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model_evaluation.pb.go
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model_evaluation.pb.go
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// 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.26.0
// protoc v3.12.2
// source: google/cloud/automl/v1/model_evaluation.proto
package automl
import (
reflect "reflect"
sync "sync"
_ "google.golang.org/genproto/googleapis/api/annotations"
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
timestamppb "google.golang.org/protobuf/types/known/timestamppb"
)
const (
// Verify that this generated code is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
// Verify that runtime/protoimpl is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
// Evaluation results of a model.
type ModelEvaluation struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Output only. Problem type specific evaluation metrics.
//
// Types that are assignable to Metrics:
// *ModelEvaluation_ClassificationEvaluationMetrics
// *ModelEvaluation_TranslationEvaluationMetrics
// *ModelEvaluation_ImageObjectDetectionEvaluationMetrics
// *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.v1.TablesModelMetadata.prediction_type]
// the
// [display_name][google.cloud.automl.v1.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.v1.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.v1.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 *timestamppb.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.v1.ModelEvaluation.annotation_spec_id].
EvaluatedExampleCount int32 `protobuf:"varint,6,opt,name=evaluated_example_count,json=evaluatedExampleCount,proto3" json:"evaluated_example_count,omitempty"`
}
func (x *ModelEvaluation) Reset() {
*x = ModelEvaluation{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_automl_v1_model_evaluation_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *ModelEvaluation) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*ModelEvaluation) ProtoMessage() {}
func (x *ModelEvaluation) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_automl_v1_model_evaluation_proto_msgTypes[0]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use ModelEvaluation.ProtoReflect.Descriptor instead.
func (*ModelEvaluation) Descriptor() ([]byte, []int) {
return file_google_cloud_automl_v1_model_evaluation_proto_rawDescGZIP(), []int{0}
}
func (m *ModelEvaluation) GetMetrics() isModelEvaluation_Metrics {
if m != nil {
return m.Metrics
}
return nil
}
func (x *ModelEvaluation) GetClassificationEvaluationMetrics() *ClassificationEvaluationMetrics {
if x, ok := x.GetMetrics().(*ModelEvaluation_ClassificationEvaluationMetrics); ok {
return x.ClassificationEvaluationMetrics
}
return nil
}
func (x *ModelEvaluation) GetTranslationEvaluationMetrics() *TranslationEvaluationMetrics {
if x, ok := x.GetMetrics().(*ModelEvaluation_TranslationEvaluationMetrics); ok {
return x.TranslationEvaluationMetrics
}
return nil
}
func (x *ModelEvaluation) GetImageObjectDetectionEvaluationMetrics() *ImageObjectDetectionEvaluationMetrics {
if x, ok := x.GetMetrics().(*ModelEvaluation_ImageObjectDetectionEvaluationMetrics); ok {
return x.ImageObjectDetectionEvaluationMetrics
}
return nil
}
func (x *ModelEvaluation) GetTextSentimentEvaluationMetrics() *TextSentimentEvaluationMetrics {
if x, ok := x.GetMetrics().(*ModelEvaluation_TextSentimentEvaluationMetrics); ok {
return x.TextSentimentEvaluationMetrics
}
return nil
}
func (x *ModelEvaluation) GetTextExtractionEvaluationMetrics() *TextExtractionEvaluationMetrics {
if x, ok := x.GetMetrics().(*ModelEvaluation_TextExtractionEvaluationMetrics); ok {
return x.TextExtractionEvaluationMetrics
}
return nil
}
func (x *ModelEvaluation) GetName() string {
if x != nil {
return x.Name
}
return ""
}
func (x *ModelEvaluation) GetAnnotationSpecId() string {
if x != nil {
return x.AnnotationSpecId
}
return ""
}
func (x *ModelEvaluation) GetDisplayName() string {
if x != nil {
return x.DisplayName
}
return ""
}
func (x *ModelEvaluation) GetCreateTime() *timestamppb.Timestamp {
if x != nil {
return x.CreateTime
}
return nil
}
func (x *ModelEvaluation) GetEvaluatedExampleCount() int32 {
if x != nil {
return x.EvaluatedExampleCount
}
return 0
}
type isModelEvaluation_Metrics interface {
isModelEvaluation_Metrics()
}
type ModelEvaluation_ClassificationEvaluationMetrics struct {
// Model evaluation metrics for image, text, video and tables
// classification.
