\x41ULT\x10\x00\x12\x06\n\x02ON\x10\x01\x12\x07\n\x03OFF\x10\x02\x12\x0e\n\nAGGRESSIVE\x10\x03\x12\x15\n\x11\x45XPERIMENTAL_MLIR\x10\x04\x12\x15\n\x11\x45XPERIMENTAL_BOTH\x10\x05\"I\n\tCpuLayout\x12\x18\n\x14NO_CONVERSION_ON_CPU\x10\x00\x12\x10\n\x0cNCHW_TO_NHWC\x10\x01\x12\x10\n\x0cNHWC_TO_NCHW\x10\x02\"<\n\x11NumIterationsType\x12\x15\n\x11\x44\x45\x46\x41ULT_NUM_ITERS\x10\x00\x12\x07\n\x03ONE\x10\x01\x12\x07\n\x03TWO\x10\x02\"\x9f\x01\n\nMemOptType\x12\x13\n\x0f\x44\x45\x46\x41ULT_MEM_OPT\x10\x00\x12\x0e\n\nNO_MEM_OPT\x10\x01\x12\n\n\x06MANUAL\x10\x02\x12\x17\n\x13SWAPPING_HEURISTICS\x10\x04\x12\x1c\n\x18RECOMPUTATION_HEURISTICS\x10\x05\x12\x19\n\x15SCHEDULING_HEURISTICS\x10\x06\x12\x0e\n\nHEURISTICS\x10\x03\x42\x8c\x01\n\x18org.tensorflow.frameworkB\x14RewriterConfigProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_AUTOPARALLELOPTIONS = DESCRIPTOR.message_types_by_name['AutoParallelOptions']
+_SCOPEDALLOCATOROPTIONS = DESCRIPTOR.message_types_by_name['ScopedAllocatorOptions']
+_REWRITERCONFIG = DESCRIPTOR.message_types_by_name['RewriterConfig']
+_REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER = _REWRITERCONFIG.nested_types_by_name['CustomGraphOptimizer']
+_REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY = _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER.nested_types_by_name['ParameterMapEntry']
+_REWRITERCONFIG_TOGGLE = _REWRITERCONFIG.enum_types_by_name['Toggle']
+_REWRITERCONFIG_CPULAYOUT = _REWRITERCONFIG.enum_types_by_name['CpuLayout']
+_REWRITERCONFIG_NUMITERATIONSTYPE = _REWRITERCONFIG.enum_types_by_name['NumIterationsType']
+_REWRITERCONFIG_MEMOPTTYPE = _REWRITERCONFIG.enum_types_by_name['MemOptType']
+AutoParallelOptions = _reflection.GeneratedProtocolMessageType('AutoParallelOptions', (_message.Message,), {
+  'DESCRIPTOR' : _AUTOPARALLELOPTIONS,
+  '__module__' : 'tensorboard.compat.proto.rewriter_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AutoParallelOptions)
+  })
+_sym_db.RegisterMessage(AutoParallelOptions)
+
+ScopedAllocatorOptions = _reflection.GeneratedProtocolMessageType('ScopedAllocatorOptions', (_message.Message,), {
+  'DESCRIPTOR' : _SCOPEDALLOCATOROPTIONS,
+  '__module__' : 'tensorboard.compat.proto.rewriter_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ScopedAllocatorOptions)
+  })
+_sym_db.RegisterMessage(ScopedAllocatorOptions)
+
+RewriterConfig = _reflection.GeneratedProtocolMessageType('RewriterConfig', (_message.Message,), {
+
+  'CustomGraphOptimizer' : _reflection.GeneratedProtocolMessageType('CustomGraphOptimizer', (_message.Message,), {
+
+    'ParameterMapEntry' : _reflection.GeneratedProtocolMessageType('ParameterMapEntry', (_message.Message,), {
+      'DESCRIPTOR' : _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY,
+      '__module__' : 'tensorboard.compat.proto.rewriter_config_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.RewriterConfig.CustomGraphOptimizer.ParameterMapEntry)
+      })
+    ,
+    'DESCRIPTOR' : _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER,
+    '__module__' : 'tensorboard.compat.proto.rewriter_config_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.RewriterConfig.CustomGraphOptimizer)
+    })
+  ,
+  'DESCRIPTOR' : _REWRITERCONFIG,
+  '__module__' : 'tensorboard.compat.proto.rewriter_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.RewriterConfig)
+  })
+_sym_db.RegisterMessage(RewriterConfig)
+_sym_db.RegisterMessage(RewriterConfig.CustomGraphOptimizer)
+_sym_db.RegisterMessage(RewriterConfig.CustomGraphOptimizer.ParameterMapEntry)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\024RewriterConfigProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY._options = None
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY._serialized_options = b'8\001'
+  _AUTOPARALLELOPTIONS._serialized_start=154
+  _AUTOPARALLELOPTIONS._serialized_end=213
+  _SCOPEDALLOCATOROPTIONS._serialized_start=215
+  _SCOPEDALLOCATOROPTIONS._serialized_end=258
+  _REWRITERCONFIG._serialized_start=261
+  _REWRITERCONFIG._serialized_end=3127
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER._serialized_start=2522
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER._serialized_end=2726
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY._serialized_start=2651
+  _REWRITERCONFIG_CUSTOMGRAPHOPTIMIZER_PARAMETERMAPENTRY._serialized_end=2726
+  _REWRITERCONFIG_TOGGLE._serialized_start=2728
+  _REWRITERCONFIG_TOGGLE._serialized_end=2828
+  _REWRITERCONFIG_CPULAYOUT._serialized_start=2830
+  _REWRITERCONFIG_CPULAYOUT._serialized_end=2903
+  _REWRITERCONFIG_NUMITERATIONSTYPE._serialized_start=2905
+  _REWRITERCONFIG_NUMITERATIONSTYPE._serialized_end=2965
+  _REWRITERCONFIG_MEMOPTTYPE._serialized_start=2968
+  _REWRITERCONFIG_MEMOPTTYPE._serialized_end=3127
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/rpc_options_pb2.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/rpc_options.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/compat/proto/rpc_options.proto\x12\x0btensorboard\"\xd5\x01\n\nRPCOptions\x12$\n\x1cuse_rpc_for_inprocess_master\x18\x01 \x01(\x08\x12\x1d\n\x15\x63ompression_algorithm\x18\x02 \x01(\t\x12\x19\n\x11\x63ompression_level\x18\x03 \x01(\x05\x12\x1a\n\x12\x63\x61\x63he_rpc_response\x18\x04 \x01(\x08\x12*\n\"disable_session_connection_sharing\x18\x05 \x01(\x08\x12\x1f\n\x17num_channels_per_target\x18\x06 \x01(\x05\x42@Z>github.com/google/tsl/tsl/go/protobuf/for_core_protos_go_protob\x06proto3')
+
+
+
+_RPCOPTIONS = DESCRIPTOR.message_types_by_name['RPCOptions']
+RPCOptions = _reflection.GeneratedProtocolMessageType('RPCOptions', (_message.Message,), {
+  'DESCRIPTOR' : _RPCOPTIONS,
+  '__module__' : 'tensorboard.compat.proto.rpc_options_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.RPCOptions)
+  })
+_sym_db.RegisterMessage(RPCOptions)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'Z>github.com/google/tsl/tsl/go/protobuf/for_core_protos_go_proto'
+  _RPCOPTIONS._serialized_start=60
+  _RPCOPTIONS._serialized_end=273
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/saved_object_graph_pb2.py

@@ -0,0 +1,193 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/saved_object_graph.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()
+
+
+from google.protobuf import any_pb2 as google_dot_protobuf_dot_any__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+from tensorboard.compat.proto import variable_pb2 as tensorboard_dot_compat_dot_proto_dot_variable__pb2
+from tensorboard.compat.proto import versions_pb2 as tensorboard_dot_compat_dot_proto_dot_versions__pb2
+from tensorboard.compat.proto import struct_pb2 as tensorboard_dot_compat_dot_proto_dot_struct__pb2
+from tensorboard.compat.proto import trackable_object_graph_pb2 as tensorboard_dot_compat_dot_proto_dot_trackable__object__graph__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n1tensorboard/compat/proto/saved_object_graph.proto\x12\x0btensorboard\x1a\x19google/protobuf/any.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\x1a\'tensorboard/compat/proto/variable.proto\x1a\'tensorboard/compat/proto/versions.proto\x1a%tensorboard/compat/proto/struct.proto\x1a\x35tensorboard/compat/proto/trackable_object_graph.proto\"\xeb\x01\n\x10SavedObjectGraph\x12\'\n\x05nodes\x18\x01 \x03(\x0b\x32\x18.tensorboard.SavedObject\x12P\n\x12\x63oncrete_functions\x18\x02 \x03(\x0b\x32\x34.tensorboard.SavedObjectGraph.ConcreteFunctionsEntry\x1a\\\n\x16\x43oncreteFunctionsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\x31\n\x05value\x18\x02 \x01(\x0b\x32\".tensorboard.SavedConcreteFunction:\x02\x38\x01\"\xdd\x07\n\x0bSavedObject\x12S\n\x08\x63hildren\x18\x01 \x03(\x0b\x32\x41.tensorboard.TrackableObjectGraph.TrackableObject.ObjectReference\x12W\n\x0c\x64\x65pendencies\x18\x0f \x03(\x0b\x32\x41.tensorboard.TrackableObjectGraph.TrackableObject.ObjectReference\x12_\n\x0eslot_variables\x18\x03 \x03(\x0b\x32G.tensorboard.TrackableObjectGraph.TrackableObject.SlotVariableReference\x12\x33\n\x0buser_object\x18\x04 \x01(\x0b\x32\x1c.tensorboard.SavedUserObjectH\x00\x12(\n\x05\x61sset\x18\x05 \x01(\x0b\x32\x17.tensorboard.SavedAssetH\x00\x12.\n\x08\x66unction\x18\x06 \x01(\x0b\x32\x1a.tensorboard.SavedFunctionH\x00\x12.\n\x08variable\x18\x07 \x01(\x0b\x32\x1a.tensorboard.SavedVariableH\x00\x12H\n\x16\x62\x61re_concrete_function\x18\x08 \x01(\x0b\x32&.tensorboard.SavedBareConcreteFunctionH\x00\x12.\n\x08\x63onstant\x18\t \x01(\x0b\x32\x1a.tensorboard.SavedConstantH\x00\x12.\n\x08resource\x18\n \x01(\x0b\x32\x1a.tensorboard.SavedResourceH\x00\x12\x36\n\x0f\x63\x61ptured_tensor\x18\x0c \x01(\x0b\x32\x1b.tensorboard.CapturedTensorH\x00\x12G\n\x10saveable_objects\x18\x0b \x03(\x0b\x32-.tensorboard.SavedObject.SaveableObjectsEntry\x12\x17\n\x0fregistered_name\x18\r \x01(\t\x12\x33\n\x15serialized_user_proto\x18\x0e \x01(\x0b\x32\x14.google.protobuf.Any\x12\x18\n\x10registered_saver\x18\x10 \x01(\t\x1aS\n\x14SaveableObjectsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12*\n\x05value\x18\x02 \x01(\x0b\x32\x1b.tensorboard.SaveableObject:\x02\x38\x01\x42\x06\n\x04kindJ\x04\x08\x02\x10\x03R\nattributes\"e\n\x0fSavedUserObject\x12\x12\n\nidentifier\x18\x01 \x01(\t\x12(\n\x07version\x18\x02 \x01(\x0b\x32\x17.tensorboard.VersionDef\x12\x14\n\x08metadata\x18\x03 \x01(\tB\x02\x18\x01\"*\n\nSavedAsset\x12\x1c\n\x14\x61sset_file_def_index\x18\x01 \x01(\x05\"]\n\rSavedFunction\x12\x1a\n\x12\x63oncrete_functions\x18\x01 \x03(\t\x12\x30\n\rfunction_spec\x18\x02 \x01(\x0b\x32\x19.tensorboard.FunctionSpec\"9\n\x0e\x43\x61pturedTensor\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x19\n\x11\x63oncrete_function\x18\x02 \x01(\t\"\xaa\x01\n\x15SavedConcreteFunction\x12\x14\n\x0c\x62ound_inputs\x18\x02 \x03(\x05\x12\x43\n\x1d\x63\x61nonicalized_input_signature\x18\x03 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\x12\x36\n\x10output_signature\x18\x04 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\"\xae\x01\n\x19SavedBareConcreteFunction\x12\x1e\n\x16\x63oncrete_function_name\x18\x01 \x01(\t\x12\x19\n\x11\x61rgument_keywords\x18\x02 \x03(\t\x12$\n\x1c\x61llowed_positional_arguments\x18\x03 \x01(\x03\x12\x30\n\rfunction_spec\x18\x04 \x01(\x0b\x32\x19.tensorboard.FunctionSpec\"\"\n\rSavedConstant\x12\x11\n\toperation\x18\x01 \x01(\t\"\xdc\x02\n\rSavedVariable\x12$\n\x05\x64type\x18\x01 \x01(\x0e\x32\x15.tensorboard.DataType\x12,\n\x05shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12\x11\n\ttrainable\x18\x03 \x01(\x08\x12=\n\x0fsynchronization\x18\x04 \x01(\x0e\x32$.tensorboard.VariableSynchronization\x12\x35\n\x0b\x61ggregation\x18\x05 \x01(\x0e\x32 .tensorboard.VariableAggregation\x12\x0c\n\x04name\x18\x06 \x01(\t\x12\x0e\n\x06\x64\x65vice\x18\x07 \x01(\t\x12P\n,experimental_distributed_variable_components\x18\x08 \x03(\x0b\x32\x1a.tensorboard.SavedVariable\"\xfe\x01\n\x0c\x46unctionSpec\x12\x31\n\x0b\x66ullargspec\x18\x01 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\x12\x11\n\tis_method\x18\x02 \x01(\x08\x12\x35\n\x0finput_signature\x18\x05 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\x12\x39\n\x0bjit_compile\x18\x06 \x01(\x0e\x32$.tensorboard.FunctionSpec.JitCompile\"*\n\nJitCompile\x12\x0b\n\x07\x44\x45\x46\x41ULT\x10\x00\x12\x06\n\x02ON\x10\x01\x12\x07\n\x03OFF\x10\x02J\x04\x08\x03\x10\x04J\x04\x08\x04\x10\x05\"\x1f\n\rSavedResource\x12\x0e\n\x06\x64\x65vice\x18\x01 \x01(\t\"A\n\x0eSaveableObject\x12\x15\n\rsave_function\x18\x02 \x01(\x05\x12\x18\n\x10restore_function\x18\x03 \x01(\x05\x42ZZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_SAVEDOBJECTGRAPH = DESCRIPTOR.message_types_by_name['SavedObjectGraph']
+_SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY = _SAVEDOBJECTGRAPH.nested_types_by_name['ConcreteFunctionsEntry']
+_SAVEDOBJECT = DESCRIPTOR.message_types_by_name['SavedObject']
+_SAVEDOBJECT_SAVEABLEOBJECTSENTRY = _SAVEDOBJECT.nested_types_by_name['SaveableObjectsEntry']
+_SAVEDUSEROBJECT = DESCRIPTOR.message_types_by_name['SavedUserObject']
+_SAVEDASSET = DESCRIPTOR.message_types_by_name['SavedAsset']
+_SAVEDFUNCTION = DESCRIPTOR.message_types_by_name['SavedFunction']
+_CAPTUREDTENSOR = DESCRIPTOR.message_types_by_name['CapturedTensor']
+_SAVEDCONCRETEFUNCTION = DESCRIPTOR.message_types_by_name['SavedConcreteFunction']
+_SAVEDBARECONCRETEFUNCTION = DESCRIPTOR.message_types_by_name['SavedBareConcreteFunction']
+_SAVEDCONSTANT = DESCRIPTOR.message_types_by_name['SavedConstant']
+_SAVEDVARIABLE = DESCRIPTOR.message_types_by_name['SavedVariable']
+_FUNCTIONSPEC = DESCRIPTOR.message_types_by_name['FunctionSpec']
+_SAVEDRESOURCE = DESCRIPTOR.message_types_by_name['SavedResource']
+_SAVEABLEOBJECT = DESCRIPTOR.message_types_by_name['SaveableObject']
+_FUNCTIONSPEC_JITCOMPILE = _FUNCTIONSPEC.enum_types_by_name['JitCompile']
+SavedObjectGraph = _reflection.GeneratedProtocolMessageType('SavedObjectGraph', (_message.Message,), {
+
+  'ConcreteFunctionsEntry' : _reflection.GeneratedProtocolMessageType('ConcreteFunctionsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY,
+    '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SavedObjectGraph.ConcreteFunctionsEntry)
+    })
+  ,
+  'DESCRIPTOR' : _SAVEDOBJECTGRAPH,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedObjectGraph)
+  })
+_sym_db.RegisterMessage(SavedObjectGraph)
+_sym_db.RegisterMessage(SavedObjectGraph.ConcreteFunctionsEntry)
+
+SavedObject = _reflection.GeneratedProtocolMessageType('SavedObject', (_message.Message,), {
+
+  'SaveableObjectsEntry' : _reflection.GeneratedProtocolMessageType('SaveableObjectsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _SAVEDOBJECT_SAVEABLEOBJECTSENTRY,
+    '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SavedObject.SaveableObjectsEntry)
+    })
+  ,
+  'DESCRIPTOR' : _SAVEDOBJECT,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedObject)
+  })
+_sym_db.RegisterMessage(SavedObject)
+_sym_db.RegisterMessage(SavedObject.SaveableObjectsEntry)
+
+SavedUserObject = _reflection.GeneratedProtocolMessageType('SavedUserObject', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDUSEROBJECT,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedUserObject)
+  })
+_sym_db.RegisterMessage(SavedUserObject)
+
+SavedAsset = _reflection.GeneratedProtocolMessageType('SavedAsset', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDASSET,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedAsset)
+  })
+_sym_db.RegisterMessage(SavedAsset)
+
+SavedFunction = _reflection.GeneratedProtocolMessageType('SavedFunction', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDFUNCTION,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedFunction)
+  })
+_sym_db.RegisterMessage(SavedFunction)
+
+CapturedTensor = _reflection.GeneratedProtocolMessageType('CapturedTensor', (_message.Message,), {
+  'DESCRIPTOR' : _CAPTUREDTENSOR,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.CapturedTensor)
+  })
+_sym_db.RegisterMessage(CapturedTensor)
+
+SavedConcreteFunction = _reflection.GeneratedProtocolMessageType('SavedConcreteFunction', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDCONCRETEFUNCTION,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedConcreteFunction)
+  })
+_sym_db.RegisterMessage(SavedConcreteFunction)
+
+SavedBareConcreteFunction = _reflection.GeneratedProtocolMessageType('SavedBareConcreteFunction', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDBARECONCRETEFUNCTION,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedBareConcreteFunction)
+  })
+_sym_db.RegisterMessage(SavedBareConcreteFunction)
+
+SavedConstant = _reflection.GeneratedProtocolMessageType('SavedConstant', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDCONSTANT,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedConstant)
+  })
+_sym_db.RegisterMessage(SavedConstant)
+
+SavedVariable = _reflection.GeneratedProtocolMessageType('SavedVariable', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDVARIABLE,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedVariable)
+  })
+_sym_db.RegisterMessage(SavedVariable)
+
+FunctionSpec = _reflection.GeneratedProtocolMessageType('FunctionSpec', (_message.Message,), {
+  'DESCRIPTOR' : _FUNCTIONSPEC,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.FunctionSpec)
+  })
+_sym_db.RegisterMessage(FunctionSpec)
+
+SavedResource = _reflection.GeneratedProtocolMessageType('SavedResource', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEDRESOURCE,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SavedResource)
+  })
+_sym_db.RegisterMessage(SavedResource)
+
+SaveableObject = _reflection.GeneratedProtocolMessageType('SaveableObject', (_message.Message,), {
+  'DESCRIPTOR' : _SAVEABLEOBJECT,
+  '__module__' : 'tensorboard.compat.proto.saved_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SaveableObject)
+  })
+_sym_db.RegisterMessage(SaveableObject)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY._options = None
+  _SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY._serialized_options = b'8\001'
+  _SAVEDOBJECT_SAVEABLEOBJECTSENTRY._options = None
+  _SAVEDOBJECT_SAVEABLEOBJECTSENTRY._serialized_options = b'8\001'
+  _SAVEDUSEROBJECT.fields_by_name['metadata']._options = None
+  _SAVEDUSEROBJECT.fields_by_name['metadata']._serialized_options = b'\030\001'
+  _SAVEDOBJECTGRAPH._serialized_start=353
+  _SAVEDOBJECTGRAPH._serialized_end=588
+  _SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY._serialized_start=496
+  _SAVEDOBJECTGRAPH_CONCRETEFUNCTIONSENTRY._serialized_end=588
+  _SAVEDOBJECT._serialized_start=591
+  _SAVEDOBJECT._serialized_end=1580
+  _SAVEDOBJECT_SAVEABLEOBJECTSENTRY._serialized_start=1471
+  _SAVEDOBJECT_SAVEABLEOBJECTSENTRY._serialized_end=1554
+  _SAVEDUSEROBJECT._serialized_start=1582
+  _SAVEDUSEROBJECT._serialized_end=1683
+  _SAVEDASSET._serialized_start=1685
+  _SAVEDASSET._serialized_end=1727
+  _SAVEDFUNCTION._serialized_start=1729
+  _SAVEDFUNCTION._serialized_end=1822
+  _CAPTUREDTENSOR._serialized_start=1824
+  _CAPTUREDTENSOR._serialized_end=1881
+  _SAVEDCONCRETEFUNCTION._serialized_start=1884
+  _SAVEDCONCRETEFUNCTION._serialized_end=2054
+  _SAVEDBARECONCRETEFUNCTION._serialized_start=2057
+  _SAVEDBARECONCRETEFUNCTION._serialized_end=2231
+  _SAVEDCONSTANT._serialized_start=2233
+  _SAVEDCONSTANT._serialized_end=2267
+  _SAVEDVARIABLE._serialized_start=2270
+  _SAVEDVARIABLE._serialized_end=2618
+  _FUNCTIONSPEC._serialized_start=2621
+  _FUNCTIONSPEC._serialized_end=2875
+  _FUNCTIONSPEC_JITCOMPILE._serialized_start=2821
+  _FUNCTIONSPEC_JITCOMPILE._serialized_end=2863
+  _SAVEDRESOURCE._serialized_start=2877
+  _SAVEDRESOURCE._serialized_end=2908
+  _SAVEABLEOBJECT._serialized_start=2910
+  _SAVEABLEOBJECT._serialized_end=2975
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/saver_pb2.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/saver.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/compat/proto/saver.proto\x12\x0btensorboard\"\x9f\x02\n\x08SaverDef\x12\x1c\n\x14\x66ilename_tensor_name\x18\x01 \x01(\t\x12\x18\n\x10save_tensor_name\x18\x02 \x01(\t\x12\x17\n\x0frestore_op_name\x18\x03 \x01(\t\x12\x13\n\x0bmax_to_keep\x18\x04 \x01(\x05\x12\x0f\n\x07sharded\x18\x05 \x01(\x08\x12%\n\x1dkeep_checkpoint_every_n_hours\x18\x06 \x01(\x02\x12>\n\x07version\x18\x07 \x01(\x0e\x32-.tensorboard.SaverDef.CheckpointFormatVersion\"5\n\x17\x43heckpointFormatVersion\x12\n\n\x06LEGACY\x10\x00\x12\x06\n\x02V1\x10\x01\x12\x06\n\x02V2\x10\x02\x42~\n\x13org.tensorflow.utilB\x0bSaverProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_SAVERDEF = DESCRIPTOR.message_types_by_name['SaverDef']
+_SAVERDEF_CHECKPOINTFORMATVERSION = _SAVERDEF.enum_types_by_name['CheckpointFormatVersion']
+SaverDef = _reflection.GeneratedProtocolMessageType('SaverDef', (_message.Message,), {
+  'DESCRIPTOR' : _SAVERDEF,
+  '__module__' : 'tensorboard.compat.proto.saver_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SaverDef)
+  })
+_sym_db.RegisterMessage(SaverDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\023org.tensorflow.utilB\013SaverProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _SAVERDEF._serialized_start=54
+  _SAVERDEF._serialized_end=341
+  _SAVERDEF_CHECKPOINTFORMATVERSION._serialized_start=288
+  _SAVERDEF_CHECKPOINTFORMATVERSION._serialized_end=341
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/step_stats_pb2.py

