chromium/third_party/mediapipe/src/mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_generator.proto

// Copyright 2019 The MediaPipe Authors.
//
// 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.

syntax = "proto2";

package mediapipe;

import "mediapipe/framework/packet_generator.proto";
import "tensorflow/core/protobuf/config.proto";

message TensorFlowSessionFromFrozenGraphGeneratorOptions {
  extend mediapipe.PacketGeneratorOptions {
    optional TensorFlowSessionFromFrozenGraphGeneratorOptions ext = 160666123;
  }

  // Path to file containing serialized proto of type tensorflow::GraphDef.
  optional string graph_proto_path = 1;

  // To run inference with MediaPipe inputs MediaPipe streams need to be mapped
  // to TensorFlow tensors. This map defines the which streams are fed into
  // which tensors in the model. The MediaPipe tag of the stream is the map key.
  // Tags must be capitalized, matching regex [A-Z0-9_]+. Examples: "JPG_STRING"
  // and "SOFTMAX". Then, those tags can be used as the MediaPipe tags of
  // input_stream or output_stream of the TensorflowInferenceCalculator
  // consuming the packet produced by this generator. The tensor names must
  // match the tensor names in the graph that you want to feed or fetch into or
  // out of. Examples:  "DecodeJpeg/contents:0" or "softmax:0". For example, a
  // mediapipe graph can include the nodes:
  //
  // packet_generator {
  //   packet_generator: "TensorFlowSessionFromFrozenGraphGenerator"
  //   output_side_packet: "SESSION:session"
  //   options {
  //     [mediapipe.TensorFlowSessionFromFrozenGraphGeneratorOptions.ext]: {
  //       graph_proto_path: "[PATH]"
  //       tag_to_tensor_names {
  //         key: "JPG_STRING"
  //         value: "input:0"
  //       }
  //       tag_to_tensor_names {
  //         key: "SOFTMAX"
  //         value: "softmax:0"
  //       }
  //     }
  //   }
  // }
  // node {
  //   calculator: "TensorflowInferenceCalculator"
  //   input_side_packet: "SESSION:graph_with_bindings"
  //   input_stream: "JPG_STRING:jpg_string_tensor"
  //   output_stream: "SOFTMAX:softmax_tensor"
  // }
  map<string, string> tag_to_tensor_names = 2;

  // Tensorflow session config options.
  optional tensorflow.ConfigProto config = 3;

  // Graph nodes to run to initialize the model. Any output of these ops is
  // ignored.
  repeated string initialization_op_names = 4;

  // The id of the device you would prefer to execute the graph nodes on.
  // If set, all graph nodes without a previously specified device, will be set
  // to run on preferred_device_id. Example values include:
  // ["/device:GPU:0","/device:CPU:0", ...]
  // NOTE: If config.allow_soft_placement = false, and the device is not found,
  // an error will be thrown.
  optional string preferred_device_id = 5;
}