// Tables problem is considered a classification when the target column
// is CATEGORY DataType.
ClassificationEvaluationMetrics *ClassificationEvaluationMetrics `protobuf:"bytes,8,opt,name=classification_evaluation_metrics,json=classificationEvaluationMetrics,proto3,oneof"`
}
type ModelEvaluation_TranslationEvaluationMetrics struct {
// Model evaluation metrics for translation.
TranslationEvaluationMetrics *TranslationEvaluationMetrics `protobuf:"bytes,9,opt,name=translation_evaluation_metrics,json=translationEvaluationMetrics,proto3,oneof"`
}
type ModelEvaluation_ImageObjectDetectionEvaluationMetrics struct {
// Model evaluation metrics for image object detection.
ImageObjectDetectionEvaluationMetrics *ImageObjectDetectionEvaluationMetrics `protobuf:"bytes,12,opt,name=image_object_detection_evaluation_metrics,json=imageObjectDetectionEvaluationMetrics,proto3,oneof"`
}
type ModelEvaluation_TextSentimentEvaluationMetrics struct {
// Evaluation metrics for text sentiment models.
TextSentimentEvaluationMetrics *TextSentimentEvaluationMetrics `protobuf:"bytes,11,opt,name=text_sentiment_evaluation_metrics,json=textSentimentEvaluationMetrics,proto3,oneof"`
}
type ModelEvaluation_TextExtractionEvaluationMetrics struct {
// Evaluation metrics for text extraction models.
TextExtractionEvaluationMetrics *TextExtractionEvaluationMetrics `protobuf:"bytes,13,opt,name=text_extraction_evaluation_metrics,json=textExtractionEvaluationMetrics,proto3,oneof"`
}
func (*ModelEvaluation_ClassificationEvaluationMetrics) isModelEvaluation_Metrics() {}
func (*ModelEvaluation_TranslationEvaluationMetrics) isModelEvaluation_Metrics() {}
func (*ModelEvaluation_ImageObjectDetectionEvaluationMetrics) isModelEvaluation_Metrics() {}
func (*ModelEvaluation_TextSentimentEvaluationMetrics) isModelEvaluation_Metrics() {}
func (*ModelEvaluation_TextExtractionEvaluationMetrics) isModelEvaluation_Metrics() {}
var File_google_cloud_automl_v1_model_evaluation_proto protoreflect.FileDescriptor
var file_google_cloud_automl_v1_model_evaluation_proto_rawDesc = []byte{
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var (
file_google_cloud_automl_v1_model_evaluation_proto_rawDescOnce sync.Once
file_google_cloud_automl_v1_model_evaluation_proto_rawDescData = file_google_cloud_automl_v1_model_evaluation_proto_rawDesc
)
func file_google_cloud_automl_v1_model_evaluation_proto_rawDescGZIP() []byte {
file_google_cloud_automl_v1_model_evaluation_proto_rawDescOnce.Do(func() {
file_google_cloud_automl_v1_model_evaluation_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_automl_v1_model_evaluation_proto_rawDescData)
})
return file_google_cloud_automl_v1_model_evaluation_proto_rawDescData
}
var file_google_cloud_automl_v1_model_evaluation_proto_msgTypes = make([]protoimpl.MessageInfo, 1)
var file_google_cloud_automl_v1_model_evaluation_proto_goTypes = []interface{}{
(*ModelEvaluation)(nil), // 0: google.cloud.automl.v1.ModelEvaluation
(*ClassificationEvaluationMetrics)(nil), // 1: google.cloud.automl.v1.ClassificationEvaluationMetrics
(*TranslationEvaluationMetrics)(nil), // 2: google.cloud.automl.v1.TranslationEvaluationMetrics
(*ImageObjectDetectionEvaluationMetrics)(nil), // 3: google.cloud.automl.v1.ImageObjectDetectionEvaluationMetrics