@@ -0,0 +1,116 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/step_stats.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()
+
+
+from tensorboard.compat.proto import allocation_description_pb2 as tensorboard_dot_compat_dot_proto_dot_allocation__description__pb2
+from tensorboard.compat.proto import tensor_description_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__description__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n)tensorboard/compat/proto/step_stats.proto\x12\x0btensorboard\x1a\x35tensorboard/compat/proto/allocation_description.proto\x1a\x31tensorboard/compat/proto/tensor_description.proto\"=\n\x10\x41llocationRecord\x12\x14\n\x0c\x61lloc_micros\x18\x01 \x01(\x03\x12\x13\n\x0b\x61lloc_bytes\x18\x02 \x01(\x03\"\xc5\x01\n\x13\x41llocatorMemoryUsed\x12\x16\n\x0e\x61llocator_name\x18\x01 \x01(\t\x12\x13\n\x0btotal_bytes\x18\x02 \x01(\x03\x12\x12\n\npeak_bytes\x18\x03 \x01(\x03\x12\x12\n\nlive_bytes\x18\x04 \x01(\x03\x12\x39\n\x12\x61llocation_records\x18\x06 \x03(\x0b\x32\x1d.tensorboard.AllocationRecord\x12\x1e\n\x16\x61llocator_bytes_in_use\x18\x05 \x01(\x03\"V\n\nNodeOutput\x12\x0c\n\x04slot\x18\x01 \x01(\x05\x12:\n\x12tensor_description\x18\x03 \x01(\x0b\x32\x1e.tensorboard.TensorDescription\"\xec\x01\n\x0bMemoryStats\x12\x18\n\x10temp_memory_size\x18\x01 \x01(\x03\x12\x1e\n\x16persistent_memory_size\x18\x03 \x01(\x03\x12#\n\x1bpersistent_tensor_alloc_ids\x18\x05 \x03(\x03\x12#\n\x17\x64\x65vice_temp_memory_size\x18\x02 \x01(\x03\x42\x02\x18\x01\x12)\n\x1d\x64\x65vice_persistent_memory_size\x18\x04 \x01(\x03\x42\x02\x18\x01\x12.\n\"device_persistent_tensor_alloc_ids\x18\x06 \x03(\x03\x42\x02\x18\x01\"\xa2\x04\n\rNodeExecStats\x12\x11\n\tnode_name\x18\x01 \x01(\t\x12\x18\n\x10\x61ll_start_micros\x18\x02 \x01(\x03\x12\x1b\n\x13op_start_rel_micros\x18\x03 \x01(\x03\x12\x19\n\x11op_end_rel_micros\x18\x04 \x01(\x03\x12\x1a\n\x12\x61ll_end_rel_micros\x18\x05 \x01(\x03\x12\x30\n\x06memory\x18\x06 \x03(\x0b\x32 .tensorboard.AllocatorMemoryUsed\x12\'\n\x06output\x18\x07 \x03(\x0b\x32\x17.tensorboard.NodeOutput\x12\x16\n\x0etimeline_label\x18\x08 \x01(\t\x12\x18\n\x10scheduled_micros\x18\t \x01(\x03\x12\x11\n\tthread_id\x18\n \x01(\r\x12=\n\x11referenced_tensor\x18\x0b \x03(\x0b\x32\".tensorboard.AllocationDescription\x12.\n\x0cmemory_stats\x18\x0c \x01(\x0b\x32\x18.tensorboard.MemoryStats\x12\x17\n\x0f\x61ll_start_nanos\x18\r \x01(\x03\x12\x1a\n\x12op_start_rel_nanos\x18\x0e \x01(\x03\x12\x18\n\x10op_end_rel_nanos\x18\x0f \x01(\x03\x12\x19\n\x11\x61ll_end_rel_nanos\x18\x10 \x01(\x03\x12\x17\n\x0fscheduled_nanos\x18\x11 \x01(\x03\"\xca\x01\n\x0f\x44\x65viceStepStats\x12\x0e\n\x06\x64\x65vice\x18\x01 \x01(\t\x12.\n\nnode_stats\x18\x02 \x03(\x0b\x32\x1a.tensorboard.NodeExecStats\x12\x43\n\x0cthread_names\x18\x03 \x03(\x0b\x32-.tensorboard.DeviceStepStats.ThreadNamesEntry\x1a\x32\n\x10ThreadNamesEntry\x12\x0b\n\x03key\x18\x01 \x01(\r\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"<\n\tStepStats\x12/\n\tdev_stats\x18\x01 \x03(\x0b\x32\x1c.tensorboard.DeviceStepStatsB\x83\x01\n\x18org.tensorflow.frameworkB\x0fStepStatsProtosP\x01ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/step_stats_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_ALLOCATIONRECORD = DESCRIPTOR.message_types_by_name['AllocationRecord']
+_ALLOCATORMEMORYUSED = DESCRIPTOR.message_types_by_name['AllocatorMemoryUsed']
+_NODEOUTPUT = DESCRIPTOR.message_types_by_name['NodeOutput']
+_MEMORYSTATS = DESCRIPTOR.message_types_by_name['MemoryStats']
+_NODEEXECSTATS = DESCRIPTOR.message_types_by_name['NodeExecStats']
+_DEVICESTEPSTATS = DESCRIPTOR.message_types_by_name['DeviceStepStats']
+_DEVICESTEPSTATS_THREADNAMESENTRY = _DEVICESTEPSTATS.nested_types_by_name['ThreadNamesEntry']
+_STEPSTATS = DESCRIPTOR.message_types_by_name['StepStats']
+AllocationRecord = _reflection.GeneratedProtocolMessageType('AllocationRecord', (_message.Message,), {
+  'DESCRIPTOR' : _ALLOCATIONRECORD,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AllocationRecord)
+  })
+_sym_db.RegisterMessage(AllocationRecord)
+
+AllocatorMemoryUsed = _reflection.GeneratedProtocolMessageType('AllocatorMemoryUsed', (_message.Message,), {
+  'DESCRIPTOR' : _ALLOCATORMEMORYUSED,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.AllocatorMemoryUsed)
+  })
+_sym_db.RegisterMessage(AllocatorMemoryUsed)
+
+NodeOutput = _reflection.GeneratedProtocolMessageType('NodeOutput', (_message.Message,), {
+  'DESCRIPTOR' : _NODEOUTPUT,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NodeOutput)
+  })
+_sym_db.RegisterMessage(NodeOutput)
+
+MemoryStats = _reflection.GeneratedProtocolMessageType('MemoryStats', (_message.Message,), {
+  'DESCRIPTOR' : _MEMORYSTATS,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.MemoryStats)
+  })
+_sym_db.RegisterMessage(MemoryStats)
+
+NodeExecStats = _reflection.GeneratedProtocolMessageType('NodeExecStats', (_message.Message,), {
+  'DESCRIPTOR' : _NODEEXECSTATS,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NodeExecStats)
+  })
+_sym_db.RegisterMessage(NodeExecStats)
+
+DeviceStepStats = _reflection.GeneratedProtocolMessageType('DeviceStepStats', (_message.Message,), {
+
+  'ThreadNamesEntry' : _reflection.GeneratedProtocolMessageType('ThreadNamesEntry', (_message.Message,), {
+    'DESCRIPTOR' : _DEVICESTEPSTATS_THREADNAMESENTRY,
+    '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.DeviceStepStats.ThreadNamesEntry)
+    })
+  ,
+  'DESCRIPTOR' : _DEVICESTEPSTATS,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DeviceStepStats)
+  })
+_sym_db.RegisterMessage(DeviceStepStats)
+_sym_db.RegisterMessage(DeviceStepStats.ThreadNamesEntry)
+
+StepStats = _reflection.GeneratedProtocolMessageType('StepStats', (_message.Message,), {
+  'DESCRIPTOR' : _STEPSTATS,
+  '__module__' : 'tensorboard.compat.proto.step_stats_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.StepStats)
+  })
+_sym_db.RegisterMessage(StepStats)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\017StepStatsProtosP\001ZQgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/step_stats_go_proto\370\001\001'
+  _MEMORYSTATS.fields_by_name['device_temp_memory_size']._options = None
+  _MEMORYSTATS.fields_by_name['device_temp_memory_size']._serialized_options = b'\030\001'
+  _MEMORYSTATS.fields_by_name['device_persistent_memory_size']._options = None
+  _MEMORYSTATS.fields_by_name['device_persistent_memory_size']._serialized_options = b'\030\001'
+  _MEMORYSTATS.fields_by_name['device_persistent_tensor_alloc_ids']._options = None
+  _MEMORYSTATS.fields_by_name['device_persistent_tensor_alloc_ids']._serialized_options = b'\030\001'
+  _DEVICESTEPSTATS_THREADNAMESENTRY._options = None
+  _DEVICESTEPSTATS_THREADNAMESENTRY._serialized_options = b'8\001'
+  _ALLOCATIONRECORD._serialized_start=164
+  _ALLOCATIONRECORD._serialized_end=225
+  _ALLOCATORMEMORYUSED._serialized_start=228
+  _ALLOCATORMEMORYUSED._serialized_end=425
+  _NODEOUTPUT._serialized_start=427
+  _NODEOUTPUT._serialized_end=513
+  _MEMORYSTATS._serialized_start=516
+  _MEMORYSTATS._serialized_end=752
+  _NODEEXECSTATS._serialized_start=755
+  _NODEEXECSTATS._serialized_end=1301
+  _DEVICESTEPSTATS._serialized_start=1304
+  _DEVICESTEPSTATS._serialized_end=1506
+  _DEVICESTEPSTATS_THREADNAMESENTRY._serialized_start=1456
+  _DEVICESTEPSTATS_THREADNAMESENTRY._serialized_end=1506
+  _STEPSTATS._serialized_start=1508
+  _STEPSTATS._serialized_end=1568
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/struct_pb2.py

