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feat: add TPU_V4_POD to AcceleratorType in aiplatform v1beta1 acceler…
…ator_type.proto feat: add split to ExportDataConfig in aiplatform v1beta1 dataset.proto feat: add evaluated_annotation.proto to aiplatform v1beta1 feat: add cpu_utilization_target to Featurestore.OnlineServingConfig.Scaling in aiplatform v1beta1 featurestore.proto feat: add large_model_reference to Model in aiplatform v1beta1 model.proto feat: add slice_spec to ModelEvaluationSlice in aiplatform v1beta1 model_evaluation_slice.proto feat: add BatchImportEvaluatedAnnotations rpc to aiplatform v1beta1 model_service.proto docs: deprecated enable_restricted_image_training in NasJob in aiplatform v1beta1 nas_job.proto PiperOrigin-RevId: 513669538
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google/cloud/aiplatform/v1beta1/evaluated_annotation.proto
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| // Copyright 2022 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. | ||
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| syntax = "proto3"; | ||
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| package google.cloud.aiplatform.v1beta1; | ||
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| import "google/api/field_behavior.proto"; | ||
| import "google/cloud/aiplatform/v1beta1/explanation.proto"; | ||
| import "google/protobuf/struct.proto"; | ||
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| option csharp_namespace = "Google.Cloud.AIPlatform.V1Beta1"; | ||
| option go_package = "cloud.google.com/go/aiplatform/apiv1beta1/aiplatformpb;aiplatformpb"; | ||
| option java_multiple_files = true; | ||
| option java_outer_classname = "EvaluatedAnnotationProto"; | ||
| option java_package = "com.google.cloud.aiplatform.v1beta1"; | ||
| option php_namespace = "Google\\Cloud\\AIPlatform\\V1beta1"; | ||
| option ruby_package = "Google::Cloud::AIPlatform::V1beta1"; | ||
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| // True positive, false positive, or false negative. | ||
| // | ||
| // EvaluatedAnnotation is only available under ModelEvaluationSlice with slice | ||
| // of `annotationSpec` dimension. | ||
| message EvaluatedAnnotation { | ||
| // Describes the type of the EvaluatedAnnotation. The type is determined | ||
| enum EvaluatedAnnotationType { | ||
| // Invalid value. | ||
| EVALUATED_ANNOTATION_TYPE_UNSPECIFIED = 0; | ||
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| // The EvaluatedAnnotation is a true positive. It has a prediction created | ||
| // by the Model and a ground truth Annotation which the prediction matches. | ||
| TRUE_POSITIVE = 1; | ||
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| // The EvaluatedAnnotation is false positive. It has a prediction created by | ||
| // the Model which does not match any ground truth annotation. | ||
| FALSE_POSITIVE = 2; | ||
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| // The EvaluatedAnnotation is false negative. It has a ground truth | ||
| // annotation which is not matched by any of the model created predictions. | ||
| FALSE_NEGATIVE = 3; | ||
| } | ||
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| // Output only. Type of the EvaluatedAnnotation. | ||
| EvaluatedAnnotationType type = 1 [(google.api.field_behavior) = OUTPUT_ONLY]; | ||
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| // Output only. The model predicted annotations. | ||
| // | ||
| // For true positive, there is one and only one prediction, which matches the | ||
| // only one ground truth annotation in | ||
| // [ground_truths][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.ground_truths]. | ||
| // | ||
| // For false positive, there is one and only one prediction, which doesn't | ||
| // match any ground truth annotation of the corresponding | ||
| // [data_item_view_id][EvaluatedAnnotation.data_item_view_id]. | ||
| // | ||
| // For false negative, there are zero or more predictions which are similar to | ||
| // the only ground truth annotation in | ||
| // [ground_truths][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.ground_truths] | ||
| // but not enough for a match. | ||
| // | ||
| // The schema of the prediction is stored in | ||
| // [ModelEvaluation.annotation_schema_uri][] | ||
| repeated google.protobuf.Value predictions = 2 | ||
| [(google.api.field_behavior) = OUTPUT_ONLY]; | ||
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| // Output only. The ground truth Annotations, i.e. the Annotations that exist | ||
| // in the test data the Model is evaluated on. | ||
| // | ||
| // For true positive, there is one and only one ground truth annotation, which | ||
| // matches the only prediction in | ||
| // [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions]. | ||
| // | ||
| // For false positive, there are zero or more ground truth annotations that | ||
| // are similar to the only prediction in | ||
