summaryrefslogtreecommitdiff
path: root/third_party/googleapis/google/cloud/automl/v1/text.proto
blob: 966e3ca7ecff7c0c0e1692fa177f842fe032d558 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
// Copyright 2021 Google LLC
//
// 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.automl.v1;

import "google/cloud/automl/v1/classification.proto";

option csharp_namespace = "Google.Cloud.AutoML.V1";
option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1;automl";
option java_multiple_files = true;
option java_outer_classname = "TextProto";
option java_package = "com.google.cloud.automl.v1";
option php_namespace = "Google\\Cloud\\AutoMl\\V1";
option ruby_package = "Google::Cloud::AutoML::V1";

// Dataset metadata for classification.
message TextClassificationDatasetMetadata {
  // Required. Type of the classification problem.
  ClassificationType classification_type = 1;
}

// Model metadata that is specific to text classification.
message TextClassificationModelMetadata {
  // Output only. Classification type of the dataset used to train this model.
  ClassificationType classification_type = 3;
}

// Dataset metadata that is specific to text extraction
message TextExtractionDatasetMetadata {

}

// Model metadata that is specific to text extraction.
message TextExtractionModelMetadata {

}

// Dataset metadata for text sentiment.
message TextSentimentDatasetMetadata {
  // Required. A sentiment is expressed as an integer ordinal, where higher value
  // means a more positive sentiment. The range of sentiments that will be used
  // is between 0 and sentiment_max (inclusive on both ends), and all the values
  // in the range must be represented in the dataset before a model can be
  // created.
  // sentiment_max value must be between 1 and 10 (inclusive).
  int32 sentiment_max = 1;
}

// Model metadata that is specific to text sentiment.
message TextSentimentModelMetadata {

}