@@ -0,0 +1,144 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/struct.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()
+
+
+from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n%tensorboard/compat/proto/struct.proto\x12\x0btensorboard\x1a%tensorboard/compat/proto/tensor.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xfd\x05\n\x0fStructuredValue\x12,\n\nnone_value\x18\x01 \x01(\x0b\x32\x16.tensorboard.NoneValueH\x00\x12\x17\n\rfloat64_value\x18\x0b \x01(\x01H\x00\x12\x15\n\x0bint64_value\x18\x0c \x01(\x12H\x00\x12\x16\n\x0cstring_value\x18\r \x01(\tH\x00\x12\x14\n\nbool_value\x18\x0e \x01(\x08H\x00\x12;\n\x12tensor_shape_value\x18\x1f \x01(\x0b\x32\x1d.tensorboard.TensorShapeProtoH\x00\x12\x33\n\x12tensor_dtype_value\x18  \x01(\x0e\x32\x15.tensorboard.DataTypeH\x00\x12\x39\n\x11tensor_spec_value\x18! \x01(\x0b\x32\x1c.tensorboard.TensorSpecProtoH\x00\x12\x35\n\x0ftype_spec_value\x18\" \x01(\x0b\x32\x1a.tensorboard.TypeSpecProtoH\x00\x12H\n\x19\x62ounded_tensor_spec_value\x18# \x01(\x0b\x32#.tensorboard.BoundedTensorSpecProtoH\x00\x12,\n\nlist_value\x18\x33 \x01(\x0b\x32\x16.tensorboard.ListValueH\x00\x12.\n\x0btuple_value\x18\x34 \x01(\x0b\x32\x17.tensorboard.TupleValueH\x00\x12,\n\ndict_value\x18\x35 \x01(\x0b\x32\x16.tensorboard.DictValueH\x00\x12\x39\n\x11named_tuple_value\x18\x36 \x01(\x0b\x32\x1c.tensorboard.NamedTupleValueH\x00\x12\x30\n\x0ctensor_value\x18\x37 \x01(\x0b\x32\x18.tensorboard.TensorProtoH\x00\x12/\n\x0bnumpy_value\x18\x38 \x01(\x0b\x32\x18.tensorboard.TensorProtoH\x00\x42\x06\n\x04kind\"\x0b\n\tNoneValue\"9\n\tListValue\x12,\n\x06values\x18\x01 \x03(\x0b\x32\x1c.tensorboard.StructuredValue\":\n\nTupleValue\x12,\n\x06values\x18\x01 \x03(\x0b\x32\x1c.tensorboard.StructuredValue\"\x8c\x01\n\tDictValue\x12\x32\n\x06\x66ields\x18\x01 \x03(\x0b\x32\".tensorboard.DictValue.FieldsEntry\x1aK\n\x0b\x46ieldsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12+\n\x05value\x18\x02 \x01(\x0b\x32\x1c.tensorboard.StructuredValue:\x02\x38\x01\"E\n\tPairValue\x12\x0b\n\x03key\x18\x01 \x01(\t\x12+\n\x05value\x18\x02 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\"G\n\x0fNamedTupleValue\x12\x0c\n\x04name\x18\x01 \x01(\t\x12&\n\x06values\x18\x02 \x03(\x0b\x32\x16.tensorboard.PairValue\"s\n\x0fTensorSpecProto\x12\x0c\n\x04name\x18\x01 \x01(\t\x12,\n\x05shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12$\n\x05\x64type\x18\x03 \x01(\x0e\x32\x15.tensorboard.DataType\"\xd0\x01\n\x16\x42oundedTensorSpecProto\x12\x0c\n\x04name\x18\x01 \x01(\t\x12,\n\x05shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12$\n\x05\x64type\x18\x03 \x01(\x0e\x32\x15.tensorboard.DataType\x12)\n\x07minimum\x18\x04 \x01(\x0b\x32\x18.tensorboard.TensorProto\x12)\n\x07maximum\x18\x05 \x01(\x0b\x32\x18.tensorboard.TensorProto\"\xfa\x03\n\rTypeSpecProto\x12\x41\n\x0ftype_spec_class\x18\x01 \x01(\x0e\x32(.tensorboard.TypeSpecProto.TypeSpecClass\x12\x30\n\ntype_state\x18\x02 \x01(\x0b\x32\x1c.tensorboard.StructuredValue\x12\x1c\n\x14type_spec_class_name\x18\x03 \x01(\t\x12\x1b\n\x13num_flat_components\x18\x04 \x01(\x05\"\xb8\x02\n\rTypeSpecClass\x12\x0b\n\x07UNKNOWN\x10\x00\x12\x16\n\x12SPARSE_TENSOR_SPEC\x10\x01\x12\x17\n\x13INDEXED_SLICES_SPEC\x10\x02\x12\x16\n\x12RAGGED_TENSOR_SPEC\x10\x03\x12\x15\n\x11TENSOR_ARRAY_SPEC\x10\x04\x12\x15\n\x11\x44\x41TA_DATASET_SPEC\x10\x05\x12\x16\n\x12\x44\x41TA_ITERATOR_SPEC\x10\x06\x12\x11\n\rOPTIONAL_SPEC\x10\x07\x12\x14\n\x10PER_REPLICA_SPEC\x10\x08\x12\x11\n\rVARIABLE_SPEC\x10\t\x12\x16\n\x12ROW_PARTITION_SPEC\x10\n\x12\x18\n\x14REGISTERED_TYPE_SPEC\x10\x0c\x12\x17\n\x13\x45XTENSION_TYPE_SPEC\x10\r\"\x04\x08\x0b\x10\x0b\x42WZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_protob\x06proto3')
+
+
+
+_STRUCTUREDVALUE = DESCRIPTOR.message_types_by_name['StructuredValue']
+_NONEVALUE = DESCRIPTOR.message_types_by_name['NoneValue']
+_LISTVALUE = DESCRIPTOR.message_types_by_name['ListValue']
+_TUPLEVALUE = DESCRIPTOR.message_types_by_name['TupleValue']
+_DICTVALUE = DESCRIPTOR.message_types_by_name['DictValue']
+_DICTVALUE_FIELDSENTRY = _DICTVALUE.nested_types_by_name['FieldsEntry']
+_PAIRVALUE = DESCRIPTOR.message_types_by_name['PairValue']
+_NAMEDTUPLEVALUE = DESCRIPTOR.message_types_by_name['NamedTupleValue']
+_TENSORSPECPROTO = DESCRIPTOR.message_types_by_name['TensorSpecProto']
+_BOUNDEDTENSORSPECPROTO = DESCRIPTOR.message_types_by_name['BoundedTensorSpecProto']
+_TYPESPECPROTO = DESCRIPTOR.message_types_by_name['TypeSpecProto']
+_TYPESPECPROTO_TYPESPECCLASS = _TYPESPECPROTO.enum_types_by_name['TypeSpecClass']
+StructuredValue = _reflection.GeneratedProtocolMessageType('StructuredValue', (_message.Message,), {
+  'DESCRIPTOR' : _STRUCTUREDVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.StructuredValue)
+  })
+_sym_db.RegisterMessage(StructuredValue)
+
+NoneValue = _reflection.GeneratedProtocolMessageType('NoneValue', (_message.Message,), {
+  'DESCRIPTOR' : _NONEVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NoneValue)
+  })
+_sym_db.RegisterMessage(NoneValue)
+
+ListValue = _reflection.GeneratedProtocolMessageType('ListValue', (_message.Message,), {
+  'DESCRIPTOR' : _LISTVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.ListValue)
+  })
+_sym_db.RegisterMessage(ListValue)
+
+TupleValue = _reflection.GeneratedProtocolMessageType('TupleValue', (_message.Message,), {
+  'DESCRIPTOR' : _TUPLEVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TupleValue)
+  })
+_sym_db.RegisterMessage(TupleValue)
+
+DictValue = _reflection.GeneratedProtocolMessageType('DictValue', (_message.Message,), {
+
+  'FieldsEntry' : _reflection.GeneratedProtocolMessageType('FieldsEntry', (_message.Message,), {
+    'DESCRIPTOR' : _DICTVALUE_FIELDSENTRY,
+    '__module__' : 'tensorboard.compat.proto.struct_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.DictValue.FieldsEntry)
+    })
+  ,
+  'DESCRIPTOR' : _DICTVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.DictValue)
+  })
+_sym_db.RegisterMessage(DictValue)
+_sym_db.RegisterMessage(DictValue.FieldsEntry)
+
+PairValue = _reflection.GeneratedProtocolMessageType('PairValue', (_message.Message,), {
+  'DESCRIPTOR' : _PAIRVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.PairValue)
+  })
+_sym_db.RegisterMessage(PairValue)
+
+NamedTupleValue = _reflection.GeneratedProtocolMessageType('NamedTupleValue', (_message.Message,), {
+  'DESCRIPTOR' : _NAMEDTUPLEVALUE,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.NamedTupleValue)
+  })
+_sym_db.RegisterMessage(NamedTupleValue)
+
+TensorSpecProto = _reflection.GeneratedProtocolMessageType('TensorSpecProto', (_message.Message,), {
+  'DESCRIPTOR' : _TENSORSPECPROTO,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TensorSpecProto)
+  })
+_sym_db.RegisterMessage(TensorSpecProto)
+
+BoundedTensorSpecProto = _reflection.GeneratedProtocolMessageType('BoundedTensorSpecProto', (_message.Message,), {
+  'DESCRIPTOR' : _BOUNDEDTENSORSPECPROTO,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.BoundedTensorSpecProto)
+  })
+_sym_db.RegisterMessage(BoundedTensorSpecProto)
+
+TypeSpecProto = _reflection.GeneratedProtocolMessageType('TypeSpecProto', (_message.Message,), {
+  'DESCRIPTOR' : _TYPESPECPROTO,
+  '__module__' : 'tensorboard.compat.proto.struct_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TypeSpecProto)
+  })
+_sym_db.RegisterMessage(TypeSpecProto)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto'
+  _DICTVALUE_FIELDSENTRY._options = None
+  _DICTVALUE_FIELDSENTRY._serialized_options = b'8\001'
+  _STRUCTUREDVALUE._serialized_start=177
+  _STRUCTUREDVALUE._serialized_end=942
+  _NONEVALUE._serialized_start=944
+  _NONEVALUE._serialized_end=955
+  _LISTVALUE._serialized_start=957
+  _LISTVALUE._serialized_end=1014
+  _TUPLEVALUE._serialized_start=1016
+  _TUPLEVALUE._serialized_end=1074
+  _DICTVALUE._serialized_start=1077
+  _DICTVALUE._serialized_end=1217
+  _DICTVALUE_FIELDSENTRY._serialized_start=1142
+  _DICTVALUE_FIELDSENTRY._serialized_end=1217
+  _PAIRVALUE._serialized_start=1219
+  _PAIRVALUE._serialized_end=1288
+  _NAMEDTUPLEVALUE._serialized_start=1290
+  _NAMEDTUPLEVALUE._serialized_end=1361
+  _TENSORSPECPROTO._serialized_start=1363
+  _TENSORSPECPROTO._serialized_end=1478
+  _BOUNDEDTENSORSPECPROTO._serialized_start=1481
+  _BOUNDEDTENSORSPECPROTO._serialized_end=1689
+  _TYPESPECPROTO._serialized_start=1692
+  _TYPESPECPROTO._serialized_end=2198
+  _TYPESPECPROTO_TYPESPECCLASS._serialized_start=1886
+  _TYPESPECPROTO_TYPESPECCLASS._serialized_end=2198
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/summary_pb2.py

@@ -0,0 +1,111 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/summary.proto
+"""Generated protocol buffer code."""
+from google.protobuf.internal import enum_type_wrapper
+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()
+
+
+from tensorboard.compat.proto import histogram_pb2 as tensorboard_dot_compat_dot_proto_dot_histogram__pb2
+from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2
+
+from tensorboard.compat.proto.histogram_pb2 import *
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n&tensorboard/compat/proto/summary.proto\x12\x0btensorboard\x1a(tensorboard/compat/proto/histogram.proto\x1a%tensorboard/compat/proto/tensor.proto\"\'\n\x12SummaryDescription\x12\x11\n\ttype_hint\x18\x01 \x01(\t\"\xe2\x01\n\x0fSummaryMetadata\x12<\n\x0bplugin_data\x18\x01 \x01(\x0b\x32\'.tensorboard.SummaryMetadata.PluginData\x12\x14\n\x0c\x64isplay_name\x18\x02 \x01(\t\x12\x1b\n\x13summary_description\x18\x03 \x01(\t\x12*\n\ndata_class\x18\x04 \x01(\x0e\x32\x16.tensorboard.DataClass\x1a\x32\n\nPluginData\x12\x13\n\x0bplugin_name\x18\x01 \x01(\t\x12\x0f\n\x07\x63ontent\x18\x02 \x01(\x0c\"\xe4\x04\n\x07Summary\x12)\n\x05value\x18\x01 \x03(\x0b\x32\x1a.tensorboard.Summary.Value\x1aX\n\x05Image\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x12\n\ncolorspace\x18\x03 \x01(\x05\x12\x1c\n\x14\x65ncoded_image_string\x18\x04 \x01(\x0c\x1a}\n\x05\x41udio\x12\x13\n\x0bsample_rate\x18\x01 \x01(\x02\x12\x14\n\x0cnum_channels\x18\x02 \x01(\x03\x12\x15\n\rlength_frames\x18\x03 \x01(\x03\x12\x1c\n\x14\x65ncoded_audio_string\x18\x04 \x01(\x0c\x12\x14\n\x0c\x63ontent_type\x18\x05 \x01(\t\x1a\xd4\x02\n\x05Value\x12\x11\n\tnode_name\x18\x07 \x01(\t\x12\x0b\n\x03tag\x18\x01 \x01(\t\x12.\n\x08metadata\x18\t \x01(\x0b\x32\x1c.tensorboard.SummaryMetadata\x12\x16\n\x0csimple_value\x18\x02 \x01(\x02H\x00\x12&\n\x1cobsolete_old_style_histogram\x18\x03 \x01(\x0cH\x00\x12+\n\x05image\x18\x04 \x01(\x0b\x32\x1a.tensorboard.Summary.ImageH\x00\x12,\n\x05histo\x18\x05 \x01(\x0b\x32\x1b.tensorboard.HistogramProtoH\x00\x12+\n\x05\x61udio\x18\x06 \x01(\x0b\x32\x1a.tensorboard.Summary.AudioH\x00\x12*\n\x06tensor\x18\x08 \x01(\x0b\x32\x18.tensorboard.TensorProtoH\x00\x42\x07\n\x05value*o\n\tDataClass\x12\x16\n\x12\x44\x41TA_CLASS_UNKNOWN\x10\x00\x12\x15\n\x11\x44\x41TA_CLASS_SCALAR\x10\x01\x12\x15\n\x11\x44\x41TA_CLASS_TENSOR\x10\x02\x12\x1c\n\x18\x44\x41TA_CLASS_BLOB_SEQUENCE\x10\x03\x42~\n\x18org.tensorflow.frameworkB\rSummaryProtosP\x01ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/summary_go_proto\xf8\x01\x01P\x00\x62\x06proto3')
+
+_DATACLASS = DESCRIPTOR.enum_types_by_name['DataClass']
+DataClass = enum_type_wrapper.EnumTypeWrapper(_DATACLASS)
+DATA_CLASS_UNKNOWN = 0
+DATA_CLASS_SCALAR = 1
+DATA_CLASS_TENSOR = 2
+DATA_CLASS_BLOB_SEQUENCE = 3
+
+
+_SUMMARYDESCRIPTION = DESCRIPTOR.message_types_by_name['SummaryDescription']
+_SUMMARYMETADATA = DESCRIPTOR.message_types_by_name['SummaryMetadata']
+_SUMMARYMETADATA_PLUGINDATA = _SUMMARYMETADATA.nested_types_by_name['PluginData']
+_SUMMARY = DESCRIPTOR.message_types_by_name['Summary']
+_SUMMARY_IMAGE = _SUMMARY.nested_types_by_name['Image']
+_SUMMARY_AUDIO = _SUMMARY.nested_types_by_name['Audio']
+_SUMMARY_VALUE = _SUMMARY.nested_types_by_name['Value']
+SummaryDescription = _reflection.GeneratedProtocolMessageType('SummaryDescription', (_message.Message,), {
+  'DESCRIPTOR' : _SUMMARYDESCRIPTION,
+  '__module__' : 'tensorboard.compat.proto.summary_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SummaryDescription)
+  })
+_sym_db.RegisterMessage(SummaryDescription)
+
+SummaryMetadata = _reflection.GeneratedProtocolMessageType('SummaryMetadata', (_message.Message,), {
+
+  'PluginData' : _reflection.GeneratedProtocolMessageType('PluginData', (_message.Message,), {
+    'DESCRIPTOR' : _SUMMARYMETADATA_PLUGINDATA,
+    '__module__' : 'tensorboard.compat.proto.summary_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.SummaryMetadata.PluginData)
+    })
+  ,
+  'DESCRIPTOR' : _SUMMARYMETADATA,
+  '__module__' : 'tensorboard.compat.proto.summary_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SummaryMetadata)
+  })
+_sym_db.RegisterMessage(SummaryMetadata)
+_sym_db.RegisterMessage(SummaryMetadata.PluginData)
+
+Summary = _reflection.GeneratedProtocolMessageType('Summary', (_message.Message,), {
+
+  'Image' : _reflection.GeneratedProtocolMessageType('Image', (_message.Message,), {
+    'DESCRIPTOR' : _SUMMARY_IMAGE,
+    '__module__' : 'tensorboard.compat.proto.summary_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.Summary.Image)
+    })
+  ,
+
+  'Audio' : _reflection.GeneratedProtocolMessageType('Audio', (_message.Message,), {
+    'DESCRIPTOR' : _SUMMARY_AUDIO,
+    '__module__' : 'tensorboard.compat.proto.summary_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.Summary.Audio)
+    })
+  ,
+
+  'Value' : _reflection.GeneratedProtocolMessageType('Value', (_message.Message,), {
+    'DESCRIPTOR' : _SUMMARY_VALUE,
+    '__module__' : 'tensorboard.compat.proto.summary_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.Summary.Value)
+    })
+  ,
+  'DESCRIPTOR' : _SUMMARY,
+  '__module__' : 'tensorboard.compat.proto.summary_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.Summary)
+  })
+_sym_db.RegisterMessage(Summary)
+_sym_db.RegisterMessage(Summary.Image)
+_sym_db.RegisterMessage(Summary.Audio)
+_sym_db.RegisterMessage(Summary.Value)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\rSummaryProtosP\001ZNgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/summary_go_proto\370\001\001'
+  _DATACLASS._serialized_start=1021
+  _DATACLASS._serialized_end=1132
+  _SUMMARYDESCRIPTION._serialized_start=136
+  _SUMMARYDESCRIPTION._serialized_end=175
+  _SUMMARYMETADATA._serialized_start=178
+  _SUMMARYMETADATA._serialized_end=404
+  _SUMMARYMETADATA_PLUGINDATA._serialized_start=354
+  _SUMMARYMETADATA_PLUGINDATA._serialized_end=404
+  _SUMMARY._serialized_start=407
+  _SUMMARY._serialized_end=1019
+  _SUMMARY_IMAGE._serialized_start=461
+  _SUMMARY_IMAGE._serialized_end=549
+  _SUMMARY_AUDIO._serialized_start=551
+  _SUMMARY_AUDIO._serialized_end=676
+  _SUMMARY_VALUE._serialized_start=679
+  _SUMMARY_VALUE._serialized_end=1019
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/tensor_description_pb2.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/tensor_description.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()
+
+
+from tensorboard.compat.proto import allocation_description_pb2 as tensorboard_dot_compat_dot_proto_dot_allocation__description__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n1tensorboard/compat/proto/tensor_description.proto\x12\x0btensorboard\x1a\x35tensorboard/compat/proto/allocation_description.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xab\x01\n\x11TensorDescription\x12$\n\x05\x64type\x18\x01 \x01(\x0e\x32\x15.tensorboard.DataType\x12,\n\x05shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12\x42\n\x16\x61llocation_description\x18\x04 \x01(\x0b\x32\".tensorboard.AllocationDescriptionB\x93\x01\n\x18org.tensorflow.frameworkB\x17TensorDescriptionProtosP\x01ZYgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_description_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_TENSORDESCRIPTION = DESCRIPTOR.message_types_by_name['TensorDescription']
+TensorDescription = _reflection.GeneratedProtocolMessageType('TensorDescription', (_message.Message,), {
+  'DESCRIPTOR' : _TENSORDESCRIPTION,
+  '__module__' : 'tensorboard.compat.proto.tensor_description_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TensorDescription)
+  })
+_sym_db.RegisterMessage(TensorDescription)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\027TensorDescriptionProtosP\001ZYgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_description_go_proto\370\001\001'
+  _TENSORDESCRIPTION._serialized_start=205
+  _TENSORDESCRIPTION._serialized_end=376
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/tensor_pb2.py

@@ -0,0 +1,68 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/tensor.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()
+
+
+from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2
+from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2
+from tensorboard.compat.proto import types_pb2 as tensorboard_dot_compat_dot_proto_dot_types__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n%tensorboard/compat/proto/tensor.proto\x12\x0btensorboard\x1a.tensorboard/compat/proto/resource_handle.proto\x1a+tensorboard/compat/proto/tensor_shape.proto\x1a$tensorboard/compat/proto/types.proto\"\xa4\x04\n\x0bTensorProto\x12$\n\x05\x64type\x18\x01 \x01(\x0e\x32\x15.tensorboard.DataType\x12\x33\n\x0ctensor_shape\x18\x02 \x01(\x0b\x32\x1d.tensorboard.TensorShapeProto\x12\x16\n\x0eversion_number\x18\x03 \x01(\x05\x12\x16\n\x0etensor_content\x18\x04 \x01(\x0c\x12\x14\n\x08half_val\x18\r \x03(\x05\x42\x02\x10\x01\x12\x15\n\tfloat_val\x18\x05 \x03(\x02\x42\x02\x10\x01\x12\x16\n\ndouble_val\x18\x06 \x03(\x01\x42\x02\x10\x01\x12\x13\n\x07int_val\x18\x07 \x03(\x05\x42\x02\x10\x01\x12\x12\n\nstring_val\x18\x08 \x03(\x0c\x12\x18\n\x0cscomplex_val\x18\t \x03(\x02\x42\x02\x10\x01\x12\x15\n\tint64_val\x18\n \x03(\x03\x42\x02\x10\x01\x12\x14\n\x08\x62ool_val\x18\x0b \x03(\x08\x42\x02\x10\x01\x12\x18\n\x0c\x64\x63omplex_val\x18\x0c \x03(\x01\x42\x02\x10\x01\x12=\n\x13resource_handle_val\x18\x0e \x03(\x0b\x32 .tensorboard.ResourceHandleProto\x12\x38\n\x0bvariant_val\x18\x0f \x03(\x0b\x32#.tensorboard.VariantTensorDataProto\x12\x16\n\nuint32_val\x18\x10 \x03(\rB\x02\x10\x01\x12\x16\n\nuint64_val\x18\x11 \x03(\x04\x42\x02\x10\x01\x12\x12\n\nfloat8_val\x18\x12 \x01(\x0c\"h\n\x16VariantTensorDataProto\x12\x11\n\ttype_name\x18\x01 \x01(\t\x12\x10\n\x08metadata\x18\x02 \x01(\x0c\x12)\n\x07tensors\x18\x03 \x03(\x0b\x32\x18.tensorboard.TensorProtoB|\n\x18org.tensorflow.frameworkB\x0cTensorProtosP\x01ZMgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_TENSORPROTO = DESCRIPTOR.message_types_by_name['TensorProto']
+_VARIANTTENSORDATAPROTO = DESCRIPTOR.message_types_by_name['VariantTensorDataProto']
+TensorProto = _reflection.GeneratedProtocolMessageType('TensorProto', (_message.Message,), {
+  'DESCRIPTOR' : _TENSORPROTO,
+  '__module__' : 'tensorboard.compat.proto.tensor_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TensorProto)
+  })
+_sym_db.RegisterMessage(TensorProto)
+
+VariantTensorDataProto = _reflection.GeneratedProtocolMessageType('VariantTensorDataProto', (_message.Message,), {
+  'DESCRIPTOR' : _VARIANTTENSORDATAPROTO,
+  '__module__' : 'tensorboard.compat.proto.tensor_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.VariantTensorDataProto)
+  })
+_sym_db.RegisterMessage(VariantTensorDataProto)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\014TensorProtosP\001ZMgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_go_proto\370\001\001'
+  _TENSORPROTO.fields_by_name['half_val']._options = None
+  _TENSORPROTO.fields_by_name['half_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['float_val']._options = None
+  _TENSORPROTO.fields_by_name['float_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['double_val']._options = None
+  _TENSORPROTO.fields_by_name['double_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['int_val']._options = None
+  _TENSORPROTO.fields_by_name['int_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['scomplex_val']._options = None
+  _TENSORPROTO.fields_by_name['scomplex_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['int64_val']._options = None
+  _TENSORPROTO.fields_by_name['int64_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['bool_val']._options = None
+  _TENSORPROTO.fields_by_name['bool_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['dcomplex_val']._options = None
+  _TENSORPROTO.fields_by_name['dcomplex_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['uint32_val']._options = None
+  _TENSORPROTO.fields_by_name['uint32_val']._serialized_options = b'\020\001'
+  _TENSORPROTO.fields_by_name['uint64_val']._options = None
+  _TENSORPROTO.fields_by_name['uint64_val']._serialized_options = b'\020\001'
+  _TENSORPROTO._serialized_start=186
+  _TENSORPROTO._serialized_end=734
+  _VARIANTTENSORDATAPROTO._serialized_start=736
+  _VARIANTTENSORDATAPROTO._serialized_end=840
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/tensor_shape_pb2.py

