1// Copyright 2020 Google LLC 2// 3// Licensed under the Apache License, Version 2.0 (the "License"); 4// you may not use this file except in compliance with the License. 5// You may obtain a copy of the License at 6// 7// http://www.apache.org/licenses/LICENSE-2.0 8// 9// Unless required by applicable law or agreed to in writing, software 10// distributed under the License is distributed on an "AS IS" BASIS, 11// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12// See the License for the specific language governing permissions and 13// limitations under the License. 14 15syntax = "proto3"; 16 17package google.cloud.automl.v1beta1; 18 19import "google/cloud/automl/v1beta1/classification.proto"; 20 21option go_package = "cloud.google.com/go/automl/apiv1beta1/automlpb;automlpb"; 22option java_multiple_files = true; 23option java_outer_classname = "TextProto"; 24option java_package = "com.google.cloud.automl.v1beta1"; 25option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1"; 26option ruby_package = "Google::Cloud::AutoML::V1beta1"; 27 28// Dataset metadata for classification. 29message TextClassificationDatasetMetadata { 30 // Required. Type of the classification problem. 31 ClassificationType classification_type = 1; 32} 33 34// Model metadata that is specific to text classification. 35message TextClassificationModelMetadata { 36 // Output only. Classification type of the dataset used to train this model. 37 ClassificationType classification_type = 3; 38} 39 40// Dataset metadata that is specific to text extraction 41message TextExtractionDatasetMetadata { 42 43} 44 45// Model metadata that is specific to text extraction. 46message TextExtractionModelMetadata { 47 // Indicates the scope of model use case. 48 // 49 // * `default`: Use to train a general text extraction model. Default value. 50 // 51 // * `health_care`: Use to train a text extraction model that is tuned for 52 // healthcare applications. 53 string model_hint = 3; 54} 55 56// Dataset metadata for text sentiment. 57message TextSentimentDatasetMetadata { 58 // Required. A sentiment is expressed as an integer ordinal, where higher value 59 // means a more positive sentiment. The range of sentiments that will be used 60 // is between 0 and sentiment_max (inclusive on both ends), and all the values 61 // in the range must be represented in the dataset before a model can be 62 // created. 63 // sentiment_max value must be between 1 and 10 (inclusive). 64 int32 sentiment_max = 1; 65} 66 67// Model metadata that is specific to text sentiment. 68message TextSentimentModelMetadata { 69 70} 71