(*TextSentimentEvaluationMetrics)(nil), // 4: google.cloud.automl.v1.TextSentimentEvaluationMetrics
(*TextExtractionEvaluationMetrics)(nil), // 5: google.cloud.automl.v1.TextExtractionEvaluationMetrics
(*timestamppb.Timestamp)(nil), // 6: google.protobuf.Timestamp
}
var file_google_cloud_automl_v1_model_evaluation_proto_depIdxs = []int32{
1, // 0: google.cloud.automl.v1.ModelEvaluation.classification_evaluation_metrics:type_name -> google.cloud.automl.v1.ClassificationEvaluationMetrics
2, // 1: google.cloud.automl.v1.ModelEvaluation.translation_evaluation_metrics:type_name -> google.cloud.automl.v1.TranslationEvaluationMetrics
3, // 2: google.cloud.automl.v1.ModelEvaluation.image_object_detection_evaluation_metrics:type_name -> google.cloud.automl.v1.ImageObjectDetectionEvaluationMetrics
4, // 3: google.cloud.automl.v1.ModelEvaluation.text_sentiment_evaluation_metrics:type_name -> google.cloud.automl.v1.TextSentimentEvaluationMetrics
5, // 4: google.cloud.automl.v1.ModelEvaluation.text_extraction_evaluation_metrics:type_name -> google.cloud.automl.v1.TextExtractionEvaluationMetrics
6, // 5: google.cloud.automl.v1.ModelEvaluation.create_time:type_name -> google.protobuf.Timestamp
6, // [6:6] is the sub-list for method output_type
6, // [6:6] is the sub-list for method input_type
6, // [6:6] is the sub-list for extension type_name
6, // [6:6] is the sub-list for extension extendee
0, // [0:6] is the sub-list for field type_name
}
func init() { file_google_cloud_automl_v1_model_evaluation_proto_init() }
func file_google_cloud_automl_v1_model_evaluation_proto_init() {
if File_google_cloud_automl_v1_model_evaluation_proto != nil {
return
}
file_google_cloud_automl_v1_classification_proto_init()
file_google_cloud_automl_v1_detection_proto_init()
file_google_cloud_automl_v1_text_extraction_proto_init()
file_google_cloud_automl_v1_text_sentiment_proto_init()
file_google_cloud_automl_v1_translation_proto_init()
if !protoimpl.UnsafeEnabled {
file_google_cloud_automl_v1_model_evaluation_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ModelEvaluation); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
}
file_google_cloud_automl_v1_model_evaluation_proto_msgTypes[0].OneofWrappers = []interface{}{
(*ModelEvaluation_ClassificationEvaluationMetrics)(nil),
(*ModelEvaluation_TranslationEvaluationMetrics)(nil),
(*ModelEvaluation_ImageObjectDetectionEvaluationMetrics)(nil),
(*ModelEvaluation_TextSentimentEvaluationMetrics)(nil),
(*ModelEvaluation_TextExtractionEvaluationMetrics)(nil),
}
type x struct{}
out := protoimpl.TypeBuilder{
File: protoimpl.DescBuilder{
GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_google_cloud_automl_v1_model_evaluation_proto_rawDesc,
NumEnums: 0,
NumMessages: 1,
NumExtensions: 0,
NumServices: 0,
},
GoTypes: file_google_cloud_automl_v1_model_evaluation_proto_goTypes,
DependencyIndexes: file_google_cloud_automl_v1_model_evaluation_proto_depIdxs,
MessageInfos: file_google_cloud_automl_v1_model_evaluation_proto_msgTypes,
}.Build()
File_google_cloud_automl_v1_model_evaluation_proto = out.File
file_google_cloud_automl_v1_model_evaluation_proto_rawDesc = nil
file_google_cloud_automl_v1_model_evaluation_proto_goTypes = nil
file_google_cloud_automl_v1_model_evaluation_proto_depIdxs = nil
}