@@ -0,0 +1,46 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/tensor_shape.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/compat/proto/tensor_shape.proto\x12\x0btensorboard\"{\n\x10TensorShapeProto\x12.\n\x03\x64im\x18\x02 \x03(\x0b\x32!.tensorboard.TensorShapeProto.Dim\x12\x14\n\x0cunknown_rank\x18\x03 \x01(\x08\x1a!\n\x03\x44im\x12\x0c\n\x04size\x18\x01 \x01(\x03\x12\x0c\n\x04name\x18\x02 \x01(\tB\x87\x01\n\x18org.tensorflow.frameworkB\x11TensorShapeProtosP\x01ZSgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_shape_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_TENSORSHAPEPROTO = DESCRIPTOR.message_types_by_name['TensorShapeProto']
+_TENSORSHAPEPROTO_DIM = _TENSORSHAPEPROTO.nested_types_by_name['Dim']
+TensorShapeProto = _reflection.GeneratedProtocolMessageType('TensorShapeProto', (_message.Message,), {
+
+  'Dim' : _reflection.GeneratedProtocolMessageType('Dim', (_message.Message,), {
+    'DESCRIPTOR' : _TENSORSHAPEPROTO_DIM,
+    '__module__' : 'tensorboard.compat.proto.tensor_shape_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.TensorShapeProto.Dim)
+    })
+  ,
+  'DESCRIPTOR' : _TENSORSHAPEPROTO,
+  '__module__' : 'tensorboard.compat.proto.tensor_shape_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TensorShapeProto)
+  })
+_sym_db.RegisterMessage(TensorShapeProto)
+_sym_db.RegisterMessage(TensorShapeProto.Dim)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\021TensorShapeProtosP\001ZSgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_shape_go_proto\370\001\001'
+  _TENSORSHAPEPROTO._serialized_start=60
+  _TENSORSHAPEPROTO._serialized_end=183
+  _TENSORSHAPEPROTO_DIM._serialized_start=150
+  _TENSORSHAPEPROTO_DIM._serialized_end=183
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/trackable_object_graph_pb2.py

@@ -0,0 +1,90 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/trackable_object_graph.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()
+
+
+from google.protobuf import wrappers_pb2 as google_dot_protobuf_dot_wrappers__pb2
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n5tensorboard/compat/proto/trackable_object_graph.proto\x12\x0btensorboard\x1a\x1egoogle/protobuf/wrappers.proto\"\xf8\x05\n\x14TrackableObjectGraph\x12@\n\x05nodes\x18\x01 \x03(\x0b\x32\x31.tensorboard.TrackableObjectGraph.TrackableObject\x1a\x9d\x05\n\x0fTrackableObject\x12S\n\x08\x63hildren\x18\x01 \x03(\x0b\x32\x41.tensorboard.TrackableObjectGraph.TrackableObject.ObjectReference\x12V\n\nattributes\x18\x02 \x03(\x0b\x32\x42.tensorboard.TrackableObjectGraph.TrackableObject.SerializedTensor\x12_\n\x0eslot_variables\x18\x03 \x03(\x0b\x32G.tensorboard.TrackableObjectGraph.TrackableObject.SlotVariableReference\x12\x36\n\x10registered_saver\x18\x04 \x01(\x0b\x32\x1c.tensorboard.RegisteredSaver\x12\x39\n\x15has_checkpoint_values\x18\x05 \x01(\x0b\x32\x1a.google.protobuf.BoolValue\x1a\x36\n\x0fObjectReference\x12\x0f\n\x07node_id\x18\x01 \x01(\x05\x12\x12\n\nlocal_name\x18\x02 \x01(\t\x1a\x63\n\x10SerializedTensor\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x11\n\tfull_name\x18\x02 \x01(\t\x12\x16\n\x0e\x63heckpoint_key\x18\x03 \x01(\tJ\x04\x08\x04\x10\x05R\x10optional_restore\x1al\n\x15SlotVariableReference\x12!\n\x19original_variable_node_id\x18\x01 \x01(\x05\x12\x11\n\tslot_name\x18\x02 \x01(\t\x12\x1d\n\x15slot_variable_node_id\x18\x03 \x01(\x05\"4\n\x0fRegisteredSaver\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x13\n\x0bobject_name\x18\x02 \x01(\tBZZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_TRACKABLEOBJECTGRAPH = DESCRIPTOR.message_types_by_name['TrackableObjectGraph']
+_TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT = _TRACKABLEOBJECTGRAPH.nested_types_by_name['TrackableObject']
+_TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_OBJECTREFERENCE = _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT.nested_types_by_name['ObjectReference']
+_TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SERIALIZEDTENSOR = _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT.nested_types_by_name['SerializedTensor']
+_TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SLOTVARIABLEREFERENCE = _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT.nested_types_by_name['SlotVariableReference']
+_REGISTEREDSAVER = DESCRIPTOR.message_types_by_name['RegisteredSaver']
+TrackableObjectGraph = _reflection.GeneratedProtocolMessageType('TrackableObjectGraph', (_message.Message,), {
+
+  'TrackableObject' : _reflection.GeneratedProtocolMessageType('TrackableObject', (_message.Message,), {
+
+    'ObjectReference' : _reflection.GeneratedProtocolMessageType('ObjectReference', (_message.Message,), {
+      'DESCRIPTOR' : _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_OBJECTREFERENCE,
+      '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.TrackableObjectGraph.TrackableObject.ObjectReference)
+      })
+    ,
+
+    'SerializedTensor' : _reflection.GeneratedProtocolMessageType('SerializedTensor', (_message.Message,), {
+      'DESCRIPTOR' : _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SERIALIZEDTENSOR,
+      '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.TrackableObjectGraph.TrackableObject.SerializedTensor)
+      })
+    ,
+
+    'SlotVariableReference' : _reflection.GeneratedProtocolMessageType('SlotVariableReference', (_message.Message,), {
+      'DESCRIPTOR' : _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SLOTVARIABLEREFERENCE,
+      '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+      # @@protoc_insertion_point(class_scope:tensorboard.TrackableObjectGraph.TrackableObject.SlotVariableReference)
+      })
+    ,
+    'DESCRIPTOR' : _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT,
+    '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+    # @@protoc_insertion_point(class_scope:tensorboard.TrackableObjectGraph.TrackableObject)
+    })
+  ,
+  'DESCRIPTOR' : _TRACKABLEOBJECTGRAPH,
+  '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.TrackableObjectGraph)
+  })
+_sym_db.RegisterMessage(TrackableObjectGraph)
+_sym_db.RegisterMessage(TrackableObjectGraph.TrackableObject)
+_sym_db.RegisterMessage(TrackableObjectGraph.TrackableObject.ObjectReference)
+_sym_db.RegisterMessage(TrackableObjectGraph.TrackableObject.SerializedTensor)
+_sym_db.RegisterMessage(TrackableObjectGraph.TrackableObject.SlotVariableReference)
+
+RegisteredSaver = _reflection.GeneratedProtocolMessageType('RegisteredSaver', (_message.Message,), {
+  'DESCRIPTOR' : _REGISTEREDSAVER,
+  '__module__' : 'tensorboard.compat.proto.trackable_object_graph_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.RegisteredSaver)
+  })
+_sym_db.RegisterMessage(RegisteredSaver)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _TRACKABLEOBJECTGRAPH._serialized_start=103
+  _TRACKABLEOBJECTGRAPH._serialized_end=863
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT._serialized_start=194
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT._serialized_end=863
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_OBJECTREFERENCE._serialized_start=598
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_OBJECTREFERENCE._serialized_end=652
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SERIALIZEDTENSOR._serialized_start=654
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SERIALIZEDTENSOR._serialized_end=753
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SLOTVARIABLEREFERENCE._serialized_start=755
+  _TRACKABLEOBJECTGRAPH_TRACKABLEOBJECT_SLOTVARIABLEREFERENCE._serialized_end=863
+  _REGISTEREDSAVER._serialized_start=865
+  _REGISTEREDSAVER._serialized_end=917
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/types_pb2.py

@@ -0,0 +1,95 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/types.proto
+"""Generated protocol buffer code."""
+from google.protobuf.internal import enum_type_wrapper
+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/compat/proto/types.proto\x12\x0btensorboard\":\n\x0fSerializedDType\x12\'\n\x08\x64\x61tatype\x18\x01 \x01(\x0e\x32\x15.tensorboard.DataType*\xc6\x07\n\x08\x44\x61taType\x12\x0e\n\nDT_INVALID\x10\x00\x12\x0c\n\x08\x44T_FLOAT\x10\x01\x12\r\n\tDT_DOUBLE\x10\x02\x12\x0c\n\x08\x44T_INT32\x10\x03\x12\x0c\n\x08\x44T_UINT8\x10\x04\x12\x0c\n\x08\x44T_INT16\x10\x05\x12\x0b\n\x07\x44T_INT8\x10\x06\x12\r\n\tDT_STRING\x10\x07\x12\x10\n\x0c\x44T_COMPLEX64\x10\x08\x12\x0c\n\x08\x44T_INT64\x10\t\x12\x0b\n\x07\x44T_BOOL\x10\n\x12\x0c\n\x08\x44T_QINT8\x10\x0b\x12\r\n\tDT_QUINT8\x10\x0c\x12\r\n\tDT_QINT32\x10\r\x12\x0f\n\x0b\x44T_BFLOAT16\x10\x0e\x12\r\n\tDT_QINT16\x10\x0f\x12\x0e\n\nDT_QUINT16\x10\x10\x12\r\n\tDT_UINT16\x10\x11\x12\x11\n\rDT_COMPLEX128\x10\x12\x12\x0b\n\x07\x44T_HALF\x10\x13\x12\x0f\n\x0b\x44T_RESOURCE\x10\x14\x12\x0e\n\nDT_VARIANT\x10\x15\x12\r\n\tDT_UINT32\x10\x16\x12\r\n\tDT_UINT64\x10\x17\x12\x12\n\x0e\x44T_FLOAT8_E5M2\x10\x18\x12\x14\n\x10\x44T_FLOAT8_E4M3FN\x10\x19\x12\x0b\n\x07\x44T_INT4\x10\x1d\x12\x0c\n\x08\x44T_UINT4\x10\x1e\x12\x10\n\x0c\x44T_FLOAT_REF\x10\x65\x12\x11\n\rDT_DOUBLE_REF\x10\x66\x12\x10\n\x0c\x44T_INT32_REF\x10g\x12\x10\n\x0c\x44T_UINT8_REF\x10h\x12\x10\n\x0c\x44T_INT16_REF\x10i\x12\x0f\n\x0b\x44T_INT8_REF\x10j\x12\x11\n\rDT_STRING_REF\x10k\x12\x14\n\x10\x44T_COMPLEX64_REF\x10l\x12\x10\n\x0c\x44T_INT64_REF\x10m\x12\x0f\n\x0b\x44T_BOOL_REF\x10n\x12\x10\n\x0c\x44T_QINT8_REF\x10o\x12\x11\n\rDT_QUINT8_REF\x10p\x12\x11\n\rDT_QINT32_REF\x10q\x12\x13\n\x0f\x44T_BFLOAT16_REF\x10r\x12\x11\n\rDT_QINT16_REF\x10s\x12\x12\n\x0e\x44T_QUINT16_REF\x10t\x12\x11\n\rDT_UINT16_REF\x10u\x12\x15\n\x11\x44T_COMPLEX128_REF\x10v\x12\x0f\n\x0b\x44T_HALF_REF\x10w\x12\x13\n\x0f\x44T_RESOURCE_REF\x10x\x12\x12\n\x0e\x44T_VARIANT_REF\x10y\x12\x11\n\rDT_UINT32_REF\x10z\x12\x11\n\rDT_UINT64_REF\x10{\x12\x16\n\x12\x44T_FLOAT8_E5M2_REF\x10|\x12\x18\n\x14\x44T_FLOAT8_E4M3FN_REF\x10}\x12\x10\n\x0b\x44T_INT4_REF\x10\x81\x01\x12\x11\n\x0c\x44T_UINT4_REF\x10\x82\x01\x42z\n\x18org.tensorflow.frameworkB\x0bTypesProtosP\x01ZLgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/types_go_proto\xf8\x01\x01\x62\x06proto3')
+
+_DATATYPE = DESCRIPTOR.enum_types_by_name['DataType']
+DataType = enum_type_wrapper.EnumTypeWrapper(_DATATYPE)
+DT_INVALID = 0
+DT_FLOAT = 1
+DT_DOUBLE = 2
+DT_INT32 = 3
+DT_UINT8 = 4
+DT_INT16 = 5
+DT_INT8 = 6
+DT_STRING = 7
+DT_COMPLEX64 = 8
+DT_INT64 = 9
+DT_BOOL = 10
+DT_QINT8 = 11
+DT_QUINT8 = 12
+DT_QINT32 = 13
+DT_BFLOAT16 = 14
+DT_QINT16 = 15
+DT_QUINT16 = 16
+DT_UINT16 = 17
+DT_COMPLEX128 = 18
+DT_HALF = 19
+DT_RESOURCE = 20
+DT_VARIANT = 21
+DT_UINT32 = 22
+DT_UINT64 = 23
+DT_FLOAT8_E5M2 = 24
+DT_FLOAT8_E4M3FN = 25
+DT_INT4 = 29
+DT_UINT4 = 30
+DT_FLOAT_REF = 101
+DT_DOUBLE_REF = 102
+DT_INT32_REF = 103
+DT_UINT8_REF = 104
+DT_INT16_REF = 105
+DT_INT8_REF = 106
+DT_STRING_REF = 107
+DT_COMPLEX64_REF = 108
+DT_INT64_REF = 109
+DT_BOOL_REF = 110
+DT_QINT8_REF = 111
+DT_QUINT8_REF = 112
+DT_QINT32_REF = 113
+DT_BFLOAT16_REF = 114
+DT_QINT16_REF = 115
+DT_QUINT16_REF = 116
+DT_UINT16_REF = 117
+DT_COMPLEX128_REF = 118
+DT_HALF_REF = 119
+DT_RESOURCE_REF = 120
+DT_VARIANT_REF = 121
+DT_UINT32_REF = 122
+DT_UINT64_REF = 123
+DT_FLOAT8_E5M2_REF = 124
+DT_FLOAT8_E4M3FN_REF = 125
+DT_INT4_REF = 129
+DT_UINT4_REF = 130
+
+
+_SERIALIZEDDTYPE = DESCRIPTOR.message_types_by_name['SerializedDType']
+SerializedDType = _reflection.GeneratedProtocolMessageType('SerializedDType', (_message.Message,), {
+  'DESCRIPTOR' : _SERIALIZEDDTYPE,
+  '__module__' : 'tensorboard.compat.proto.types_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SerializedDType)
+  })
+_sym_db.RegisterMessage(SerializedDType)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\013TypesProtosP\001ZLgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/types_go_proto\370\001\001'
+  _DATATYPE._serialized_start=114
+  _DATATYPE._serialized_end=1080
+  _SERIALIZEDDTYPE._serialized_start=53
+  _SERIALIZEDDTYPE._serialized_end=111
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/variable_pb2.py

