TensorFlow协议缓冲区示例
2018-09-27 09:22 更新
//用于描述机器学习模型功能的协议消息
//训练或推理.
//
//有三种基本的功能类型:
// - 字节
// - float
// - int64
//
//功能包含可能包含零个或多个值的列表.这些
//列表是基本值BytesList,FloatList,Int64List.
//
//功能按名称分为类别和功能消息
//包含从名称到功能的映射.
//
//以下是一个电影推荐应用程序的示例功能:
// 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;
};
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