| // Copyright 2019 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 v1.22.0 |
| // protoc v3.12.2 |
| // source: google/cloud/datalabeling/v1beta1/evaluation_job.proto |
| |
| package datalabeling |
| |
| import ( |
| reflect "reflect" |
| sync "sync" |
| |
| proto "github.com/golang/protobuf/proto" |
| timestamp "github.com/golang/protobuf/ptypes/timestamp" |
| _ "google.golang.org/genproto/googleapis/api/annotations" |
| status "google.golang.org/genproto/googleapis/rpc/status" |
| protoreflect "google.golang.org/protobuf/reflect/protoreflect" |
| protoimpl "google.golang.org/protobuf/runtime/protoimpl" |
| ) |
| |
| 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) |
| ) |
| |
| // This is a compile-time assertion that a sufficiently up-to-date version |
| // of the legacy proto package is being used. |
| const _ = proto.ProtoPackageIsVersion4 |
| |
| // State of the job. |
| type EvaluationJob_State int32 |
| |
| const ( |
| EvaluationJob_STATE_UNSPECIFIED EvaluationJob_State = 0 |
| // The job is scheduled to run at the [configured interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. You |
| // can [pause][google.cloud.datalabeling.v1beta1.DataLabelingService.PauseEvaluationJob] or |
| // [delete][google.cloud.datalabeling.v1beta1.DataLabelingService.DeleteEvaluationJob] the job. |
| // |
| // When the job is in this state, it samples prediction input and output |
| // from your model version into your BigQuery table as predictions occur. |
| EvaluationJob_SCHEDULED EvaluationJob_State = 1 |
| // The job is currently running. When the job runs, Data Labeling Service |
| // does several things: |
| // |
| // 1. If you have configured your job to use Data Labeling Service for |
| // ground truth labeling, the service creates a |
| // [Dataset][google.cloud.datalabeling.v1beta1.Dataset] and a labeling task for all data sampled |
| // since the last time the job ran. Human labelers provide ground truth |
| // labels for your data. Human labeling may take hours, or even days, |
| // depending on how much data has been sampled. The job remains in the |
| // `RUNNING` state during this time, and it can even be running multiple |
| // times in parallel if it gets triggered again (for example 24 hours |
| // later) before the earlier run has completed. When human labelers have |
| // finished labeling the data, the next step occurs. |
| // <br><br> |
| // If you have configured your job to provide your own ground truth |
| // labels, Data Labeling Service still creates a [Dataset][google.cloud.datalabeling.v1beta1.Dataset] for newly |
| // sampled data, but it expects that you have already added ground truth |
| // labels to the BigQuery table by this time. The next step occurs |
| // immediately. |
| // |
| // 2. Data Labeling Service creates an [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] by comparing your |
| // model version's predictions with the ground truth labels. |
| // |
| // If the job remains in this state for a long time, it continues to sample |
| // prediction data into your BigQuery table and will run again at the next |
| // interval, even if it causes the job to run multiple times in parallel. |
| EvaluationJob_RUNNING EvaluationJob_State = 2 |
| // The job is not sampling prediction input and output into your BigQuery |
| // table and it will not run according to its schedule. You can |
| // [resume][google.cloud.datalabeling.v1beta1.DataLabelingService.ResumeEvaluationJob] the job. |
| EvaluationJob_PAUSED EvaluationJob_State = 3 |
| // The job has this state right before it is deleted. |
| EvaluationJob_STOPPED EvaluationJob_State = 4 |
| ) |
| |
| // Enum value maps for EvaluationJob_State. |
| var ( |
| EvaluationJob_State_name = map[int32]string{ |
| 0: "STATE_UNSPECIFIED", |
| 1: "SCHEDULED", |
| 2: "RUNNING", |
| 3: "PAUSED", |
| 4: "STOPPED", |
| } |
| EvaluationJob_State_value = map[string]int32{ |
| "STATE_UNSPECIFIED": 0, |
| "SCHEDULED": 1, |
| "RUNNING": 2, |
| "PAUSED": 3, |
| "STOPPED": 4, |
| } |
| ) |
| |
| func (x EvaluationJob_State) Enum() *EvaluationJob_State { |
| p := new(EvaluationJob_State) |
| *p = x |
| return p |
| } |
| |
| func (x EvaluationJob_State) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (EvaluationJob_State) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_enumTypes[0].Descriptor() |
| } |
| |
| func (EvaluationJob_State) Type() protoreflect.EnumType { |
| return &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_enumTypes[0] |
| } |
| |