@@ -0,0 +1,62 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/variable.proto
+"""Generated protocol buffer code."""
+from google.protobuf.internal import enum_type_wrapper
+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/compat/proto/variable.proto\x12\x0btensorboard\"\xcb\x02\n\x0bVariableDef\x12\x15\n\rvariable_name\x18\x01 \x01(\t\x12\x1a\n\x12initial_value_name\x18\x06 \x01(\t\x12\x18\n\x10initializer_name\x18\x02 \x01(\t\x12\x15\n\rsnapshot_name\x18\x03 \x01(\t\x12:\n\x13save_slice_info_def\x18\x04 \x01(\x0b\x32\x1d.tensorboard.SaveSliceInfoDef\x12\x13\n\x0bis_resource\x18\x05 \x01(\x08\x12\x11\n\ttrainable\x18\x07 \x01(\x08\x12=\n\x0fsynchronization\x18\x08 \x01(\x0e\x32$.tensorboard.VariableSynchronization\x12\x35\n\x0b\x61ggregation\x18\t \x01(\x0e\x32 .tensorboard.VariableAggregation\"`\n\x10SaveSliceInfoDef\x12\x11\n\tfull_name\x18\x01 \x01(\t\x12\x12\n\nfull_shape\x18\x02 \x03(\x03\x12\x12\n\nvar_offset\x18\x03 \x03(\x03\x12\x11\n\tvar_shape\x18\x04 \x03(\x03*\xac\x01\n\x17VariableSynchronization\x12!\n\x1dVARIABLE_SYNCHRONIZATION_AUTO\x10\x00\x12!\n\x1dVARIABLE_SYNCHRONIZATION_NONE\x10\x01\x12%\n!VARIABLE_SYNCHRONIZATION_ON_WRITE\x10\x02\x12$\n VARIABLE_SYNCHRONIZATION_ON_READ\x10\x03*\x9e\x01\n\x13VariableAggregation\x12\x1d\n\x19VARIABLE_AGGREGATION_NONE\x10\x00\x12\x1c\n\x18VARIABLE_AGGREGATION_SUM\x10\x01\x12\x1d\n\x19VARIABLE_AGGREGATION_MEAN\x10\x02\x12+\n\'VARIABLE_AGGREGATION_ONLY_FIRST_REPLICA\x10\x03\x42\x80\x01\n\x18org.tensorflow.frameworkB\x0eVariableProtosP\x01ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/variable_go_proto\xf8\x01\x01\x62\x06proto3')
+
+_VARIABLESYNCHRONIZATION = DESCRIPTOR.enum_types_by_name['VariableSynchronization']
+VariableSynchronization = enum_type_wrapper.EnumTypeWrapper(_VARIABLESYNCHRONIZATION)
+_VARIABLEAGGREGATION = DESCRIPTOR.enum_types_by_name['VariableAggregation']
+VariableAggregation = enum_type_wrapper.EnumTypeWrapper(_VARIABLEAGGREGATION)
+VARIABLE_SYNCHRONIZATION_AUTO = 0
+VARIABLE_SYNCHRONIZATION_NONE = 1
+VARIABLE_SYNCHRONIZATION_ON_WRITE = 2
+VARIABLE_SYNCHRONIZATION_ON_READ = 3
+VARIABLE_AGGREGATION_NONE = 0
+VARIABLE_AGGREGATION_SUM = 1
+VARIABLE_AGGREGATION_MEAN = 2
+VARIABLE_AGGREGATION_ONLY_FIRST_REPLICA = 3
+
+
+_VARIABLEDEF = DESCRIPTOR.message_types_by_name['VariableDef']
+_SAVESLICEINFODEF = DESCRIPTOR.message_types_by_name['SaveSliceInfoDef']
+VariableDef = _reflection.GeneratedProtocolMessageType('VariableDef', (_message.Message,), {
+  'DESCRIPTOR' : _VARIABLEDEF,
+  '__module__' : 'tensorboard.compat.proto.variable_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.VariableDef)
+  })
+_sym_db.RegisterMessage(VariableDef)
+
+SaveSliceInfoDef = _reflection.GeneratedProtocolMessageType('SaveSliceInfoDef', (_message.Message,), {
+  'DESCRIPTOR' : _SAVESLICEINFODEF,
+  '__module__' : 'tensorboard.compat.proto.variable_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.SaveSliceInfoDef)
+  })
+_sym_db.RegisterMessage(SaveSliceInfoDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\016VariableProtosP\001ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/variable_go_proto\370\001\001'
+  _VARIABLESYNCHRONIZATION._serialized_start=489
+  _VARIABLESYNCHRONIZATION._serialized_end=661
+  _VARIABLEAGGREGATION._serialized_start=664
+  _VARIABLEAGGREGATION._serialized_end=822
+  _VARIABLEDEF._serialized_start=57
+  _VARIABLEDEF._serialized_end=388
+  _SAVESLICEINFODEF._serialized_start=390
+  _SAVESLICEINFODEF._serialized_end=486
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/verifier_config_pb2.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/verifier_config.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/compat/proto/verifier_config.proto\x12\x0btensorboard\"\x9c\x01\n\x0eVerifierConfig\x12\"\n\x1averification_timeout_in_ms\x18\x01 \x01(\x03\x12>\n\x12structure_verifier\x18\x02 \x01(\x0e\x32\".tensorboard.VerifierConfig.Toggle\"&\n\x06Toggle\x12\x0b\n\x07\x44\x45\x46\x41ULT\x10\x00\x12\x06\n\x02ON\x10\x01\x12\x07\n\x03OFF\x10\x02\x42\x8c\x01\n\x18org.tensorflow.frameworkB\x14VerifierConfigProtosP\x01ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_VERIFIERCONFIG = DESCRIPTOR.message_types_by_name['VerifierConfig']
+_VERIFIERCONFIG_TOGGLE = _VERIFIERCONFIG.enum_types_by_name['Toggle']
+VerifierConfig = _reflection.GeneratedProtocolMessageType('VerifierConfig', (_message.Message,), {
+  'DESCRIPTOR' : _VERIFIERCONFIG,
+  '__module__' : 'tensorboard.compat.proto.verifier_config_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.VerifierConfig)
+  })
+_sym_db.RegisterMessage(VerifierConfig)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\024VerifierConfigProtosP\001ZUgithub.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto\370\001\001'
+  _VERIFIERCONFIG._serialized_start=64
+  _VERIFIERCONFIG._serialized_end=220
+  _VERIFIERCONFIG_TOGGLE._serialized_start=182
+  _VERIFIERCONFIG_TOGGLE._serialized_end=220
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/proto/versions_pb2.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: tensorboard/compat/proto/versions.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/compat/proto/versions.proto\x12\x0btensorboard\"K\n\nVersionDef\x12\x10\n\x08producer\x18\x01 \x01(\x05\x12\x14\n\x0cmin_consumer\x18\x02 \x01(\x05\x12\x15\n\rbad_consumers\x18\x03 \x03(\x05\x42\x80\x01\n\x18org.tensorflow.frameworkB\x0eVersionsProtosP\x01ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/versions_go_proto\xf8\x01\x01\x62\x06proto3')
+
+
+
+_VERSIONDEF = DESCRIPTOR.message_types_by_name['VersionDef']
+VersionDef = _reflection.GeneratedProtocolMessageType('VersionDef', (_message.Message,), {
+  'DESCRIPTOR' : _VERSIONDEF,
+  '__module__' : 'tensorboard.compat.proto.versions_pb2'
+  # @@protoc_insertion_point(class_scope:tensorboard.VersionDef)
+  })
+_sym_db.RegisterMessage(VersionDef)
+
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\030org.tensorflow.frameworkB\016VersionsProtosP\001ZOgithub.com/tensorflow/tensorflow/tensorflow/go/core/framework/versions_go_proto\370\001\001'
+  _VERSIONDEF._serialized_start=56
+  _VERSIONDEF._serialized_end=131
+# @@protoc_insertion_point(module_scope)

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/__init__.py

@@ -0,0 +1,38 @@
+# Copyright 2018 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.
+# ==============================================================================
+
+
+from tensorboard.compat.proto.config_pb2 import *  # noqa
+from tensorboard.compat.proto.event_pb2 import *  # noqa
+from tensorboard.compat.proto.graph_pb2 import *  # noqa
+from tensorboard.compat.proto.meta_graph_pb2 import *  # noqa
+from tensorboard.compat.proto.summary_pb2 import *  # noqa
+from .dtypes import as_dtype  # noqa
+from .dtypes import DType  # noqa
+from .dtypes import string  # noqa
+from . import app  # noqa
+from . import compat  # noqa
+from . import dtypes  # noqa
+from . import error_codes  # noqa
+from . import errors  # noqa
+from . import flags  # noqa
+from . import io  # noqa
+from . import pywrap_tensorflow  # noqa
+from . import tensor_shape  # noqa
+
+compat.v1.errors = errors
+
+# Set a fake __version__ to help distinguish this as our own stub API.
+__version__ = "stub"

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/app.py

@@ -0,0 +1,124 @@
+# Copyright 2015 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.
+# ==============================================================================
+
+"""Generic entry point script."""
+
+import errno as _errno
+import sys as _sys
+
+from . import flags
+
+
+def _usage(shorthelp):
+    """Writes __main__'s docstring to stdout with some help text.
+
+    Args:
+      shorthelp: bool, if True, prints only flags from the main module,
+          rather than all flags.
+    """
+    doc = _sys.modules["__main__"].__doc__
+    if not doc:
+        doc = "\nUSAGE: %s [flags]\n" % _sys.argv[0]
+        doc = flags.text_wrap(doc, indent="       ", firstline_indent="")
+    else:
+        # Replace all '%s' with sys.argv[0], and all '%%' with '%'.
+        num_specifiers = doc.count("%") - 2 * doc.count("%%")
+        try:
+            doc %= (_sys.argv[0],) * num_specifiers
+        except (OverflowError, TypeError, ValueError):
+            # Just display the docstring as-is.
+            pass
+    if shorthelp:
+        flag_str = flags.FLAGS.main_module_help()
+    else:
+        flag_str = str(flags.FLAGS)
+    try:
+        _sys.stdout.write(doc)
+        if flag_str:
+            _sys.stdout.write("\nflags:\n")
+            _sys.stdout.write(flag_str)
+        _sys.stdout.write("\n")
+    except IOError as e:
+        # We avoid printing a huge backtrace if we get EPIPE, because
+        # "foo.par --help | less" is a frequent use case.
+        if e.errno != _errno.EPIPE:
+            raise
+
+
+class _HelpFlag(flags.BooleanFlag):
+    """Special boolean flag that displays usage and raises SystemExit."""
+
+    NAME = "help"
+    SHORT_NAME = "h"
+
+    def __init__(self):
+        super().__init__(
+            self.NAME, False, "show this help", short_name=self.SHORT_NAME
+        )
+
+    def parse(self, arg):
+        if arg:
+            _usage(shorthelp=True)
+            print()
+            print("Try --helpfull to get a list of all flags.")
+            _sys.exit(1)
+
+
+class _HelpshortFlag(_HelpFlag):
+    """--helpshort is an alias for --help."""
+
+    NAME = "helpshort"
+    SHORT_NAME = None
+
+
+class _HelpfullFlag(flags.BooleanFlag):
+    """Display help for flags in main module and all dependent modules."""
+
+    def __init__(self):
+        super().__init__("helpfull", False, "show full help")
+
+    def parse(self, arg):
+        if arg:
+            _usage(shorthelp=False)
+            _sys.exit(1)
+
+
+_define_help_flags_called = False
+
+
+def _define_help_flags():
+    global _define_help_flags_called
+    if not _define_help_flags_called:
+        flags.DEFINE_flag(_HelpFlag())
+        flags.DEFINE_flag(_HelpfullFlag())
+        flags.DEFINE_flag(_HelpshortFlag())
+        _define_help_flags_called = True
+
+
+# @tf_export('app.run')
+def run(main=None, argv=None):
+    """Runs the program with an optional 'main' function and 'argv' list."""
+
+    # Define help flags.
+    _define_help_flags()
+
+    # Parse known flags.
+    argv = flags.FLAGS(_sys.argv if argv is None else argv, known_only=True)
+
+    main = main or _sys.modules["__main__"].main
+
+    # Call the main function, passing through any arguments
+    # to the final program.
+    _sys.exit(main(argv))

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/compat/__init__.py

@@ -0,0 +1,132 @@
+# Copyright 2015 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.
+# ==============================================================================
+"""Functions for Python 2 vs. 3 compatibility.
+
+## Conversion routines
+In addition to the functions below, `as_str` converts an object to a `str`.
+
+
+## Types
+The compatibility module also provides the following types:
+
+* `bytes_or_text_types`
+* `complex_types`
+* `integral_types`
+* `real_types`
+"""
+
+
+import numbers as _numbers
+import numpy as _np
+
+from tensorboard.compat.tensorflow_stub.compat.v1 import *  # noqa
+
+
+def as_bytes(bytes_or_text, encoding="utf-8"):
+    """Converts either bytes or unicode to `bytes`, using utf-8 encoding for
+    text.
+
+    Args:
+    bytes_or_text: A `bytes`, `str`, or `unicode` object.
+    encoding: A string indicating the charset for encoding unicode.
+
+    Returns:
+    A `bytes` object.
+
+    Raises:
+    TypeError: If `bytes_or_text` is not a binary or unicode string.
+    """
+    if isinstance(bytes_or_text, str):
+        return bytes_or_text.encode(encoding)
+    elif isinstance(bytes_or_text, bytes):
+        return bytes_or_text
+    else:
+        raise TypeError(
+            "Expected binary or unicode string, got %r" % (bytes_or_text,)
+        )
+
+
+def as_text(bytes_or_text, encoding="utf-8"):
+    """Returns the given argument as a unicode string.
+
+    Args:
+    bytes_or_text: A `bytes`, `str`, or `unicode` object.
+    encoding: A string indicating the charset for decoding unicode.
+
+    Returns:
+    A `unicode` (Python 2) or `str` (Python 3) object.
+
+    Raises:
+    TypeError: If `bytes_or_text` is not a binary or unicode string.
+    """
+    if isinstance(bytes_or_text, str):
+        return bytes_or_text
+    elif isinstance(bytes_or_text, bytes):
+        return bytes_or_text.decode(encoding)
+    else:
+        raise TypeError(
+            "Expected binary or unicode string, got %r" % bytes_or_text
+        )
+
+
+# Convert an object to a `str` in both Python 2 and 3.
+as_str = as_text
+
+
+# @tf_export('compat.as_str_any')
+def as_str_any(value):
+    """Converts to `str` as `str(value)`, but use `as_str` for `bytes`.
+
+    Args:
+    value: A object that can be converted to `str`.
+
+    Returns:
+    A `str` object.
+    """
+    if isinstance(value, bytes):
+        return as_str(value)
+    else:
+        return str(value)
+
+
+# @tf_export('compat.path_to_str')
+def path_to_str(path):
+    """Returns the file system path representation of a `PathLike` object, else
+    as it is.
+
+    Args:
+    path: An object that can be converted to path representation.
+
+    Returns:
+    A `str` object.
+    """
+    if hasattr(path, "__fspath__"):
+        path = as_str_any(path.__fspath__())
+    return path
+
+
+# Numpy 1.8 scalars don't inherit from numbers.Integral in Python 3, so we
+# need to check them specifically.  The same goes from Real and Complex.
+integral_types = (_numbers.Integral, _np.integer)
+# tf_export('compat.integral_types').export_constant(__name__, 'integral_types')
+real_types = (_numbers.Real, _np.integer, _np.floating)
+# tf_export('compat.real_types').export_constant(__name__, 'real_types')
+complex_types = (_numbers.Complex, _np.number)
+# tf_export('compat.complex_types').export_constant(__name__, 'complex_types')
+
+# Either bytes or text.
+bytes_or_text_types = (bytes, str)
+# tf_export('compat.bytes_or_text_types').export_constant(__name__,
+#                                                         'bytes_or_text_types')

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/compat/v1/__init__.py

@@ -0,0 +1,20 @@
+# Copyright 2018 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.
+# ==============================================================================
+
+
+# Set this in tensorboard/compat/tensorflow_stub/__init__.py to eliminate
+# any cycles on import
+#
+# from tensorboard.compat.tensorflow_stub import pywrap_tensorflow  # noqa