| // [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions], | ||
| // but not enough for a match. | ||
| // | ||
| // For false negative, there is one and only one ground truth annotation, | ||
| // which doesn't match any predictions created by the model. | ||
| // | ||
| // The schema of the ground truth is stored in | ||
| // [ModelEvaluation.annotation_schema_uri][] | ||
| repeated google.protobuf.Value ground_truths = 3 | ||
| [(google.api.field_behavior) = OUTPUT_ONLY]; | ||
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| // Output only. The data item payload that the Model predicted this | ||
| // EvaluatedAnnotation on. | ||
| google.protobuf.Value data_item_payload = 5 | ||
| [(google.api.field_behavior) = OUTPUT_ONLY]; | ||
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| // Output only. ID of the EvaluatedDataItemView under the same ancestor | ||
| // ModelEvaluation. The EvaluatedDataItemView consists of all ground truths | ||
| // and predictions on | ||
| // [data_item_payload][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.data_item_payload]. | ||
| // | ||
| // Can be passed in | ||
| // [GetEvaluatedDataItemView's][ModelService.GetEvaluatedDataItemView][] | ||
| // [id][GetEvaluatedDataItemViewRequest.id]. | ||
| string evaluated_data_item_view_id = 6 | ||
| [(google.api.field_behavior) = OUTPUT_ONLY]; | ||
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| // Explanations of | ||
| // [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions]. | ||
| // Each element of the explanations indicates the explanation for one | ||
| // explanation Method. | ||
| // | ||
| // The attributions list in the | ||
| // [EvaluatedAnnotationExplanation.explanation][google.cloud.aiplatform.v1beta1.EvaluatedAnnotationExplanation.explanation] | ||
| // object corresponds to the | ||
| // [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions] | ||
| // list. For example, the second element in the attributions list explains the | ||
| // second element in the predictions list. | ||
| repeated EvaluatedAnnotationExplanation explanations = 8; | ||
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| // Annotations of model error analysis results. | ||
| repeated ErrorAnalysisAnnotation error_analysis_annotations = 9; | ||
| } | ||
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| // Explanation result of the prediction produced by the Model. | ||
| message EvaluatedAnnotationExplanation { | ||
| // Explanation type. | ||
| // | ||
| // For AutoML Image Classification models, possible values are: | ||
| // | ||
| // * `image-integrated-gradients` | ||
| // * `image-xrai` | ||
| string explanation_type = 1; | ||
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| // Explanation attribution response details. | ||
| Explanation explanation = 2; | ||
| } | ||
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| // Model error analysis for each annotation. | ||
| message ErrorAnalysisAnnotation { | ||
| // Attributed items for a given annotation, typically representing neighbors | ||
| // from the training sets constrained by the query type. | ||
| message AttributedItem { | ||
| // The unique ID for each annotation. Used by FE to allocate the annotation | ||
| // in DB. | ||
| string annotation_resource_name = 1; | ||
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| // The distance of this item to the annotation. | ||
| double distance = 2; | ||
| } | ||
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| // The query type used for finding the attributed items. | ||
| enum QueryType { | ||
| // Unspecified query type for model error analysis. | ||
| QUERY_TYPE_UNSPECIFIED = 0; | ||
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| // Query similar samples across all classes in the dataset. | ||
| ALL_SIMILAR = 1; | ||
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| // Query similar samples from the same class of the input sample. | ||
| SAME_CLASS_SIMILAR = 2; | ||
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| // Query dissimilar samples from the same class of the input sample. | ||
| SAME_CLASS_DISSIMILAR = 3; | ||
| } | ||
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| // Attributed items for a given annotation, typically representing neighbors | ||
| // from the training sets constrained by the query type. | ||
| repeated AttributedItem attributed_items = 1; | ||
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| // The query type used for finding the attributed items. | ||
| QueryType query_type = 2; | ||
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| // The outlier score of this annotated item. Usually defined as the min of all | ||
| // distances from attributed items. | ||
| double outlier_score = 3; | ||
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| // The threshold used to determine if this annotation is an outlier or not. | ||
| double outlier_threshold = 4; | ||
| } |
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