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Diffstat (limited to 'google/cloud/ml/v1/prediction_service.proto')
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diff --git a/google/cloud/ml/v1/prediction_service.proto b/google/cloud/ml/v1/prediction_service.proto new file mode 100644 index 000000000..dba49277c --- /dev/null +++ b/google/cloud/ml/v1/prediction_service.proto @@ -0,0 +1,241 @@ +// Copyright 2017 Google Inc. +// +// Licensed 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 google.cloud.ml.v1; + +import "google/api/annotations.proto"; +import "google/api/httpbody.proto"; + +option go_package = "google.golang.org/genproto/googleapis/cloud/ml/v1;ml"; +option java_multiple_files = true; +option java_outer_classname = "PredictionServiceProto"; +option java_package = "com.google.cloud.ml.api.v1"; + +// Copyright 2017 Google Inc. All Rights Reserved. +// +// Proto file for the Google Cloud Machine Learning Engine. +// Describes the online prediction service. + +// The Prediction API, which serves predictions for models managed by +// ModelService. +service OnlinePredictionService { + // Performs prediction on the data in the request. + // + // **** REMOVE FROM GENERATED DOCUMENTATION + rpc Predict(PredictRequest) returns (google.api.HttpBody) { + option (google.api.http) = { + post: "/v1/{name=projects/**}:predict" + body: "*" + }; + } +} + +// Request for predictions to be issued against a trained model. +// +// The body of the request is a single JSON object with a single top-level +// field: +// +// <dl> +// <dt>instances</dt> +// <dd>A JSON array containing values representing the instances to use for +// prediction.</dd> +// </dl> +// +// The structure of each element of the instances list is determined by your +// model's input definition. Instances can include named inputs or can contain +// only unlabeled values. +// +// Not all data includes named inputs. Some instances will be simple +// JSON values (boolean, number, or string). However, instances are often lists +// of simple values, or complex nested lists. Here are some examples of request +// bodies: +// +// CSV data with each row encoded as a string value: +// <pre> +// {"instances": ["1.0,true,\\"x\\"", "-2.0,false,\\"y\\""]} +// </pre> +// Plain text: +// <pre> +// {"instances": ["the quick brown fox", "la bruja le dio"]} +// </pre> +// Sentences encoded as lists of words (vectors of strings): +// <pre> +// { +// "instances": [ +// ["the","quick","brown"], +// ["la","bruja","le"], +// ... +// ] +// } +// </pre> +// Floating point scalar values: +// <pre> +// {"instances": [0.0, 1.1, 2.2]} +// </pre> +// Vectors of integers: +// <pre> +// { +// "instances": [ +// [0, 1, 2], +// [3, 4, 5], +// ... +// ] +// } +// </pre> +// Tensors (in this case, two-dimensional tensors): +// <pre> +// { +// "instances": [ +// [ +// [0, 1, 2], +// [3, 4, 5] +// ], +// ... +// ] +// } +// </pre> +// Images can be represented different ways. In this encoding scheme the first +// two dimensions represent the rows and columns of the image, and the third +// contains lists (vectors) of the R, G, and B values for each pixel. +// <pre> +// { +// "instances": [ +// [ +// [ +// [138, 30, 66], +// [130, 20, 56], +// ... +// ], +// [ +// [126, 38, 61], +// [122, 24, 57], +// ... +// ], +// ... +// ], +// ... +// ] +// } +// </pre> +// JSON strings must be encoded as UTF-8. To send binary data, you must +// base64-encode the data and mark it as binary. To mark a JSON string +// as binary, replace it with a JSON object with a single attribute named `b64`: +// <pre>{"b64": "..."} </pre> +// For example: +// +// Two Serialized tf.Examples (fake data, for illustrative purposes only): +// <pre> +// {"instances": [{"b64": "X5ad6u"}, {"b64": "IA9j4nx"}]} +// </pre> +// Two JPEG image byte strings (fake data, for illustrative purposes only): +// <pre> +// {"instances": [{"b64": "ASa8asdf"}, {"b64": "JLK7ljk3"}]} +// </pre> +// If your data includes named references, format each instance as a JSON object +// with the named references as the keys: +// +// JSON input data to be preprocessed: +// <pre> +// { +// "instances": [ +// { +// "a": 1.0, +// "b": true, +// "c": "x" +// }, +// { +// "a": -2.0, +// "b": false, +// "c": "y" +// } +// ] +// } +// </pre> +// Some models have an underlying TensorFlow graph that accepts multiple input +// tensors. In this case, you should use the names of JSON name/value pairs to +// identify the input tensors, as shown in the following exmaples: +// +// For a graph with input tensor aliases "tag" (string) and "image" +// (base64-encoded string): +// <pre> +// { +// "instances": [ +// { +// "tag": "beach", +// "image": {"b64": "ASa8asdf"} +// }, +// { +// "tag": "car", +// "image": {"b64": "JLK7ljk3"} +// } +// ] +// } +// </pre> +// For a graph with input tensor aliases "tag" (string) and "image" +// (3-dimensional array of 8-bit ints): +// <pre> +// { +// "instances": [ +// { +// "tag": "beach", +// "image": [ +// [ +// [138, 30, 66], +// [130, 20, 56], +// ... +// ], +// [ +// [126, 38, 61], +// [122, 24, 57], +// ... +// ], +// ... +// ] +// }, +// { +// "tag": "car", +// "image": [ +// [ +// [255, 0, 102], +// [255, 0, 97], +// ... +// ], +// [ +// [254, 1, 101], +// [254, 2, 93], +// ... +// ], +// ... +// ] +// }, +// ... +// ] +// } +// </pre> +// If the call is successful, the response body will contain one prediction +// entry per instance in the request body. If prediction fails for any +// instance, the response body will contain no predictions and will contian +// a single error entry instead. +message PredictRequest { + // Required. The resource name of a model or a version. + // + // Authorization: requires `Viewer` role on the parent project. + string name = 1; + + // + // Required. The prediction request body. + google.api.HttpBody http_body = 2; +} |