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105 lines
4.4 KiB
105 lines
4.4 KiB
// Copyright 2018 Google LLC.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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syntax = "proto3";
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package google.cloud.automl.v1beta1;
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import "google/api/annotations.proto";
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import "google/cloud/automl/v1beta1/classification.proto";
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import "google/cloud/automl/v1beta1/detection.proto";
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import "google/cloud/automl/v1beta1/regression.proto";
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import "google/cloud/automl/v1beta1/tables.proto";
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import "google/cloud/automl/v1beta1/text_extraction.proto";
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import "google/cloud/automl/v1beta1/text_sentiment.proto";
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import "google/cloud/automl/v1beta1/translation.proto";
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import "google/protobuf/timestamp.proto";
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option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
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option java_multiple_files = true;
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option java_package = "com.google.cloud.automl.v1beta1";
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option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";
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// Evaluation results of a model.
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message ModelEvaluation {
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// Output only. Problem type specific evaluation metrics.
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oneof metrics {
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// Model evaluation metrics for image, text, video and tables
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// classification.
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// Tables problem is considered a classification when the target column
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// has either CATEGORY or ARRAY(CATEGORY) DataType.
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ClassificationEvaluationMetrics classification_evaluation_metrics = 8;
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// Model evaluation metrics for Tables regression.
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// Tables problem is considered a regression when the target column
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// has FLOAT64 DataType.
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RegressionEvaluationMetrics regression_evaluation_metrics = 24;
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// Model evaluation metrics for translation.
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TranslationEvaluationMetrics translation_evaluation_metrics = 9;
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// Model evaluation metrics for image object detection.
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ImageObjectDetectionEvaluationMetrics image_object_detection_evaluation_metrics = 12;
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// Evaluation metrics for text sentiment models.
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TextSentimentEvaluationMetrics text_sentiment_evaluation_metrics = 11;
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// Evaluation metrics for text extraction models.
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TextExtractionEvaluationMetrics text_extraction_evaluation_metrics = 13;
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}
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// Output only.
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// Resource name of the model evaluation.
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// Format:
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//
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// `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}`
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string name = 1;
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// Output only.
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// The ID of the annotation spec that the model evaluation applies to. The
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// The ID is empty for the overall model evaluation.
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// For Tables classification these are the distinct values of the target
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// column at the moment of the evaluation; for this problem annotation specs
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// in the dataset do not exist.
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// NOTE: Currently there is no way to obtain the display_name of the
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// annotation spec from its ID. To see the display_names, review the model
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// evaluations in the UI.
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string annotation_spec_id = 2;
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// Output only. The value of [AnnotationSpec.display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] when the model
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// was trained. Because this field returns a value at model training time,
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// for different models trained using the same dataset, the returned value
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// could be different as model owner could update the display_name between
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// any two model training.
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// The display_name is empty for the overall model evaluation.
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string display_name = 15;
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// Output only.
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// Timestamp when this model evaluation was created.
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google.protobuf.Timestamp create_time = 5;
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// Output only.
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// The number of examples used for model evaluation, i.e. for
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// which ground truth from time of model creation is compared against the
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// predicted annotations created by the model.
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// For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is
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// the total number of all examples used for evaluation.
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// Otherwise, this is the count of examples that according to the ground
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// truth were annotated by the
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//
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// [annotation_spec_id][google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id].
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int32 evaluated_example_count = 6;
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}
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