syntax = "proto3";

import "tensorflow/core/framework/tensor_shape.proto";
import "tensorflow/core/framework/types.proto";

package tensorflow.tfprof;

message TFProfTensorProto {
  DataType dtype = 1;
  // Flatten tensor in row-major.
  // Only one of the following array is set.
  repeated double value_double = 2;
  repeated int64 value_int64 = 3;
  repeated string value_str = 4;
}

// A node in TensorFlow graph. Used by scope/graph view.
message GraphNodeProto {
  // op name.
  string name = 1;
  // tensor value restored from checkpoint.
  TFProfTensorProto tensor_value = 15;
  // op execution time.
  // A node can be defined once but run multiple times in tf.while_loop.
  // the times sum up all different runs.
  int64 run_count = 21;
  int64 exec_micros = 2;
  int64 accelerator_exec_micros = 17;
  int64 cpu_exec_micros = 18;

  // Total requested bytes by the op.
  int64 requested_bytes = 3;
  // Number of parameters if available.
  int64 parameters = 4;
  // Number of float operations.
  int64 float_ops = 13;
  // Device the op is assigned to.
  // Since an op can fire multiple kernel calls, there can be multiple devices.
  repeated string devices = 10;

  // The following are the aggregated stats from all *accounted* children and
  // the node itself. The actual children depend on the data structure used.
  // In graph view, children are inputs recursively.
  // In scope view, children are nodes under the name scope.
  int64 total_definition_count = 23;
  int64 total_run_count = 22;
  int64 total_exec_micros = 6;
  int64 total_accelerator_exec_micros = 19;
  int64 total_cpu_exec_micros = 20;

  int64 total_requested_bytes = 7;
  int64 total_parameters = 8;
  int64 total_float_ops = 14;

  // shape information, if available.
  // TODO(xpan): Why is this repeated?
  repeated TensorShapeProto shapes = 11;

  map<int32, TensorShapeProto> input_shapes = 16;

  // Descendants of the graph. The actual descendants depend on the data
  // structure used (scope, graph).
  repeated GraphNodeProto children = 12;
}

// A node that groups multiple GraphNodeProto.
// Depending on the 'view', the semantics of the TFmultiGraphNodeProto
// is different:
// code view: A node groups all TensorFlow graph nodes created by the
//            Python code.
// op view:   A node groups all TensorFlow graph nodes that are of type
//            of the op (e.g. MatMul, Conv2D).
message MultiGraphNodeProto {
  // Name of the node.
  string name = 1;

  // code execution time.
  int64 exec_micros = 2;
  int64 accelerator_exec_micros = 12;
  int64 cpu_exec_micros = 13;

  // Total requested bytes by the code.
  int64 requested_bytes = 3;
  // Number of parameters if available.
  int64 parameters = 4;
  // Number of float operations.
  int64 float_ops = 5;

  // The following are the aggregated stats from descendants.
  // The actual descendants depend on the data structure used.
  int64 total_exec_micros = 6;
  int64 total_accelerator_exec_micros = 14;
  int64 total_cpu_exec_micros = 15;

  int64 total_requested_bytes = 7;
  int64 total_parameters = 8;
  int64 total_float_ops = 9;

  // TensorFlow graph nodes contained by the MultiGraphNodeProto.
  repeated GraphNodeProto graph_nodes = 10;
  // Descendants of the node. The actual descendants depend on the data
  // structure used.
  repeated MultiGraphNodeProto children = 11;
}

message AdviceProto {
  // checker name -> a list of reports from the checker.
  map<string, Checker> checkers = 1;
  message Checker {
    repeated string reports = 2;
  }
}