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py

@@ -0,0 +1,692 @@
+# Copyright 2015 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.
+# ==============================================================================
+"""Library of dtypes (Tensor element types)."""
+
+import numpy as np
+
+from . import pywrap_tensorflow
+from tensorboard.compat.proto import types_pb2
+
+_np_bfloat16 = pywrap_tensorflow.TF_bfloat16_type()
+
+
+# @tf_export("DType")
+class DType:
+    """Represents the type of the elements in a `Tensor`.
+
+    The following `DType` objects are defined:
+
+    * `tf.float16`: 16-bit half-precision floating-point.
+    * `tf.float32`: 32-bit single-precision floating-point.
+    * `tf.float64`: 64-bit double-precision floating-point.
+    * `tf.bfloat16`: 16-bit truncated floating-point.
+    * `tf.complex64`: 64-bit single-precision complex.
+    * `tf.complex128`: 128-bit double-precision complex.
+    * `tf.int8`: 8-bit signed integer.
+    * `tf.uint8`: 8-bit unsigned integer.
+    * `tf.uint16`: 16-bit unsigned integer.
+    * `tf.uint32`: 32-bit unsigned integer.
+    * `tf.uint64`: 64-bit unsigned integer.
+    * `tf.int16`: 16-bit signed integer.
+    * `tf.int32`: 32-bit signed integer.
+    * `tf.int64`: 64-bit signed integer.
+    * `tf.bool`: Boolean.
+    * `tf.string`: String.
+    * `tf.qint8`: Quantized 8-bit signed integer.
+    * `tf.quint8`: Quantized 8-bit unsigned integer.
+    * `tf.qint16`: Quantized 16-bit signed integer.
+    * `tf.quint16`: Quantized 16-bit unsigned integer.
+    * `tf.qint32`: Quantized 32-bit signed integer.
+    * `tf.resource`: Handle to a mutable resource.
+    * `tf.variant`: Values of arbitrary types.
+
+    In addition, variants of these types with the `_ref` suffix are
+    defined for reference-typed tensors.
+
+    The `tf.as_dtype()` function converts numpy types and string type
+    names to a `DType` object.
+    """
+
+    def __init__(self, type_enum):
+        """Creates a new `DataType`.
+
+        NOTE(mrry): In normal circumstances, you should not need to
+        construct a `DataType` object directly. Instead, use the
+        `tf.as_dtype()` function.
+
+        Args:
+          type_enum: A `types_pb2.DataType` enum value.
+
+        Raises:
+          TypeError: If `type_enum` is not a value `types_pb2.DataType`.
+        """
+        # TODO(mrry): Make the necessary changes (using __new__) to ensure
+        # that calling this returns one of the interned values.
+        type_enum = int(type_enum)
+        if (
+            type_enum not in types_pb2.DataType.values()
+            or type_enum == types_pb2.DT_INVALID
+        ):
+            raise TypeError(
+                "type_enum is not a valid types_pb2.DataType: %s" % type_enum
+            )
+        self._type_enum = type_enum
+
+    @property
+    def _is_ref_dtype(self):
+        """Returns `True` if this `DType` represents a reference type."""
+        return self._type_enum > 100
+
+    @property
+    def _as_ref(self):
+        """Returns a reference `DType` based on this `DType`."""
+        if self._is_ref_dtype:
+            return self
+        else:
+            return _INTERN_TABLE[self._type_enum + 100]
+
+    @property
+    def base_dtype(self):
+        """Returns a non-reference `DType` based on this `DType`."""
+        if self._is_ref_dtype:
+            return _INTERN_TABLE[self._type_enum - 100]
+        else:
+            return self
+
+    @property
+    def real_dtype(self):
+        """Returns the dtype correspond to this dtype's real part."""
+        base = self.base_dtype
+        if base == complex64:
+            return float32
+        elif base == complex128:
+            return float64
+        else:
+            return self
+
+    @property
+    def is_numpy_compatible(self):
+        return self._type_enum not in _NUMPY_INCOMPATIBLE
+
+    @property
+    def as_numpy_dtype(self):
+        """Returns a `numpy.dtype` based on this `DType`."""
+        return _TF_TO_NP[self._type_enum]
+
+    @property
+    def as_datatype_enum(self):
+        """Returns a `types_pb2.DataType` enum value based on this `DType`."""
+        return self._type_enum
+
+    @property
+    def is_bool(self):
+        """Returns whether this is a boolean data type."""
+        return self.base_dtype == bool
+
+    @property
+    def is_integer(self):
+        """Returns whether this is a (non-quantized) integer type."""
+        return (
+            self.is_numpy_compatible
+            and not self.is_quantized
+            and np.issubdtype(self.as_numpy_dtype, np.integer)
+        )
+
+    @property
+    def is_floating(self):
+        """Returns whether this is a (non-quantized, real) floating point
+        type."""
+        return (
+            self.is_numpy_compatible
+            and np.issubdtype(self.as_numpy_dtype, np.floating)
+        ) or self.base_dtype == bfloat16
+
+    @property
+    def is_complex(self):
+        """Returns whether this is a complex floating point type."""
+        return self.base_dtype in (complex64, complex128)
+
+    @property
+    def is_quantized(self):
+        """Returns whether this is a quantized data type."""
+        return self.base_dtype in _QUANTIZED_DTYPES_NO_REF
+
+    @property
+    def is_unsigned(self):
+        """Returns whether this type is unsigned.
+
+        Non-numeric, unordered, and quantized types are not considered unsigned, and
+        this function returns `False`.
+
+        Returns:
+          Whether a `DType` is unsigned.
+        """
+        try:
+            return self.min == 0
+        except TypeError:
+            return False
+
+    @property
+    def min(self):
+        """Returns the minimum representable value in this data type.
+
+        Raises:
+          TypeError: if this is a non-numeric, unordered, or quantized type.
+        """
+        if self.is_quantized or self.base_dtype in (
+            bool,
+            string,
+            complex64,
+            complex128,
+        ):
+            raise TypeError("Cannot find minimum value of %s." % self)
+
+        # there is no simple way to get the min value of a dtype, we have to check
+        # float and int types separately
+        try:
+            return np.finfo(self.as_numpy_dtype).min
+        except:  # bare except as possible raises by finfo not documented
+            try:
+                return np.iinfo(self.as_numpy_dtype).min
+            except:
+                if self.base_dtype == bfloat16:
+                    return _np_bfloat16(float.fromhex("-0x1.FEp127"))
+                raise TypeError("Cannot find minimum value of %s." % self)
+
+    @property
+    def max(self):
+        """Returns the maximum representable value in this data type.
+
+        Raises:
+          TypeError: if this is a non-numeric, unordered, or quantized type.
+        """
+        if self.is_quantized or self.base_dtype in (
+            bool,
+            string,
+            complex64,
+            complex128,
+        ):
+            raise TypeError("Cannot find maximum value of %s." % self)
+
+        # there is no simple way to get the max value of a dtype, we have to check
+        # float and int types separately
+        try:
+            return np.finfo(self.as_numpy_dtype).max
+        except:  # bare except as possible raises by finfo not documented
+            try:
+                return np.iinfo(self.as_numpy_dtype).max
+            except:
+                if self.base_dtype == bfloat16:
+                    return _np_bfloat16(float.fromhex("0x1.FEp127"))
+                raise TypeError("Cannot find maximum value of %s." % self)
+
+    @property
+    def limits(self, clip_negative=True):
+        """Return intensity limits, i.e. (min, max) tuple, of the dtype.
+
+        Args:
+          clip_negative : bool, optional
+              If True, clip the negative range (i.e. return 0 for min intensity)
+              even if the image dtype allows negative values.
+        Returns
+          min, max : tuple
+            Lower and upper intensity limits.
+        """
+        min, max = dtype_range[
+            self.as_numpy_dtype
+        ]  # pylint: disable=redefined-builtin
+        if clip_negative:
+            min = 0  # pylint: disable=redefined-builtin
+        return min, max
+
+    def is_compatible_with(self, other):
+        """Returns True if the `other` DType will be converted to this DType.
+
+        The conversion rules are as follows:
+
+        ```python
+        DType(T)       .is_compatible_with(DType(T))        == True
+        DType(T)       .is_compatible_with(DType(T).as_ref) == True
+        DType(T).as_ref.is_compatible_with(DType(T))        == False
+        DType(T).as_ref.is_compatible_with(DType(T).as_ref) == True
+        ```
+
+        Args:
+          other: A `DType` (or object that may be converted to a `DType`).
+
+        Returns:
+          True if a Tensor of the `other` `DType` will be implicitly converted to
+          this `DType`.
+        """
+        other = as_dtype(other)
+        return self._type_enum in (
+            other.as_datatype_enum,
+            other.base_dtype.as_datatype_enum,
+        )
+
+    def __eq__(self, other):
+        """Returns True iff this DType refers to the same type as `other`."""
+        if other is None:
+            return False
+        try:
+            dtype = as_dtype(other).as_datatype_enum
+            return self._type_enum == dtype  # pylint: disable=protected-access
+        except TypeError:
+            return False
+
+    def __ne__(self, other):
+        """Returns True iff self != other."""
+        return not self.__eq__(other)
+
+    @property
+    def name(self):
+        """Returns the string name for this `DType`."""
+        return _TYPE_TO_STRING[self._type_enum]
+
+    def __int__(self):
+        return self._type_enum
+
+    def __str__(self):
+        return "<dtype: %r>" % self.name
+
+    def __repr__(self):
+        return "tf." + self.name
+
+    def __hash__(self):
+        return self._type_enum
+
+    def __reduce__(self):
+        return as_dtype, (self.name,)
+
+    @property
+    def size(self):
+        if (
+            self._type_enum == types_pb2.DT_VARIANT
+            or self._type_enum == types_pb2.DT_RESOURCE
+        ):
+            return 1
+        return np.dtype(self.as_numpy_dtype).itemsize
+
+
+# Define data type range of numpy dtype
+dtype_range = {
+    np.bool_: (False, True),
+    np.uint8: (0, 255),
+    np.uint16: (0, 65535),
+    np.int8: (-128, 127),
+    np.int16: (-32768, 32767),
+    np.int64: (-(2**63), 2**63 - 1),
+    np.uint64: (0, 2**64 - 1),
+    np.int32: (-(2**31), 2**31 - 1),
+    np.uint32: (0, 2**32 - 1),
+    np.float32: (-1, 1),
+    np.float64: (-1, 1),
+}
+
+# Define standard wrappers for the types_pb2.DataType enum.
+resource = DType(types_pb2.DT_RESOURCE)
+# tf_export("resource").export_constant(__name__, "resource")
+variant = DType(types_pb2.DT_VARIANT)
+# tf_export("variant").export_constant(__name__, "variant")
+float16 = DType(types_pb2.DT_HALF)
+# tf_export("float16").export_constant(__name__, "float16")
+half = float16
+# tf_export("half").export_constant(__name__, "half")
+float32 = DType(types_pb2.DT_FLOAT)
+# tf_export("float32").export_constant(__name__, "float32")
+float64 = DType(types_pb2.DT_DOUBLE)
+# tf_export("float64").export_constant(__name__, "float64")
+double = float64
+# tf_export("double").export_constant(__name__, "double")
+int32 = DType(types_pb2.DT_INT32)
+# tf_export("int32").export_constant(__name__, "int32")
+uint8 = DType(types_pb2.DT_UINT8)
+# tf_export("uint8").export_constant(__name__, "uint8")
+uint16 = DType(types_pb2.DT_UINT16)
+# tf_export("uint16").export_constant(__name__, "uint16")
+uint32 = DType(types_pb2.DT_UINT32)
+# tf_export("uint32").export_constant(__name__, "uint32")
+uint64 = DType(types_pb2.DT_UINT64)
+# tf_export("uint64").export_constant(__name__, "uint64")
+int16 = DType(types_pb2.DT_INT16)
+# tf_export("int16").export_constant(__name__, "int16")
+int8 = DType(types_pb2.DT_INT8)
+# tf_export("int8").export_constant(__name__, "int8")
+string = DType(types_pb2.DT_STRING)
+# tf_export("string").export_constant(__name__, "string")
+complex64 = DType(types_pb2.DT_COMPLEX64)
+# tf_export("complex64").export_constant(__name__, "complex64")
+complex128 = DType(types_pb2.DT_COMPLEX128)
+# tf_export("complex128").export_constant(__name__, "complex128")
+int64 = DType(types_pb2.DT_INT64)
+# tf_export("int64").export_constant(__name__, "int64")
+bool = DType(types_pb2.DT_BOOL)  # pylint: disable=redefined-builtin
+# tf_export("bool").export_constant(__name__, "bool")
+qint8 = DType(types_pb2.DT_QINT8)
+# tf_export("qint8").export_constant(__name__, "qint8")
+quint8 = DType(types_pb2.DT_QUINT8)
+# tf_export("quint8").export_constant(__name__, "quint8")
+qint16 = DType(types_pb2.DT_QINT16)
+# tf_export("qint16").export_constant(__name__, "qint16")
+quint16 = DType(types_pb2.DT_QUINT16)
+# tf_export("quint16").export_constant(__name__, "quint16")
+qint32 = DType(types_pb2.DT_QINT32)
+# tf_export("qint32").export_constant(__name__, "qint32")
+resource_ref = DType(types_pb2.DT_RESOURCE_REF)
+variant_ref = DType(types_pb2.DT_VARIANT_REF)
+bfloat16 = DType(types_pb2.DT_BFLOAT16)
+# tf_export("bfloat16").export_constant(__name__, "bfloat16")
+float16_ref = DType(types_pb2.DT_HALF_REF)
+half_ref = float16_ref
+float32_ref = DType(types_pb2.DT_FLOAT_REF)
+float64_ref = DType(types_pb2.DT_DOUBLE_REF)
+double_ref = float64_ref
+int32_ref = DType(types_pb2.DT_INT32_REF)
+uint32_ref = DType(types_pb2.DT_UINT32_REF)
+uint8_ref = DType(types_pb2.DT_UINT8_REF)
+uint16_ref = DType(types_pb2.DT_UINT16_REF)
+int16_ref = DType(types_pb2.DT_INT16_REF)
+int8_ref = DType(types_pb2.DT_INT8_REF)
+string_ref = DType(types_pb2.DT_STRING_REF)
+complex64_ref = DType(types_pb2.DT_COMPLEX64_REF)
+complex128_ref = DType(types_pb2.DT_COMPLEX128_REF)
+int64_ref = DType(types_pb2.DT_INT64_REF)
+uint64_ref = DType(types_pb2.DT_UINT64_REF)
+bool_ref = DType(types_pb2.DT_BOOL_REF)
+qint8_ref = DType(types_pb2.DT_QINT8_REF)
+quint8_ref = DType(types_pb2.DT_QUINT8_REF)
+qint16_ref = DType(types_pb2.DT_QINT16_REF)
+quint16_ref = DType(types_pb2.DT_QUINT16_REF)
+qint32_ref = DType(types_pb2.DT_QINT32_REF)
+bfloat16_ref = DType(types_pb2.DT_BFLOAT16_REF)
+
+_NUMPY_INCOMPATIBLE = frozenset(
+    [
+        types_pb2.DT_VARIANT,
+        types_pb2.DT_VARIANT_REF,
+        types_pb2.DT_RESOURCE,
+        types_pb2.DT_RESOURCE_REF,
+    ]
+)
+
+# Maintain an intern table so that we don't have to create a large
+# number of small objects.
+_INTERN_TABLE = {
+    types_pb2.DT_HALF: float16,
+    types_pb2.DT_FLOAT: float32,
+    types_pb2.DT_DOUBLE: float64,
+    types_pb2.DT_INT32: int32,
+    types_pb2.DT_UINT8: uint8,
+    types_pb2.DT_UINT16: uint16,
+    types_pb2.DT_UINT32: uint32,
+    types_pb2.DT_UINT64: uint64,
+    types_pb2.DT_INT16: int16,
+    types_pb2.DT_INT8: int8,
+    types_pb2.DT_STRING: string,
+    types_pb2.DT_COMPLEX64: complex64,
+    types_pb2.DT_COMPLEX128: complex128,
+    types_pb2.DT_INT64: int64,
+    types_pb2.DT_BOOL: bool,
+    types_pb2.DT_QINT8: qint8,
+    types_pb2.DT_QUINT8: quint8,
+    types_pb2.DT_QINT16: qint16,
+    types_pb2.DT_QUINT16: quint16,
+    types_pb2.DT_QINT32: qint32,
+    types_pb2.DT_BFLOAT16: bfloat16,
+    types_pb2.DT_RESOURCE: resource,
+    types_pb2.DT_VARIANT: variant,
+    types_pb2.DT_HALF_REF: float16_ref,
+    types_pb2.DT_FLOAT_REF: float32_ref,
+    types_pb2.DT_DOUBLE_REF: float64_ref,
+    types_pb2.DT_INT32_REF: int32_ref,
+    types_pb2.DT_UINT32_REF: uint32_ref,
+    types_pb2.DT_UINT8_REF: uint8_ref,
+    types_pb2.DT_UINT16_REF: uint16_ref,
+    types_pb2.DT_INT16_REF: int16_ref,
+    types_pb2.DT_INT8_REF: int8_ref,
+    types_pb2.DT_STRING_REF: string_ref,
+    types_pb2.DT_COMPLEX64_REF: complex64_ref,
+    types_pb2.DT_COMPLEX128_REF: complex128_ref,
+    types_pb2.DT_INT64_REF: int64_ref,
+    types_pb2.DT_UINT64_REF: uint64_ref,
+    types_pb2.DT_BOOL_REF: bool_ref,
+    types_pb2.DT_QINT8_REF: qint8_ref,
+    types_pb2.DT_QUINT8_REF: quint8_ref,
+    types_pb2.DT_QINT16_REF: qint16_ref,
+    types_pb2.DT_QUINT16_REF: quint16_ref,
+    types_pb2.DT_QINT32_REF: qint32_ref,
+    types_pb2.DT_BFLOAT16_REF: bfloat16_ref,
+    types_pb2.DT_RESOURCE_REF: resource_ref,
+    types_pb2.DT_VARIANT_REF: variant_ref,
+}
+
+# Standard mappings between types_pb2.DataType values and string names.
+_TYPE_TO_STRING = {
+    types_pb2.DT_HALF: "float16",
+    types_pb2.DT_FLOAT: "float32",
+    types_pb2.DT_DOUBLE: "float64",
+    types_pb2.DT_INT32: "int32",
+    types_pb2.DT_UINT8: "uint8",
+    types_pb2.DT_UINT16: "uint16",
+    types_pb2.DT_UINT32: "uint32",
+    types_pb2.DT_UINT64: "uint64",
+    types_pb2.DT_INT16: "int16",
+    types_pb2.DT_INT8: "int8",
+    types_pb2.DT_STRING: "string",
+    types_pb2.DT_COMPLEX64: "complex64",
+    types_pb2.DT_COMPLEX128: "complex128",
+    types_pb2.DT_INT64: "int64",
+    types_pb2.DT_BOOL: "bool",
+    types_pb2.DT_QINT8: "qint8",
+    types_pb2.DT_QUINT8: "quint8",
+    types_pb2.DT_QINT16: "qint16",
+    types_pb2.DT_QUINT16: "quint16",
+    types_pb2.DT_QINT32: "qint32",
+    types_pb2.DT_BFLOAT16: "bfloat16",
+    types_pb2.DT_RESOURCE: "resource",
+    types_pb2.DT_VARIANT: "variant",
+    types_pb2.DT_HALF_REF: "float16_ref",
+    types_pb2.DT_FLOAT_REF: "float32_ref",
+    types_pb2.DT_DOUBLE_REF: "float64_ref",
+    types_pb2.DT_INT32_REF: "int32_ref",
+    types_pb2.DT_UINT32_REF: "uint32_ref",
+    types_pb2.DT_UINT8_REF: "uint8_ref",
+    types_pb2.DT_UINT16_REF: "uint16_ref",
+    types_pb2.DT_INT16_REF: "int16_ref",
+    types_pb2.DT_INT8_REF: "int8_ref",
+    types_pb2.DT_STRING_REF: "string_ref",
+    types_pb2.DT_COMPLEX64_REF: "complex64_ref",
+    types_pb2.DT_COMPLEX128_REF: "complex128_ref",
+    types_pb2.DT_INT64_REF: "int64_ref",
+    types_pb2.DT_UINT64_REF: "uint64_ref",
+    types_pb2.DT_BOOL_REF: "bool_ref",
+    types_pb2.DT_QINT8_REF: "qint8_ref",
+    types_pb2.DT_QUINT8_REF: "quint8_ref",
+    types_pb2.DT_QINT16_REF: "qint16_ref",
+    types_pb2.DT_QUINT16_REF: "quint16_ref",
+    types_pb2.DT_QINT32_REF: "qint32_ref",
+    types_pb2.DT_BFLOAT16_REF: "bfloat16_ref",
+    types_pb2.DT_RESOURCE_REF: "resource_ref",
+    types_pb2.DT_VARIANT_REF: "variant_ref",
+}
+_STRING_TO_TF = {
+    value: _INTERN_TABLE[key] for key, value in _TYPE_TO_STRING.items()
+}
+# Add non-canonical aliases.
+_STRING_TO_TF["half"] = float16
+_STRING_TO_TF["half_ref"] = float16_ref
+_STRING_TO_TF["float"] = float32
+_STRING_TO_TF["float_ref"] = float32_ref
+_STRING_TO_TF["double"] = float64
+_STRING_TO_TF["double_ref"] = float64_ref
+
+# Numpy representation for quantized dtypes.
+#
+# These are magic strings that are used in the swig wrapper to identify
+# quantized types.
+# TODO(mrry,keveman): Investigate Numpy type registration to replace this
+# hard-coding of names.
+_np_qint8 = np.dtype([("qint8", np.int8)])
+_np_quint8 = np.dtype([("quint8", np.uint8)])
+_np_qint16 = np.dtype([("qint16", np.int16)])
+_np_quint16 = np.dtype([("quint16", np.uint16)])
+_np_qint32 = np.dtype([("qint32", np.int32)])
+
+# _np_bfloat16 is defined by a module import.
+
+# Custom struct dtype for directly-fed ResourceHandles of supported type(s).
+np_resource = np.dtype([("resource", np.ubyte)])
+
+# Standard mappings between types_pb2.DataType values and numpy.dtypes.
+_NP_TO_TF = frozenset(
+    [
+        (np.float16, float16),
+        (np.float32, float32),
+        (np.float64, float64),
+        (np.int32, int32),
+        (np.int64, int64),
+        (np.uint8, uint8),
+        (np.uint16, uint16),
+        (np.uint32, uint32),
+        (np.uint64, uint64),
+        (np.int16, int16),
+        (np.int8, int8),
+        (np.complex64, complex64),
+        (np.complex128, complex128),
+        (np.object_, string),
+        (np.bool_, bool),
+        (_np_qint8, qint8),
+        (_np_quint8, quint8),
+        (_np_qint16, qint16),
+        (_np_quint16, quint16),
+        (_np_qint32, qint32),
+        # TODO(#1677): _np_bfloat16 is defined as 0. This causes `as_dtype` to
+        # error. Add below back after we fix `TF_bfloat16_type`.
+        # (_np_bfloat16, bfloat16),
+    ]
+)
+_TF_TO_NP = {
+    types_pb2.DT_HALF: np.float16,
+    types_pb2.DT_FLOAT: np.float32,
+    types_pb2.DT_DOUBLE: np.float64,
+    types_pb2.DT_INT32: np.int32,
+    types_pb2.DT_UINT8: np.uint8,
+    types_pb2.DT_UINT16: np.uint16,
+    types_pb2.DT_UINT32: np.uint32,
+    types_pb2.DT_UINT64: np.uint64,
+    types_pb2.DT_INT16: np.int16,
+    types_pb2.DT_INT8: np.int8,
+    # NOTE(touts): For strings we use np.object as it supports variable length
+    # strings.
+    types_pb2.DT_STRING: np.object_,
+    types_pb2.DT_COMPLEX64: np.complex64,
+    types_pb2.DT_COMPLEX128: np.complex128,
+    types_pb2.DT_INT64: np.int64,
+    types_pb2.DT_BOOL: np.bool_,
+    types_pb2.DT_QINT8: _np_qint8,
+    types_pb2.DT_QUINT8: _np_quint8,
+    types_pb2.DT_QINT16: _np_qint16,
+    types_pb2.DT_QUINT16: _np_quint16,
+    types_pb2.DT_QINT32: _np_qint32,
+    types_pb2.DT_BFLOAT16: _np_bfloat16,
+    # Ref types
+    types_pb2.DT_HALF_REF: np.float16,
+    types_pb2.DT_FLOAT_REF: np.float32,
+    types_pb2.DT_DOUBLE_REF: np.float64,
+    types_pb2.DT_INT32_REF: np.int32,
+    types_pb2.DT_UINT32_REF: np.uint32,
+    types_pb2.DT_UINT8_REF: np.uint8,
+    types_pb2.DT_UINT16_REF: np.uint16,
+    types_pb2.DT_INT16_REF: np.int16,
+    types_pb2.DT_INT8_REF: np.int8,
+    types_pb2.DT_STRING_REF: np.object_,
+    types_pb2.DT_COMPLEX64_REF: np.complex64,
+    types_pb2.DT_COMPLEX128_REF: np.complex128,
+    types_pb2.DT_INT64_REF: np.int64,
+    types_pb2.DT_UINT64_REF: np.uint64,
+    types_pb2.DT_BOOL_REF: np.bool_,
+    types_pb2.DT_QINT8_REF: _np_qint8,
+    types_pb2.DT_QUINT8_REF: _np_quint8,
+    types_pb2.DT_QINT16_REF: _np_qint16,
+    types_pb2.DT_QUINT16_REF: _np_quint16,
+    types_pb2.DT_QINT32_REF: _np_qint32,
+    types_pb2.DT_BFLOAT16_REF: _np_bfloat16,
+}
+
+_QUANTIZED_DTYPES_NO_REF = frozenset([qint8, quint8, qint16, quint16, qint32])
+_QUANTIZED_DTYPES_REF = frozenset(
+    [qint8_ref, quint8_ref, qint16_ref, quint16_ref, qint32_ref]
+)
+QUANTIZED_DTYPES = _QUANTIZED_DTYPES_REF.union(_QUANTIZED_DTYPES_NO_REF)
+# tf_export("QUANTIZED_DTYPES").export_constant(__name__, "QUANTIZED_DTYPES")
+
+_PYTHON_TO_TF = {float: float32, bool: bool}
+
+
+# @tf_export("as_dtype")
+def as_dtype(type_value):
+    """Converts the given `type_value` to a `DType`.
+
+    Args:
+      type_value: A value that can be converted to a `tf.DType` object. This may
+        currently be a `tf.DType` object, a [`DataType`
+        enum](https://www.tensorflow.org/code/tensorflow/core/framework/types.proto),
+        a string type name, or a `numpy.dtype`.
+
+    Returns:
+      A `DType` corresponding to `type_value`.
+
+    Raises:
+      TypeError: If `type_value` cannot be converted to a `DType`.
+    """
+    if isinstance(type_value, DType):
+        return type_value
+
+    try:
+        return _INTERN_TABLE[type_value]
+    except KeyError:
+        pass
+
+    try:
+        return _STRING_TO_TF[type_value]
+    except KeyError:
+        pass
+
+    try:
+        return _PYTHON_TO_TF[type_value]
+    except KeyError:
+        pass
+
+    if isinstance(type_value, np.dtype):
+        # The numpy dtype for strings is variable length. We can not compare
+        # dtype with a single constant (np.string does not exist) to decide
+        # dtype is a "string" type. We need to compare the dtype.type to be
+        # sure it's a string type.
+        if type_value.type == np.bytes_ or type_value.type == np.str_:
+            return string
+
+    if isinstance(type_value, (type, np.dtype)):
+        for key, val in _NP_TO_TF:
+            try:
+                if key == type_value:
+                    return val
+            except TypeError as e:
+                raise TypeError(
+                    "Cannot convert {} to a dtype. {}".format(type_value, e)
+                )
+
+    raise TypeError(
+        "Cannot convert value %r to a TensorFlow DType." % type_value
+    )

