// Copyright 2019 Google LLC.

//

// Redistribution and use in source and binary forms, with or without

// modification, are permitted provided that the following conditions

// are met:

//

// 1. Redistributions of source code must retain the above copyright notice,

//    this list of conditions and the following disclaimer.

//

// 2. Redistributions in binary form must reproduce the above copyright

//    notice, this list of conditions and the following disclaimer in the

//    documentation and/or other materials provided with the distribution.

//

// 3. Neither the name of the copyright holder nor the names of its

//    contributors may be used to endorse or promote products derived from this

//    software without specific prior written permission.

//

// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"

// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE

// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE

// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE

// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR

// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF

// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS

// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN

// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)

// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE

// POSSIBILITY OF SUCH DAMAGE.

// Protocol messages for describing features for machine learning model

// training or inference.

//

// There are three base Feature types:

//   - bytes

//   - float

//   - int64

//

// A Feature contains Lists which may hold zero or more values.  These

// lists are the base values BytesList, FloatList, Int64List.

//

// Features are organized into categories by name.  The Features message

// contains the mapping from name to Feature.

//

// Example Features for a movie recommendation application:

//   feature {

//     key: "age"

//     value { float_list {

//       value: 29.0

//     }}

//   }

//   feature {

//     key: "movie"

//     value { bytes_list {

//       value: "The Shawshank Redemption"

//       value: "Fight Club"

//     }}

//   }

//   feature {

//     key: "movie_ratings"

//     value { float_list {

//       value: 9.0

//       value: 9.7

//     }}

//   }

//   feature {

//     key: "suggestion"

//     value { bytes_list {

//       value: "Inception"

//     }}

//   }

//   feature {

//     key: "suggestion_purchased"

//     value { int64_list {

//       value: 1

//     }}

//   }

//   feature {

//     key: "purchase_price"

//     value { float_list {

//       value: 9.99

//     }}

//   }

//

syntax = "proto3";

option cc_enable_arenas = true;

option java_outer_classname = "FeatureProtos";

option java_multiple_files = true;

option java_package = "org.tensorflow.example";

package tensorflow;

// Containers to hold repeated fundamental values.

message BytesList {

  repeated bytes value = 1;

}

message FloatList {

  repeated float value = 1 [packed = true];

}

message Int64List {

  repeated int64 value = 1 [packed = true];

}

// Containers for non-sequential data.

message Feature {

  // Each feature can be exactly one kind.

  oneof kind {

    BytesList bytes_list = 1;

    FloatList float_list = 2;

    Int64List int64_list = 3;

  }

};

message Features {

  // Map from feature name to feature.

  map<string, Feature> feature = 1;

};

// Containers for sequential data.

//

// A FeatureList contains lists of Features.  These may hold zero or more

// Feature values.

//

// FeatureLists are organized into categories by name.  The FeatureLists message

// contains the mapping from name to FeatureList.

//

message FeatureList {

  repeated Feature feature = 1;

};

message FeatureLists {

  // Map from feature name to feature list.

  map<string, FeatureList> feature_list = 1;

};