| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // source: google/cloud/automl/v1beta1/model_evaluation.proto |
| |
| package automl |
| |
| import ( |
| fmt "fmt" |
| math "math" |
| |
| proto "github.com/golang/protobuf/proto" |
| timestamp "github.com/golang/protobuf/ptypes/timestamp" |
| _ "google.golang.org/genproto/googleapis/api/annotations" |
| ) |
| |
| // Reference imports to suppress errors if they are not otherwise used. |
| var _ = proto.Marshal |
| var _ = fmt.Errorf |
| var _ = math.Inf |
| |
| // This is a compile-time assertion to ensure that this generated file |
| // is compatible with the proto package it is being compiled against. |
| // A compilation error at this line likely means your copy of the |
| // proto package needs to be updated. |
| const _ = proto.ProtoPackageIsVersion3 // please upgrade the proto package |
| |
| // Evaluation results of a model. |
| type ModelEvaluation struct { |
| // Output only. Problem type specific evaluation metrics. |
| // |
| // Types that are valid to be assigned to Metrics: |
| // *ModelEvaluation_ClassificationEvaluationMetrics |
| // *ModelEvaluation_RegressionEvaluationMetrics |
| // *ModelEvaluation_TranslationEvaluationMetrics |
| // *ModelEvaluation_ImageObjectDetectionEvaluationMetrics |
| // *ModelEvaluation_VideoObjectTrackingEvaluationMetrics |
| // *ModelEvaluation_TextSentimentEvaluationMetrics |
| // *ModelEvaluation_TextExtractionEvaluationMetrics |
| Metrics isModelEvaluation_Metrics `protobuf_oneof:"metrics"` |
| // Output only. Resource name of the model evaluation. |
| // Format: |
| // |
| // `projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}` |
| Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` |
| // Output only. The ID of the annotation spec that the model evaluation applies to. The |
| // The ID is empty for the overall model evaluation. |
| // For Tables annotation specs in the dataset do not exist and this ID is |
| // always not set, but for CLASSIFICATION |
| // |
| // [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] |
| // the |
| // [display_name][google.cloud.automl.v1beta1.ModelEvaluation.display_name] |
| // field is used. |
| AnnotationSpecId string `protobuf:"bytes,2,opt,name=annotation_spec_id,json=annotationSpecId,proto3" json:"annotation_spec_id,omitempty"` |
| // Output only. The value of |
| // [display_name][google.cloud.automl.v1beta1.AnnotationSpec.display_name] at |
| // the moment when the model was trained. Because this field returns a value |
| // at model training time, for different models trained from the same dataset, |
| // the values may differ, since display names could had been changed between |
| // the two model's trainings. |
| // For Tables CLASSIFICATION |
| // |
| // [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] |
| // distinct values of the target column at the moment of the model evaluation |
| // are populated here. |
| // The display_name is empty for the overall model evaluation. |
| DisplayName string `protobuf:"bytes,15,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"` |
| // Output only. Timestamp when this model evaluation was created. |
| CreateTime *timestamp.Timestamp `protobuf:"bytes,5,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"` |
| // Output only. The number of examples used for model evaluation, i.e. for |
| // which ground truth from time of model creation is compared against the |
| // predicted annotations created by the model. |
| // For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is |
| // the total number of all examples used for evaluation. |
| // Otherwise, this is the count of examples that according to the ground |
| // truth were annotated by the |
| // |
| // [annotation_spec_id][google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id]. |
| EvaluatedExampleCount int32 `protobuf:"varint,6,opt,name=evaluated_example_count,json=evaluatedExampleCount,proto3" json:"evaluated_example_count,omitempty"` |
| XXX_NoUnkeyedLiteral struct{} `json:"-"` |
| XXX_unrecognized []byte `json:"-"` |
| XXX_sizecache int32 `json:"-"` |
| } |
| |
| func (m *ModelEvaluation) Reset() { *m = ModelEvaluation{} } |
| func (m *ModelEvaluation) String() string { return proto.CompactTextString(m) } |
| func (*ModelEvaluation) ProtoMessage() {} |
| func (*ModelEvaluation) Descriptor() ([]byte, []int) { |
| return fileDescriptor_2d3cea51cfd5443a, []int{0} |
| } |
| |
| func (m *ModelEvaluation) XXX_Unmarshal(b []byte) error { |
| return xxx_messageInfo_ModelEvaluation.Unmarshal(m, b) |
| } |
| func (m *ModelEvaluation) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) { |
| return xxx_messageInfo_ModelEvaluation.Marshal(b, m, deterministic) |
| } |
| func (m *ModelEvaluation) XXX_Merge(src proto.Message) { |
| xxx_messageInfo_ModelEvaluation.Merge(m, src) |
| } |
| func (m *ModelEvaluation) XXX_Size() int { |
| return xxx_messageInfo_ModelEvaluation.Size(m) |
| } |
| func (m *ModelEvaluation) XXX_DiscardUnknown() { |
| xxx_messageInfo_ModelEvaluation.DiscardUnknown(m) |
| } |
| |
| var xxx_messageInfo_ModelEvaluation proto.InternalMessageInfo |
| |
| type isModelEvaluation_Metrics interface { |
| isModelEvaluation_Metrics() |
| } |
| |
| type ModelEvaluation_ClassificationEvaluationMetrics struct { |
| ClassificationEvaluationMetrics *ClassificationEvaluationMetrics `protobuf:"bytes,8,opt,name=classification_evaluation_metrics,json=classificationEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_RegressionEvaluationMetrics struct { |