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/error_codes.py

@@ -0,0 +1,169 @@
+# Copyright 2018 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 error codes defined in tensorflow/core/lib/core/error_codes.proto
+
+# Not an error; returned on success
+OK = 0
+
+# The operation was cancelled (typically by the caller).
+CANCELLED = 1
+
+"""
+Unknown error.  An example of where this error may be returned is
+if a Status value received from another address space belongs to
+an error-space that is not known in this address space.  Also
+errors raised by APIs that do not return enough error information
+may be converted to this error.
+"""
+UNKNOWN = 2
+
+"""
+Client specified an invalid argument.  Note that this differs
+from FAILED_PRECONDITION.  INVALID_ARGUMENT indicates arguments
+that are problematic regardless of the state of the system
+(e.g., a malformed file name).
+"""
+INVALID_ARGUMENT = 3
+
+"""
+Deadline expired before operation could complete.  For operations
+that change the state of the system, this error may be returned
+even if the operation has completed successfully.  For example, a
+successful response from a server could have been delayed long
+enough for the deadline to expire.
+"""
+DEADLINE_EXCEEDED = 4
+
+"""
+Some requested entity (e.g., file or directory) was not found.
+For privacy reasons, this code *may* be returned when the client
+does not have the access right to the entity.
+"""
+NOT_FOUND = 5
+
+"""
+Some entity that we attempted to create (e.g., file or directory)
+already exists.
+"""
+ALREADY_EXISTS = 6
+
+"""
+The caller does not have permission to execute the specified
+operation.  PERMISSION_DENIED must not be used for rejections
+caused by exhausting some resource (use RESOURCE_EXHAUSTED
+instead for those errors).  PERMISSION_DENIED must not be
+used if the caller can not be identified (use UNAUTHENTICATED
+instead for those errors).
+"""
+PERMISSION_DENIED = 7
+
+"""
+Some resource has been exhausted, perhaps a per-user quota, or
+perhaps the entire file system is out of space.
+"""
+RESOURCE_EXHAUSTED = 8
+
+"""
+Operation was rejected because the system is not in a state
+required for the operation's execution.  For example, directory
+to be deleted may be non-empty, an rmdir operation is applied to
+a non-directory, etc.
+A litmus test that may help a service implementor in deciding
+between FAILED_PRECONDITION, ABORTED, and UNAVAILABLE:
+(a) Use UNAVAILABLE if the client can retry just the failing call.
+(b) Use ABORTED if the client should retry at a higher-level
+    (e.g., restarting a read-modify-write sequence).
+(c) Use FAILED_PRECONDITION if the client should not retry until
+    the system state has been explicitly fixed.  E.g., if an "rmdir"
+    fails because the directory is non-empty, FAILED_PRECONDITION
+    should be returned since the client should not retry unless
+    they have first fixed up the directory by deleting files from it.
+(d) Use FAILED_PRECONDITION if the client performs conditional
+    REST Get/Update/Delete on a resource and the resource on the
+    server does not match the condition. E.g., conflicting
+    read-modify-write on the same resource.
+"""
+FAILED_PRECONDITION = 9
+
+"""
+The operation was aborted, typically due to a concurrency issue
+like sequencer check failures, transaction aborts, etc.
+
+See litmus test above for deciding between FAILED_PRECONDITION,
+ABORTED, and UNAVAILABLE.
+"""
+ABORTED = 10
+
+"""
+Operation tried to iterate past the valid input range.  E.g., seeking or
+reading past end of file.
+
+Unlike INVALID_ARGUMENT, this error indicates a problem that may
+be fixed if the system state changes. For example, a 32-bit file
+system will generate INVALID_ARGUMENT if asked to read at an
+offset that is not in the range [0,2^32-1], but it will generate
+OUT_OF_RANGE if asked to read from an offset past the current
+file size.
+
+There is a fair bit of overlap between FAILED_PRECONDITION and
+OUT_OF_RANGE.  We recommend using OUT_OF_RANGE (the more specific
+error) when it applies so that callers who are iterating through
+a space can easily look for an OUT_OF_RANGE error to detect when
+they are done.
+"""
+OUT_OF_RANGE = 11
+
+# Operation is not implemented or not supported/enabled in this service.
+UNIMPLEMENTED = 12
+
+"""
+Internal errors.  Means some invariant expected by the underlying
+system has been broken.  If you see one of these errors,
+something is very broken.
+"""
+INTERNAL = 13
+
+"""
+The service is currently unavailable.  This is a most likely a
+transient condition and may be corrected by retrying with
+a backoff.
+
+See litmus test above for deciding between FAILED_PRECONDITION,
+ABORTED, and UNAVAILABLE.
+"""
+UNAVAILABLE = 14
+
+# Unrecoverable data loss or corruption.
+DATA_LOSS = 15
+
+"""
+The request does not have valid authentication credentials for the
+operation.
+"""
+UNAUTHENTICATED = 16
+
+"""
+An extra enum entry to prevent people from writing code that
+fails to compile when a new code is added.
+
+Nobody should ever reference this enumeration entry. In particular,
+if you write C++ code that switches on this enumeration, add a default:
+case instead of a case that mentions this enumeration entry.
+
+Nobody should rely on the value (currently 20) listed here.  It
+may change in the future.
+"""
+DO_NOT_USE_RESERVED_FOR_FUTURE_EXPANSION_USE_DEFAULT_IN_SWITCH_INSTEAD_ = 20

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/errors.py

@@ -0,0 +1,508 @@
+# Copyright 2015 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.
+# ==============================================================================
+"""Exception types for TensorFlow errors."""
+
+
+import traceback
+import warnings
+
+from . import error_codes
+
+
+# @tf_export("OpError", "errors.OpError")
+class OpError(Exception):
+    """A generic error that is raised when TensorFlow execution fails.
+
+    Whenever possible, the session will raise a more specific subclass
+    of `OpError` from the `tf.errors` module.
+    """
+
+    def __init__(self, node_def, op, message, error_code):
+        """Creates a new `OpError` indicating that a particular op failed.
+
+        Args:
+          node_def: The `node_def_pb2.NodeDef` proto representing the op that
+            failed, if known; otherwise None.
+          op: The `ops.Operation` that failed, if known; otherwise None.
+          message: The message string describing the failure.
+          error_code: The `error_codes.Code` describing the error.
+        """
+        super().__init__()
+        self._message = message
+        self._node_def = node_def
+        self._op = op
+        self._error_code = error_code
+
+    @property
+    def message(self):
+        """The error message that describes the error."""
+        return self._message
+
+    @property
+    def op(self):
+        """The operation that failed, if known.
+
+        *N.B.* If the failed op was synthesized at runtime, e.g. a `Send`
+        or `Recv` op, there will be no corresponding
+        @{tf.Operation}
+        object.  In that case, this will return `None`, and you should
+        instead use the @{tf.OpError.node_def} to
+        discover information about the op.
+
+        Returns:
+          The `Operation` that failed, or None.
+        """
+        return self._op
+
+    @property
+    def error_code(self):
+        """The integer error code that describes the error."""
+        return self._error_code
+
+    @property
+    def node_def(self):
+        """The `NodeDef` proto representing the op that failed."""
+        return self._node_def
+
+    def __str__(self):
+        if self._op is not None:
+            output = [
+                "%s\n\nCaused by op %r, defined at:\n"
+                % (self.message, self._op.name)
+            ]
+            curr_traceback_list = traceback.format_list(self._op.traceback)
+            output.extend(curr_traceback_list)
+            # pylint: disable=protected-access
+            original_op = self._op._original_op
+            # pylint: enable=protected-access
+            while original_op is not None:
+                output.append(
+                    "\n...which was originally created as op %r, defined at:\n"
+                    % (original_op.name,)
+                )
+                prev_traceback_list = curr_traceback_list
+                curr_traceback_list = traceback.format_list(
+                    original_op.traceback
+                )
+
+                # Attempt to elide large common subsequences of the subsequent
+                # stack traces.
+                #
+                # TODO(mrry): Consider computing the actual longest common subsequence.
+                is_eliding = False
+                elide_count = 0
+                last_elided_line = None
+                for line, line_in_prev in zip(
+                    curr_traceback_list, prev_traceback_list
+                ):
+                    if line == line_in_prev:
+                        if is_eliding:
+                            elide_count += 1
+                            last_elided_line = line
+                        else:
+                            output.append(line)
+                            is_eliding = True
+                            elide_count = 0
+                    else:
+                        if is_eliding:
+                            if elide_count > 0:
+                                output.extend(
+                                    [
+                                        "[elided %d identical lines from previous traceback]\n"
+                                        % (elide_count - 1,),
+                                        last_elided_line,
+                                    ]
+                                )
+                            is_eliding = False
+                        output.extend(line)
+
+                # pylint: disable=protected-access
+                original_op = original_op._original_op
+                # pylint: enable=protected-access
+            output.append(
+                "\n%s (see above for traceback): %s\n"
+                % (type(self).__name__, self.message)
+            )
+            return "".join(output)
+        else:
+            return self.message
+
+
+OK = error_codes.OK
+# tf_export("errors.OK").export_constant(__name__, "OK")
+CANCELLED = error_codes.CANCELLED
+# tf_export("errors.CANCELLED").export_constant(__name__, "CANCELLED")
+UNKNOWN = error_codes.UNKNOWN
+# tf_export("errors.UNKNOWN").export_constant(__name__, "UNKNOWN")
+INVALID_ARGUMENT = error_codes.INVALID_ARGUMENT
+# tf_export("errors.INVALID_ARGUMENT").export_constant(__name__,
+# "INVALID_ARGUMENT")
+DEADLINE_EXCEEDED = error_codes.DEADLINE_EXCEEDED
+# tf_export("errors.DEADLINE_EXCEEDED").export_constant(__name__,
+# "DEADLINE_EXCEEDED")
+NOT_FOUND = error_codes.NOT_FOUND
+# tf_export("errors.NOT_FOUND").export_constant(__name__, "NOT_FOUND")
+ALREADY_EXISTS = error_codes.ALREADY_EXISTS
+# tf_export("errors.ALREADY_EXISTS").export_constant(__name__, "ALREADY_EXISTS")
+PERMISSION_DENIED = error_codes.PERMISSION_DENIED
+# tf_export("errors.PERMISSION_DENIED").export_constant(__name__,
+# "PERMISSION_DENIED")
+UNAUTHENTICATED = error_codes.UNAUTHENTICATED
+# tf_export("errors.UNAUTHENTICATED").export_constant(__name__, "UNAUTHENTICATED")
+RESOURCE_EXHAUSTED = error_codes.RESOURCE_EXHAUSTED
+# tf_export("errors.RESOURCE_EXHAUSTED").export_constant(__name__,
+# "RESOURCE_EXHAUSTED")
+FAILED_PRECONDITION = error_codes.FAILED_PRECONDITION
+# tf_export("errors.FAILED_PRECONDITION").export_constant(__name__,
+# "FAILED_PRECONDITION")
+ABORTED = error_codes.ABORTED
+# tf_export("errors.ABORTED").export_constant(__name__, "ABORTED")
+OUT_OF_RANGE = error_codes.OUT_OF_RANGE
+# tf_export("errors.OUT_OF_RANGE").export_constant(__name__, "OUT_OF_RANGE")
+UNIMPLEMENTED = error_codes.UNIMPLEMENTED
+# tf_export("errors.UNIMPLEMENTED").export_constant(__name__, "UNIMPLEMENTED")
+INTERNAL = error_codes.INTERNAL
+# tf_export("errors.INTERNAL").export_constant(__name__, "INTERNAL")
+UNAVAILABLE = error_codes.UNAVAILABLE
+# tf_export("errors.UNAVAILABLE").export_constant(__name__, "UNAVAILABLE")
+DATA_LOSS = error_codes.DATA_LOSS
+# tf_export("errors.DATA_LOSS").export_constant(__name__, "DATA_LOSS")
+
+
+# @tf_export("errors.CancelledError")
+class CancelledError(OpError):
+    """Raised when an operation or step is cancelled.
+
+    For example, a long-running operation (e.g.
+    @{tf.QueueBase.enqueue} may be
+    cancelled by running another operation (e.g.
+    @{tf.QueueBase.close},
+    or by @{tf.Session.close}.
+    A step that is running such a long-running operation will fail by raising
+    `CancelledError`.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `CancelledError`."""
+        super().__init__(node_def, op, message, CANCELLED)
+
+
+# @tf_export("errors.UnknownError")
+class UnknownError(OpError):
+    """Unknown error.
+
+    An example of where this error may be returned is if a Status value
+    received from another address space belongs to an error-space that
+    is not known to this address space. Also errors raised by APIs that
+    do not return enough error information may be converted to this
+    error.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message, error_code=UNKNOWN):
+        """Creates an `UnknownError`."""
+        super().__init__(node_def, op, message, error_code)
+
+
+# @tf_export("errors.InvalidArgumentError")
+class InvalidArgumentError(OpError):
+    """Raised when an operation receives an invalid argument.
+
+    This may occur, for example, if an operation is receives an input
+    tensor that has an invalid value or shape. For example, the
+    @{tf.matmul} op will raise this
+    error if it receives an input that is not a matrix, and the
+    @{tf.reshape} op will raise
+    this error if the new shape does not match the number of elements in the input
+    tensor.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `InvalidArgumentError`."""
+        super().__init__(node_def, op, message, INVALID_ARGUMENT)
+
+
+# @tf_export("errors.DeadlineExceededError")
+class DeadlineExceededError(OpError):
+    """Raised when a deadline expires before an operation could complete.
+
+    This exception is not currently used.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `DeadlineExceededError`."""
+        super().__init__(node_def, op, message, DEADLINE_EXCEEDED)
+
+
+# @tf_export("errors.NotFoundError")
+class NotFoundError(OpError):
+    """Raised when a requested entity (e.g., a file or directory) was not
+    found.
+
+    For example, running the
+    @{tf.WholeFileReader.read}
+    operation could raise `NotFoundError` if it receives the name of a file that
+    does not exist.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `NotFoundError`."""
+        super().__init__(node_def, op, message, NOT_FOUND)
+
+
+# @tf_export("errors.AlreadyExistsError")
+class AlreadyExistsError(OpError):
+    """Raised when an entity that we attempted to create already exists.
+
+    For example, running an operation that saves a file
+    (e.g. @{tf.train.Saver.save})
+    could potentially raise this exception if an explicit filename for an
+    existing file was passed.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `AlreadyExistsError`."""
+        super().__init__(node_def, op, message, ALREADY_EXISTS)
+
+
+# @tf_export("errors.PermissionDeniedError")
+class PermissionDeniedError(OpError):
+    """Raised when the caller does not have permission to run an operation.
+
+    For example, running the
+    @{tf.WholeFileReader.read}
+    operation could raise `PermissionDeniedError` if it receives the name of a
+    file for which the user does not have the read file permission.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `PermissionDeniedError`."""
+        super().__init__(node_def, op, message, PERMISSION_DENIED)
+
+
+# @tf_export("errors.UnauthenticatedError")
+class UnauthenticatedError(OpError):
+    """The request does not have valid authentication credentials.
+
+    This exception is not currently used.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `UnauthenticatedError`."""
+        super().__init__(node_def, op, message, UNAUTHENTICATED)
+
+
+# @tf_export("errors.ResourceExhaustedError")
+class ResourceExhaustedError(OpError):
+    """Some resource has been exhausted.
+
+    For example, this error might be raised if a per-user quota is
+    exhausted, or perhaps the entire file system is out of space.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `ResourceExhaustedError`."""
+        super().__init__(node_def, op, message, RESOURCE_EXHAUSTED)
+
+
+# @tf_export("errors.FailedPreconditionError")
+class FailedPreconditionError(OpError):
+    """Operation was rejected because the system is not in a state to execute
+    it.
+
+    This exception is most commonly raised when running an operation
+    that reads a @{tf.Variable}
+    before it has been initialized.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `FailedPreconditionError`."""
+        super().__init__(node_def, op, message, FAILED_PRECONDITION)
+
+
+# @tf_export("errors.AbortedError")
+class AbortedError(OpError):
+    """The operation was aborted, typically due to a concurrent action.
+
+    For example, running a
+    @{tf.QueueBase.enqueue}
+    operation may raise `AbortedError` if a
+    @{tf.QueueBase.close} operation
+    previously ran.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `AbortedError`."""
+        super().__init__(node_def, op, message, ABORTED)
+
+
+# @tf_export("errors.OutOfRangeError")
+class OutOfRangeError(OpError):
+    """Raised when an operation iterates past the valid input range.
+
+    This exception is raised in "end-of-file" conditions, such as when a
+    @{tf.QueueBase.dequeue}
+    operation is blocked on an empty queue, and a
+    @{tf.QueueBase.close}
+    operation executes.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `OutOfRangeError`."""
+        super().__init__(node_def, op, message, OUT_OF_RANGE)
+
+
+# @tf_export("errors.UnimplementedError")
+class UnimplementedError(OpError):
+    """Raised when an operation has not been implemented.
+
+    Some operations may raise this error when passed otherwise-valid
+    arguments that it does not currently support. For example, running
+    the @{tf.nn.max_pool} operation
+    would raise this error if pooling was requested on the batch dimension,
+    because this is not yet supported.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `UnimplementedError`."""
+        super().__init__(node_def, op, message, UNIMPLEMENTED)
+
+
+# @tf_export("errors.InternalError")
+class InternalError(OpError):
+    """Raised when the system experiences an internal error.
+
+    This exception is raised when some invariant expected by the runtime
+    has been broken. Catching this exception is not recommended.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `InternalError`."""
+        super().__init__(node_def, op, message, INTERNAL)
+
+
+# @tf_export("errors.UnavailableError")
+class UnavailableError(OpError):
+    """Raised when the runtime is currently unavailable.
+
+    This exception is not currently used.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates an `UnavailableError`."""
+        super().__init__(node_def, op, message, UNAVAILABLE)
+
+
+# @tf_export("errors.DataLossError")
+class DataLossError(OpError):
+    """Raised when unrecoverable data loss or corruption is encountered.
+
+    For example, this may be raised by running a
+    @{tf.WholeFileReader.read}
+    operation, if the file is truncated while it is being read.
+
+    @@__init__
+    """
+
+    def __init__(self, node_def, op, message):
+        """Creates a `DataLossError`."""
+        super().__init__(node_def, op, message, DATA_LOSS)
+
+
+_CODE_TO_EXCEPTION_CLASS = {
+    CANCELLED: CancelledError,
+    UNKNOWN: UnknownError,
+    INVALID_ARGUMENT: InvalidArgumentError,
+    DEADLINE_EXCEEDED: DeadlineExceededError,
+    NOT_FOUND: NotFoundError,
+    ALREADY_EXISTS: AlreadyExistsError,
+    PERMISSION_DENIED: PermissionDeniedError,
+    UNAUTHENTICATED: UnauthenticatedError,
+    RESOURCE_EXHAUSTED: ResourceExhaustedError,
+    FAILED_PRECONDITION: FailedPreconditionError,
+    ABORTED: AbortedError,
+    OUT_OF_RANGE: OutOfRangeError,
+    UNIMPLEMENTED: UnimplementedError,
+    INTERNAL: InternalError,
+    UNAVAILABLE: UnavailableError,
+    DATA_LOSS: DataLossError,
+}
+
+_EXCEPTION_CLASS_TO_CODE = dict(
+    ((class_, code) for (code, class_) in _CODE_TO_EXCEPTION_CLASS.items())
+)
+
+
+# @tf_export("errors.exception_type_from_error_code")
+def exception_type_from_error_code(error_code):
+    return _CODE_TO_EXCEPTION_CLASS[error_code]
+
+
+# @tf_export("errors.error_code_from_exception_type")
+def error_code_from_exception_type(cls):
+    return _EXCEPTION_CLASS_TO_CODE[cls]
+
+
+def _make_specific_exception(node_def, op, message, error_code):
+    try:
+        exc_type = exception_type_from_error_code(error_code)
+        return exc_type(node_def, op, message)
+    except KeyError:
+        warnings.warn("Unknown error code: %d" % error_code)
+        return UnknownError(node_def, op, message, error_code)
+
+
+# Named like a function for backwards compatibility with the
+# @tf_contextlib.contextmanager version, which was switched to a class to avoid
+# some object creation overhead.
+# TODO(b/77295559): expand use of TF_Status* SWIG typemap and deprecate this.
+# @tf_export("errors.raise_exception_on_not_ok_status")  # pylint: disable=invalid-name
+class raise_exception_on_not_ok_status:
+    """Context manager to check for C API status."""
+
+    def __enter__(self):
+        return "Status not OK"
+
+    def __exit__(self, type_arg, value_arg, traceback_arg):
+        return False  # False values do not suppress exceptions