| func (x EvaluationJob_State) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use EvaluationJob_State.Descriptor instead. |
| func (EvaluationJob_State) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP(), []int{0, 0} |
| } |
| |
| // Defines an evaluation job that runs periodically to generate |
| // [Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation |
| // job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point |
| // for using continuous evaluation. |
| type EvaluationJob struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Output only. After you create a job, Data Labeling Service assigns a name |
| // to the job with the following format: |
| // |
| // "projects/<var>{project_id}</var>/evaluationJobs/<var>{evaluation_job_id}</var>" |
| Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` |
| // Required. Description of the job. The description can be up to 25,000 |
| // characters long. |
| Description string `protobuf:"bytes,2,opt,name=description,proto3" json:"description,omitempty"` |
| // Output only. Describes the current state of the job. |
| State EvaluationJob_State `protobuf:"varint,3,opt,name=state,proto3,enum=google.cloud.datalabeling.v1beta1.EvaluationJob_State" json:"state,omitempty"` |
| // Required. Describes the interval at which the job runs. This interval must |
| // be at least 1 day, and it is rounded to the nearest day. For example, if |
| // you specify a 50-hour interval, the job runs every 2 days. |
| // |
| // You can provide the schedule in |
| // [crontab format](/scheduler/docs/configuring/cron-job-schedules) or in an |
| // [English-like |
| // format](/appengine/docs/standard/python/config/cronref#schedule_format). |
| // |
| // Regardless of what you specify, the job will run at 10:00 AM UTC. Only the |
| // interval from this schedule is used, not the specific time of day. |
| Schedule string `protobuf:"bytes,4,opt,name=schedule,proto3" json:"schedule,omitempty"` |
| // Required. The [AI Platform Prediction model |
| // version](/ml-engine/docs/prediction-overview) to be evaluated. Prediction |
| // input and output is sampled from this model version. When creating an |
| // evaluation job, specify the model version in the following format: |
| // |
| // "projects/<var>{project_id}</var>/models/<var>{model_name}</var>/versions/<var>{version_name}</var>" |
| // |
| // There can only be one evaluation job per model version. |
| ModelVersion string `protobuf:"bytes,5,opt,name=model_version,json=modelVersion,proto3" json:"model_version,omitempty"` |
| // Required. Configuration details for the evaluation job. |
| EvaluationJobConfig *EvaluationJobConfig `protobuf:"bytes,6,opt,name=evaluation_job_config,json=evaluationJobConfig,proto3" json:"evaluation_job_config,omitempty"` |
| // Required. Name of the [AnnotationSpecSet][google.cloud.datalabeling.v1beta1.AnnotationSpecSet] describing all the |
| // labels that your machine learning model outputs. You must create this |
| // resource before you create an evaluation job and provide its name in the |
| // following format: |
| // |
| // "projects/<var>{project_id}</var>/annotationSpecSets/<var>{annotation_spec_set_id}</var>" |
| AnnotationSpecSet string `protobuf:"bytes,7,opt,name=annotation_spec_set,json=annotationSpecSet,proto3" json:"annotation_spec_set,omitempty"` |
| // Required. Whether you want Data Labeling Service to provide ground truth |
| // labels for prediction input. If you want the service to assign human |
| // labelers to annotate your data, set this to `true`. If you want to provide |
| // your own ground truth labels in the evaluation job's BigQuery table, set |
| // this to `false`. |
| LabelMissingGroundTruth bool `protobuf:"varint,8,opt,name=label_missing_ground_truth,json=labelMissingGroundTruth,proto3" json:"label_missing_ground_truth,omitempty"` |
| // Output only. Every time the evaluation job runs and an error occurs, the |
| // failed attempt is appended to this array. |
| Attempts []*Attempt `protobuf:"bytes,9,rep,name=attempts,proto3" json:"attempts,omitempty"` |
| // Output only. Timestamp of when this evaluation job was created. |
| CreateTime *timestamp.Timestamp `protobuf:"bytes,10,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"` |
| } |
| |
| func (x *EvaluationJob) Reset() { |
| *x = EvaluationJob{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[0] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *EvaluationJob) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*EvaluationJob) ProtoMessage() {} |
| |
