/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 = "proto3";

package tensorflow.serving;

import "google/protobuf/wrappers.proto";

option cc_enable_arenas = true;

// Metadata for an inference request such as the model name and version.
message ModelSpec {
  // Required servable name.
  string name = 1;

  // Optional choice of which version of the model to use.
  //
  // Expected to be left unset in the common case. Should be specified when
  // there is a strong version consistency requirement (e.g. when the model
  // signature changes across versions and requests need to be
  // version-specific).
  //
  // When left unspecified, the system will serve the best available version.
  // This is typically the latest version, though during version transitions,
  // notably when serving on a fleet of instances, may be either the previous or
  // new version.
  oneof version_choice {
    // Use this specific version number.
    google.protobuf.Int64Value version = 2;

    // Use the version associated with the given label.
    string version_label = 4;
  }

  // A named signature to evaluate. If unspecified, the default signature will
  // be used.
  string signature_name = 3;
}