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/flags.py

@@ -0,0 +1,125 @@
+# Copyright 2015 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.
+# ==============================================================================
+
+"""Import router for absl.flags.
+
+See https://github.com/abseil/abseil-py.
+"""
+
+import logging as _logging
+import sys as _sys
+
+# go/tf-wildcard-import
+from absl.flags import *  # pylint: disable=wildcard-import
+
+
+# Since we wrap absl.flags DEFINE functions, we need to declare this module
+# does not affect key flags.
+disclaim_key_flags()  # pylint: disable=undefined-variable
+
+
+_RENAMED_ARGUMENTS = {
+    "flag_name": "name",
+    "default_value": "default",
+    "docstring": "help",
+}
+
+
+def _wrap_define_function(original_function):
+    """Wraps absl.flags's define functions so tf.flags accepts old names."""
+
+    def wrapper(*args, **kwargs):
+        """Wrapper function that turns old keyword names to new ones."""
+        has_old_names = False
+        for old_name, new_name in __RENAMED_ARGUMENTS.items():
+            if old_name in kwargs:
+                has_old_names = True
+                value = kwargs.pop(old_name)
+                kwargs[new_name] = value
+        if has_old_names:
+            _logging.warning(
+                "Use of the keyword argument names (flag_name, default_value, "
+                "docstring) is deprecated, please use (name, default, help) instead."
+            )
+        return original_function(*args, **kwargs)
+
+    return wrapper
+
+
+class _FlagValuesWrapper:
+    """Wrapper class for absl.flags.FLAGS.
+
+    The difference is that tf.compat.v1.flags.FLAGS implicitly parses
+    flags with sys.argv when accessing the FLAGS values before it's
+    explicitly parsed, while absl.flags.FLAGS raises an exception.
+    """
+
+    def __init__(self, flags_object):
+        self.__dict__["__wrapped"] = flags_object
+
+    def __getattribute__(self, name):
+        if name == "__dict__":
+            return super().__getattribute__(name)
+        elif name == "__class__":
+            return super.__class__
+        return self.__dict__["__wrapped"].__getattribute__(name)
+
+    def __getattr__(self, name):
+        wrapped = self.__dict__["__wrapped"]
+        # To maintain backwards compatibility, implicitly parse flags when reading
+        # a flag.
+        if not wrapped.is_parsed():
+            wrapped(_sys.argv)
+        return wrapped.__getattr__(name)
+
+    def __setattr__(self, name, value):
+        return self.__dict__["__wrapped"].__setattr__(name, value)
+
+    def __delattr__(self, name):
+        return self.__dict__["__wrapped"].__delattr__(name)
+
+    def __dir__(self):
+        return self.__dict__["__wrapped"].__dir__()
+
+    def __getitem__(self, name):
+        return self.__dict__["__wrapped"].__getitem__(name)
+
+    def __setitem__(self, name, flag):
+        return self.__dict__["__wrapped"].__setitem__(name, flag)
+
+    def __len__(self):
+        return self.__dict__["__wrapped"].__len__()
+
+    def __iter__(self):
+        return self.__dict__["__wrapped"].__iter__()
+
+    def __str__(self):
+        return self.__dict__["__wrapped"].__str__()
+
+    def __call__(self, *args, **kwargs):
+        return self.__dict__["__wrapped"].__call__(*args, **kwargs)
+
+
+# pylint: disable=invalid-name,used-before-assignment
+# absl.flags APIs use `default` as the name of the default value argument.
+# Allow the following functions continue to accept `default_value`.
+DEFINE_string = _wrap_define_function(DEFINE_string)
+DEFINE_boolean = _wrap_define_function(DEFINE_boolean)
+DEFINE_bool = DEFINE_boolean
+DEFINE_float = _wrap_define_function(DEFINE_float)
+DEFINE_integer = _wrap_define_function(DEFINE_integer)
+# pylint: enable=invalid-name,used-before-assignment
+
+FLAGS = _FlagValuesWrapper(FLAGS)  # pylint: disable=used-before-assignment

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/io/__init__.py

@@ -0,0 +1,17 @@
+# Copyright 2018 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.
+# ==============================================================================
+
+
+from . import gfile  # noqa

rl/Lib/site-packages/tensorboard/compat/tensorflow_stub/pywrap_tensorflow.py

@@ -0,0 +1,287 @@
+# 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.
+# =============================================================================
+"""A wrapper for TensorFlow SWIG-generated bindings."""
+
+
+import array
+import struct
+
+from . import errors
+from .io import gfile
+
+
+TFE_DEVICE_PLACEMENT_WARN = 0
+TFE_DEVICE_PLACEMENT_SILENT_FOR_INT32 = 0
+TFE_DEVICE_PLACEMENT_SILENT = 0
+TFE_DEVICE_PLACEMENT_EXPLICIT = 0
+
+
+def __getattr__(attr):
+    return 0
+
+
+def TF_bfloat16_type():
+    return 0
+
+
+def masked_crc32c(data):
+    x = u32(crc32c(data))
+    return u32(((x >> 15) | u32(x << 17)) + 0xA282EAD8)
+
+
+def u32(x):
+    return x & 0xFFFFFFFF
+
+
+# fmt: off
+CRC_TABLE = (
+    0x00000000, 0xF26B8303, 0xE13B70F7, 0x1350F3F4,
+    0xC79A971F, 0x35F1141C, 0x26A1E7E8, 0xD4CA64EB,
+    0x8AD958CF, 0x78B2DBCC, 0x6BE22838, 0x9989AB3B,
+    0x4D43CFD0, 0xBF284CD3, 0xAC78BF27, 0x5E133C24,
+    0x105EC76F, 0xE235446C, 0xF165B798, 0x030E349B,
+    0xD7C45070, 0x25AFD373, 0x36FF2087, 0xC494A384,
+    0x9A879FA0, 0x68EC1CA3, 0x7BBCEF57, 0x89D76C54,
+    0x5D1D08BF, 0xAF768BBC, 0xBC267848, 0x4E4DFB4B,
+    0x20BD8EDE, 0xD2D60DDD, 0xC186FE29, 0x33ED7D2A,
+    0xE72719C1, 0x154C9AC2, 0x061C6936, 0xF477EA35,
+    0xAA64D611, 0x580F5512, 0x4B5FA6E6, 0xB93425E5,
+    0x6DFE410E, 0x9F95C20D, 0x8CC531F9, 0x7EAEB2FA,
+    0x30E349B1, 0xC288CAB2, 0xD1D83946, 0x23B3BA45,
+    0xF779DEAE, 0x05125DAD, 0x1642AE59, 0xE4292D5A,
+    0xBA3A117E, 0x4851927D, 0x5B016189, 0xA96AE28A,
+    0x7DA08661, 0x8FCB0562, 0x9C9BF696, 0x6EF07595,
+    0x417B1DBC, 0xB3109EBF, 0xA0406D4B, 0x522BEE48,
+    0x86E18AA3, 0x748A09A0, 0x67DAFA54, 0x95B17957,
+    0xCBA24573, 0x39C9C670, 0x2A993584, 0xD8F2B687,
+    0x0C38D26C, 0xFE53516F, 0xED03A29B, 0x1F682198,
+    0x5125DAD3, 0xA34E59D0, 0xB01EAA24, 0x42752927,
+    0x96BF4DCC, 0x64D4CECF, 0x77843D3B, 0x85EFBE38,
+    0xDBFC821C, 0x2997011F, 0x3AC7F2EB, 0xC8AC71E8,
+    0x1C661503, 0xEE0D9600, 0xFD5D65F4, 0x0F36E6F7,
+    0x61C69362, 0x93AD1061, 0x80FDE395, 0x72966096,
+    0xA65C047D, 0x5437877E, 0x4767748A, 0xB50CF789,
+    0xEB1FCBAD, 0x197448AE, 0x0A24BB5A, 0xF84F3859,
+    0x2C855CB2, 0xDEEEDFB1, 0xCDBE2C45, 0x3FD5AF46,
+    0x7198540D, 0x83F3D70E, 0x90A324FA, 0x62C8A7F9,
+    0xB602C312, 0x44694011, 0x5739B3E5, 0xA55230E6,
+    0xFB410CC2, 0x092A8FC1, 0x1A7A7C35, 0xE811FF36,
+    0x3CDB9BDD, 0xCEB018DE, 0xDDE0EB2A, 0x2F8B6829,
+    0x82F63B78, 0x709DB87B, 0x63CD4B8F, 0x91A6C88C,
+    0x456CAC67, 0xB7072F64, 0xA457DC90, 0x563C5F93,
+    0x082F63B7, 0xFA44E0B4, 0xE9141340, 0x1B7F9043,
+    0xCFB5F4A8, 0x3DDE77AB, 0x2E8E845F, 0xDCE5075C,
+    0x92A8FC17, 0x60C37F14, 0x73938CE0, 0x81F80FE3,
+    0x55326B08, 0xA759E80B, 0xB4091BFF, 0x466298FC,
+    0x1871A4D8, 0xEA1A27DB, 0xF94AD42F, 0x0B21572C,
+    0xDFEB33C7, 0x2D80B0C4, 0x3ED04330, 0xCCBBC033,
+    0xA24BB5A6, 0x502036A5, 0x4370C551, 0xB11B4652,
+    0x65D122B9, 0x97BAA1BA, 0x84EA524E, 0x7681D14D,
+    0x2892ED69, 0xDAF96E6A, 0xC9A99D9E, 0x3BC21E9D,
+    0xEF087A76, 0x1D63F975, 0x0E330A81, 0xFC588982,
+    0xB21572C9, 0x407EF1CA, 0x532E023E, 0xA145813D,
+    0x758FE5D6, 0x87E466D5, 0x94B49521, 0x66DF1622,
+    0x38CC2A06, 0xCAA7A905, 0xD9F75AF1, 0x2B9CD9F2,
+    0xFF56BD19, 0x0D3D3E1A, 0x1E6DCDEE, 0xEC064EED,
+    0xC38D26C4, 0x31E6A5C7, 0x22B65633, 0xD0DDD530,
+    0x0417B1DB, 0xF67C32D8, 0xE52CC12C, 0x1747422F,
+    0x49547E0B, 0xBB3FFD08, 0xA86F0EFC, 0x5A048DFF,
+    0x8ECEE914, 0x7CA56A17, 0x6FF599E3, 0x9D9E1AE0,
+    0xD3D3E1AB, 0x21B862A8, 0x32E8915C, 0xC083125F,
+    0x144976B4, 0xE622F5B7, 0xF5720643, 0x07198540,
+    0x590AB964, 0xAB613A67, 0xB831C993, 0x4A5A4A90,
+    0x9E902E7B, 0x6CFBAD78, 0x7FAB5E8C, 0x8DC0DD8F,
+    0xE330A81A, 0x115B2B19, 0x020BD8ED, 0xF0605BEE,
+    0x24AA3F05, 0xD6C1BC06, 0xC5914FF2, 0x37FACCF1,
+    0x69E9F0D5, 0x9B8273D6, 0x88D28022, 0x7AB90321,
+    0xAE7367CA, 0x5C18E4C9, 0x4F48173D, 0xBD23943E,
+    0xF36E6F75, 0x0105EC76, 0x12551F82, 0xE03E9C81,
+    0x34F4F86A, 0xC69F7B69, 0xD5CF889D, 0x27A40B9E,
+    0x79B737BA, 0x8BDCB4B9, 0x988C474D, 0x6AE7C44E,
+    0xBE2DA0A5, 0x4C4623A6, 0x5F16D052, 0xAD7D5351,
+)
+# fmt: on
+
+
+CRC_INIT = 0
+
+_MASK = 0xFFFFFFFF
+
+
+def crc_update(crc, data):
+    """Update CRC-32C checksum with data.
+
+    Args:
+      crc: 32-bit checksum to update as long.
+      data: byte array, string or iterable over bytes.
+    Returns:
+      32-bit updated CRC-32C as long.
+    """
+
+    if type(data) != array.array or data.itemsize != 1:
+        buf = array.array("B", data)
+    else:
+        buf = data
+
+    crc ^= _MASK
+    for b in buf:
+        table_index = (crc ^ b) & 0xFF
+        crc = (CRC_TABLE[table_index] ^ (crc >> 8)) & _MASK
+    return crc ^ _MASK
+
+
+def crc_finalize(crc):
+    """Finalize CRC-32C checksum.
+
+    This function should be called as last step of crc calculation.
+    Args:
+      crc: 32-bit checksum as long.
+    Returns:
+      finalized 32-bit checksum as long
+    """
+    return crc & _MASK
+
+
+def crc32c(data):
+    """Compute CRC-32C checksum of the data.
+
+    Args:
+      data: byte array, string or iterable over bytes.
+    Returns:
+      32-bit CRC-32C checksum of data as long.
+    """
+    return crc_finalize(crc_update(CRC_INIT, data))
+
+
+class PyRecordReader_New:
+    def __init__(
+        self, filename=None, start_offset=0, compression_type=None, status=None
+    ):
+        if filename is None:
+            raise errors.NotFoundError(
+                None, None, "No filename provided, cannot read Events"
+            )
+        if not gfile.exists(filename):
+            raise errors.NotFoundError(
+                None,
+                None,
+                "{} does not point to valid Events file".format(filename),
+            )
+        if start_offset:
+            raise errors.UnimplementedError(
+                None, None, "start offset not supported by compat reader"
+            )
+        if compression_type:
+            # TODO: Handle gzip and zlib compressed files
+            raise errors.UnimplementedError(
+                None, None, "compression not supported by compat reader"
+            )
+        self.filename = filename
+        self.start_offset = start_offset
+        self.compression_type = compression_type
+        self.status = status
+        self.curr_event = None
+        self.file_handle = gfile.GFile(self.filename, "rb")
+        # Maintain a buffer of partially read records, so we can recover from
+        # truncated records upon a retry.
+        self._buffer = b""
+        self._buffer_pos = 0
+
+    def GetNext(self):
+        # Each new read should start at the beginning of any partial record.
+        self._buffer_pos = 0
+        # Read the header
+        self.curr_event = None
+        header_str = self._read(8)
+        if not header_str:
+            # Hit EOF so raise and exit
+            raise errors.OutOfRangeError(None, None, "No more events to read")
+        if len(header_str) < 8:
+            raise self._truncation_error("header")
+        header = struct.unpack("<Q", header_str)
+
+        # Read the crc32, which is 4 bytes, and check it against
+        # the crc32 of the header
+        crc_header_str = self._read(4)
+        if len(crc_header_str) < 4:
+            raise self._truncation_error("header crc")
+        crc_header = struct.unpack("<I", crc_header_str)
+        header_crc_calc = masked_crc32c(header_str)
+        if header_crc_calc != crc_header[0]:
+            raise errors.DataLossError(
+                None, None, "{} failed header crc32 check".format(self.filename)
+            )
+
+        # The length of the header tells us how many bytes the Event
+        # string takes
+        header_len = int(header[0])
+        event_str = self._read(header_len)
+        if len(event_str) < header_len:
+            raise self._truncation_error("data")
+
+        event_crc_calc = masked_crc32c(event_str)
+
+        # The next 4 bytes contain the crc32 of the Event string,
+        # which we check for integrity.
+        crc_event_str = self._read(4)
+        if len(crc_event_str) < 4:
+            raise self._truncation_error("data crc")
+        crc_event = struct.unpack("<I", crc_event_str)
+        if event_crc_calc != crc_event[0]:
+            raise errors.DataLossError(
+                None,
+                None,
+                "{} failed event crc32 check".format(self.filename),
+            )
+
+        # Set the current event to be read later by record() call
+        self.curr_event = event_str
+        # Clear the buffered partial record since we're done reading it.
+        self._buffer = b""
+
+    def _read(self, n):
+        """Read up to n bytes from the underlying file, with buffering.
+
+        Reads are satisfied from a buffer of previous data read starting at
+        `self._buffer_pos` until the buffer is exhausted, and then from the
+        actual underlying file. Any new data is added to the buffer, and
+        `self._buffer_pos` is advanced to the point in the buffer past all
+        data returned as part of this read.
+
+        Args:
+          n: non-negative number of bytes to read
+
+        Returns:
+          bytestring of data read, up to n bytes
+        """
+        result = self._buffer[self._buffer_pos : self._buffer_pos + n]
+        self._buffer_pos += len(result)
+        n -= len(result)
+        if n > 0:
+            new_data = self.file_handle.read(n)
+            result += new_data
+            self._buffer += new_data
+            self._buffer_pos += len(new_data)
+        return result
+
+    def _truncation_error(self, section):
+        return errors.DataLossError(
+            None,
+            None,
+            "{} has truncated record in {}".format(self.filename, section),
+        )
+
+    def record(self):
+        return self.curr_event