| RegressionEvaluationMetrics *RegressionEvaluationMetrics `protobuf:"bytes,24,opt,name=regression_evaluation_metrics,json=regressionEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_TranslationEvaluationMetrics struct { |
| TranslationEvaluationMetrics *TranslationEvaluationMetrics `protobuf:"bytes,9,opt,name=translation_evaluation_metrics,json=translationEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_ImageObjectDetectionEvaluationMetrics struct { |
| ImageObjectDetectionEvaluationMetrics *ImageObjectDetectionEvaluationMetrics `protobuf:"bytes,12,opt,name=image_object_detection_evaluation_metrics,json=imageObjectDetectionEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_VideoObjectTrackingEvaluationMetrics struct { |
| VideoObjectTrackingEvaluationMetrics *VideoObjectTrackingEvaluationMetrics `protobuf:"bytes,14,opt,name=video_object_tracking_evaluation_metrics,json=videoObjectTrackingEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_TextSentimentEvaluationMetrics struct { |
| TextSentimentEvaluationMetrics *TextSentimentEvaluationMetrics `protobuf:"bytes,11,opt,name=text_sentiment_evaluation_metrics,json=textSentimentEvaluationMetrics,proto3,oneof"` |
| } |
| |
| type ModelEvaluation_TextExtractionEvaluationMetrics struct { |
| TextExtractionEvaluationMetrics *TextExtractionEvaluationMetrics `protobuf:"bytes,13,opt,name=text_extraction_evaluation_metrics,json=textExtractionEvaluationMetrics,proto3,oneof"` |
| } |
| |
| func (*ModelEvaluation_ClassificationEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_RegressionEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_TranslationEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_ImageObjectDetectionEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_VideoObjectTrackingEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_TextSentimentEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (*ModelEvaluation_TextExtractionEvaluationMetrics) isModelEvaluation_Metrics() {} |
| |
| func (m *ModelEvaluation) GetMetrics() isModelEvaluation_Metrics { |
| if m != nil { |
| return m.Metrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetClassificationEvaluationMetrics() *ClassificationEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_ClassificationEvaluationMetrics); ok { |
| return x.ClassificationEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetRegressionEvaluationMetrics() *RegressionEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_RegressionEvaluationMetrics); ok { |
| return x.RegressionEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetTranslationEvaluationMetrics() *TranslationEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_TranslationEvaluationMetrics); ok { |
| return x.TranslationEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetImageObjectDetectionEvaluationMetrics() *ImageObjectDetectionEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_ImageObjectDetectionEvaluationMetrics); ok { |
| return x.ImageObjectDetectionEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetVideoObjectTrackingEvaluationMetrics() *VideoObjectTrackingEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_VideoObjectTrackingEvaluationMetrics); ok { |
| return x.VideoObjectTrackingEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetTextSentimentEvaluationMetrics() *TextSentimentEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_TextSentimentEvaluationMetrics); ok { |
| return x.TextSentimentEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetTextExtractionEvaluationMetrics() *TextExtractionEvaluationMetrics { |
| if x, ok := m.GetMetrics().(*ModelEvaluation_TextExtractionEvaluationMetrics); ok { |
| return x.TextExtractionEvaluationMetrics |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetName() string { |
| if m != nil { |
| return m.Name |
| } |
| return "" |
| } |
| |
| func (m *ModelEvaluation) GetAnnotationSpecId() string { |
| if m != nil { |
| return m.AnnotationSpecId |
| } |
| return "" |
| } |
| |
| func (m *ModelEvaluation) GetDisplayName() string { |
| if m != nil { |
| return m.DisplayName |
| } |
| return "" |
| } |
| |
| func (m *ModelEvaluation) GetCreateTime() *timestamp.Timestamp { |
| if m != nil { |
| return m.CreateTime |
| } |
| return nil |
| } |
| |
| func (m *ModelEvaluation) GetEvaluatedExampleCount() int32 { |
| if m != nil { |
| return m.EvaluatedExampleCount |
| } |
| return 0 |
| } |
| |
| // XXX_OneofWrappers is for the internal use of the proto package. |
| func (*ModelEvaluation) XXX_OneofWrappers() []interface{} { |
| return []interface{}{ |
| (*ModelEvaluation_ClassificationEvaluationMetrics)(nil), |
| (*ModelEvaluation_RegressionEvaluationMetrics)(nil), |
| (*ModelEvaluation_TranslationEvaluationMetrics)(nil), |
| (*ModelEvaluation_ImageObjectDetectionEvaluationMetrics)(nil), |
| (*ModelEvaluation_VideoObjectTrackingEvaluationMetrics)(nil), |
| (*ModelEvaluation_TextSentimentEvaluationMetrics)(nil), |
| (*ModelEvaluation_TextExtractionEvaluationMetrics)(nil), |
| } |
| } |
| |
| func init() { |
| proto.RegisterType((*ModelEvaluation)(nil), "google.cloud.automl.v1beta1.ModelEvaluation") |
| } |
| |
| func init() { |
| proto.RegisterFile("google/cloud/automl/v1beta1/model_evaluation.proto", fileDescriptor_2d3cea51cfd5443a) |
| } |
| |
| var fileDescriptor_2d3cea51cfd5443a = []byte{ |
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