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// Protocol messages for describing features for machine learning model
// training or inference.
//
// There are three base Feature types:
// - bytes
// - float
// - int64
//
// Base features are contained in Lists which may hold zero or more values.
//
// 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"
// float_list {
// value: 29.0
// }
// }
// feature {
// key: "movie"
// bytes_list {
// value: "The Shawshank Redemption"
// value: "Fight Club"
// }
// }
// feature {
// key: "movie_ratings"
// float_list {
// value: 9.0
// value: 9.7
// }
// }
// feature {
// key: "suggestion"
// bytes_list {
// value: "Inception"
// }
// }
// feature {
// key: "suggestion_purchased"
// int64_list {
// value: 1
// }
// }
// feature {
// key: "purchase_price"
// float_list {
// value: 9.99
// }
// }
syntax = "proto3";
// option cc_enable_arenas = true;
package tensorflow;
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 to hold repeated fundamental features.
message BytesList {
repeated bytes value = 1;
}
message FloatList {
repeated float value = 1 [packed=true];
}
message Int64List {
repeated int64 value = 1 [packed=true];
}
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