| func (x *EvaluationJob) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_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 EvaluationJob.ProtoReflect.Descriptor instead. |
| func (*EvaluationJob) Descriptor() ([]byte, []int) { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP(), []int{0} |
| } |
| |
| func (x *EvaluationJob) GetName() string { |
| if x != nil { |
| return x.Name |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJob) GetDescription() string { |
| if x != nil { |
| return x.Description |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJob) GetState() EvaluationJob_State { |
| if x != nil { |
| return x.State |
| } |
| return EvaluationJob_STATE_UNSPECIFIED |
| } |
| |
| func (x *EvaluationJob) GetSchedule() string { |
| if x != nil { |
| return x.Schedule |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJob) GetModelVersion() string { |
| if x != nil { |
| return x.ModelVersion |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJob) GetEvaluationJobConfig() *EvaluationJobConfig { |
| if x != nil { |
| return x.EvaluationJobConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJob) GetAnnotationSpecSet() string { |
| if x != nil { |
| return x.AnnotationSpecSet |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJob) GetLabelMissingGroundTruth() bool { |
| if x != nil { |
| return x.LabelMissingGroundTruth |
| } |
| return false |
| } |
| |
| func (x *EvaluationJob) GetAttempts() []*Attempt { |
| if x != nil { |
| return x.Attempts |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJob) GetCreateTime() *timestamp.Timestamp { |
| if x != nil { |
| return x.CreateTime |
| } |
| return nil |
| } |
| |
| // Configures specific details of how a continuous evaluation job works. Provide |
| // this configuration when you create an EvaluationJob. |
| type EvaluationJobConfig struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Required. Details for how you want human reviewers to provide ground truth |
| // labels. |
| // |
| // Types that are assignable to HumanAnnotationRequestConfig: |
| // *EvaluationJobConfig_ImageClassificationConfig |
| // *EvaluationJobConfig_BoundingPolyConfig |
| // *EvaluationJobConfig_TextClassificationConfig |
| HumanAnnotationRequestConfig isEvaluationJobConfig_HumanAnnotationRequestConfig `protobuf_oneof:"human_annotation_request_config"` |
| // Rquired. Details for the sampled prediction input. Within this |
| // configuration, there are requirements for several fields: |
| // |
| // * `dataType` must be one of `IMAGE`, `TEXT`, or `GENERAL_DATA`. |
| // * `annotationType` must be one of `IMAGE_CLASSIFICATION_ANNOTATION`, |
| // `TEXT_CLASSIFICATION_ANNOTATION`, `GENERAL_CLASSIFICATION_ANNOTATION`, |
| // or `IMAGE_BOUNDING_BOX_ANNOTATION` (image object detection). |
| // * If your machine learning model performs classification, you must specify |
| // `classificationMetadata.isMultiLabel`. |
| // * You must specify `bigquerySource` (not `gcsSource`). |
| InputConfig *InputConfig `protobuf:"bytes,1,opt,name=input_config,json=inputConfig,proto3" json:"input_config,omitempty"` |
| // Required. Details for calculating evaluation metrics and creating |
| // [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object |
| // detection, you must specify the `boundingBoxEvaluationOptions` field within |
| // this configuration. Otherwise, provide an empty object for this |
| // configuration. |
| EvaluationConfig *EvaluationConfig `protobuf:"bytes,2,opt,name=evaluation_config,json=evaluationConfig,proto3" json:"evaluation_config,omitempty"` |
| // Optional. Details for human annotation of your data. If you set |
| // [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to |
| // `true` for this evaluation job, then you must specify this field. If you |
| // plan to provide your own ground truth labels, then omit this field. |
| // |
| // Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can |
| // specify this field. Provide the name of the instruction resource in the |
| // `instruction` field within this configuration. |
| HumanAnnotationConfig *HumanAnnotationConfig `protobuf:"bytes,3,opt,name=human_annotation_config,json=humanAnnotationConfig,proto3" json:"human_annotation_config,omitempty"` |
| // Required. Prediction keys that tell Data Labeling Service where to find the |
| // data for evaluation in your BigQuery table. When the service samples |
| // prediction input and output from your model version and saves it to |
| // BigQuery, the data gets stored as JSON strings in the BigQuery table. These |
