pytorch/caffe2/proto/metanet.proto

syntax = "proto2";

import "caffe2/proto/caffe2.proto";

package caffe2;

message ModelInfo {
  optional string project = 1;
  optional string modelClass = 2;
  optional string version = 3;
  optional string predictorType = 4 [ default = "SINGLE_PREDICTOR" ];
  optional string modelId = 5;
}

message BlobsMap {
  required string key = 1;
  repeated string value = 2;
}

message NetsMap {
  required string key = 1;
  required NetDef value = 2;
}

message PlansMap {
  required string key = 1;
  required PlanDef value = 2;
}

message StringMap {
  required string key = 1;
  required string value = 2;
}

message MetaNetDef {
  repeated BlobsMap blobs = 1;
  // Text-format serialized NetDefs.
  repeated NetsMap nets = 2;
  // Info about where the model comes from. Possible use cases:
  // 1) sanity check or diagnose
  // 2) provide info for evaluation.
  optional ModelInfo modelInfo = 3;
  repeated PlansMap plans = 4;
  repeated StringMap applicationSpecificInfo = 5;
  repeated string blobsOrder = 6;
  repeated string preLoadBlobs = 7;
  optional TensorBoundShapes tensorBoundShapes = 8;
  repeated string requestOnlyEmbeddings = 9;
  optional AOTConfig aotConfig = 10;
}