/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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syntax = "proto3";
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package tensorflow;
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import "tensorflow/core/framework/tensor.proto";
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import "tensorflow/core/profiler/tfprof_log.proto";
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import "tensorflow/core/protobuf/debug.proto";
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import "tensorflow/core/util/event.proto";
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// Reply message from EventListener to the client, i.e., to the source of the
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// Event protocol buffers, e.g., debug ops inserted by a debugged runtime to a
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// TensorFlow graph being executed.
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message EventReply {
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message DebugOpStateChange {
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enum State {
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STATE_UNSPECIFIED = 0;
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DISABLED = 1;
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READ_ONLY = 2;
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READ_WRITE = 3;
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}
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State state = 1;
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string node_name = 2;
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int32 output_slot = 3;
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string debug_op = 4;
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}
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repeated DebugOpStateChange debug_op_state_changes = 1;
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// New tensor value to override the current tensor value with.
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TensorProto tensor = 2;
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// TODO(cais): Make use of this field to implement overriding of tensor value
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// during debugging.
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}
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// Data on the traceback of a debugged call, e.g., a Session.run() call, or the
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// execution of an eager operation.
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message CallTraceback {
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enum CallType {
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UNSPECIFIED = 0;
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GRAPH_EXECUTION = 1;
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EAGER_EXECUTION = 2;
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}
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CallType call_type = 1;
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// A key for the call. For example, for graph execution, this is a key
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// consisting of the names of the fed and fetched tensors.
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string call_key = 2;
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// Traceback stack for the origin of the call event.
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// For graph execution, this is the stack of the Session.run() call.
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// For eager execution, this is the stack of the Python line that invokes
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// the execution of the eager op.
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tfprof.CodeDef origin_stack = 3;
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// Keeps track of the mapping from integer IDs in `origin_stack` to actual
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// string values (e.g., file paths, function names).
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map<int64, string> origin_id_to_string = 4;
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// Traceback for the graph (if any) involved in the call.
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tfprof.OpLogProto graph_traceback = 5;
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// Version of the graph in `graph_traceback` (if any).
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int64 graph_version = 6;
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}
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// EventListener: Receives Event protos, e.g., from debugged TensorFlow
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// runtime(s).
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service EventListener {
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// Client(s) can use this RPC method to send the EventListener Event protos.
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// The Event protos can hold information such as:
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// 1) intermediate tensors from a debugged graph being executed, which can
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// be sent from DebugIdentity ops configured with grpc URLs.
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// 2) GraphDefs of partition graphs, which can be sent from special debug
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// ops that get executed immediately after the beginning of the graph
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// execution.
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rpc SendEvents(stream Event) returns (stream EventReply);
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// Send the tracebacks of a TensorFlow execution call.
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rpc SendTracebacks(CallTraceback) returns (EventReply);
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// Send a collection of source code files being debugged.
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rpc SendSourceFiles(DebuggedSourceFiles) returns (EventReply);
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}
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