| // keys tell Data Labeling Service how to parse the JSON. |
| // |
| // You can provide the following entries in this field: |
| // |
| // * `data_json_key`: the data key for prediction input. You must provide |
| // either this key or `reference_json_key`. |
| // * `reference_json_key`: the data reference key for prediction input. You |
| // must provide either this key or `data_json_key`. |
| // * `label_json_key`: the label key for prediction output. Required. |
| // * `label_score_json_key`: the score key for prediction output. Required. |
| // * `bounding_box_json_key`: the bounding box key for prediction output. |
| // Required if your model version perform image object detection. |
| // |
| // Learn [how to configure prediction |
| // keys](/ml-engine/docs/continuous-evaluation/create-job#prediction-keys). |
| BigqueryImportKeys map[string]string `protobuf:"bytes,9,rep,name=bigquery_import_keys,json=bigqueryImportKeys,proto3" json:"bigquery_import_keys,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` |
| // Required. The maximum number of predictions to sample and save to BigQuery |
| // during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit |
| // overrides `example_sample_percentage`: even if the service has not sampled |
| // enough predictions to fulfill `example_sample_perecentage` during an |
| // interval, it stops sampling predictions when it meets this limit. |
| ExampleCount int32 `protobuf:"varint,10,opt,name=example_count,json=exampleCount,proto3" json:"example_count,omitempty"` |
| // Required. Fraction of predictions to sample and save to BigQuery during |
| // each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means |
| // 10% of predictions served by your model version get saved to BigQuery. |
| ExampleSamplePercentage float64 `protobuf:"fixed64,11,opt,name=example_sample_percentage,json=exampleSamplePercentage,proto3" json:"example_sample_percentage,omitempty"` |
| // Optional. Configuration details for evaluation job alerts. Specify this |
| // field if you want to receive email alerts if the evaluation job finds that |
| // your predictions have low mean average precision during a run. |
| EvaluationJobAlertConfig *EvaluationJobAlertConfig `protobuf:"bytes,13,opt,name=evaluation_job_alert_config,json=evaluationJobAlertConfig,proto3" json:"evaluation_job_alert_config,omitempty"` |
| } |
| |
| func (x *EvaluationJobConfig) Reset() { |
| *x = EvaluationJobConfig{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[1] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *EvaluationJobConfig) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*EvaluationJobConfig) ProtoMessage() {} |
| |
| func (x *EvaluationJobConfig) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[1] |
| 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 EvaluationJobConfig.ProtoReflect.Descriptor instead. |
| func (*EvaluationJobConfig) Descriptor() ([]byte, []int) { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP(), []int{1} |
| } |
| |
| func (m *EvaluationJobConfig) GetHumanAnnotationRequestConfig() isEvaluationJobConfig_HumanAnnotationRequestConfig { |
| if m != nil { |
| return m.HumanAnnotationRequestConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetImageClassificationConfig() *ImageClassificationConfig { |
| if x, ok := x.GetHumanAnnotationRequestConfig().(*EvaluationJobConfig_ImageClassificationConfig); ok { |
| return x.ImageClassificationConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetBoundingPolyConfig() *BoundingPolyConfig { |
| if x, ok := x.GetHumanAnnotationRequestConfig().(*EvaluationJobConfig_BoundingPolyConfig); ok { |
| return x.BoundingPolyConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetTextClassificationConfig() *TextClassificationConfig { |
| if x, ok := x.GetHumanAnnotationRequestConfig().(*EvaluationJobConfig_TextClassificationConfig); ok { |
| return x.TextClassificationConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetInputConfig() *InputConfig { |
| if x != nil { |
| return x.InputConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetEvaluationConfig() *EvaluationConfig { |
| if x != nil { |
| return x.EvaluationConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetHumanAnnotationConfig() *HumanAnnotationConfig { |
| if x != nil { |
| return x.HumanAnnotationConfig |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetBigqueryImportKeys() map[string]string { |
| if x != nil { |
| return x.BigqueryImportKeys |
| } |
| return nil |
| } |
| |
| func (x *EvaluationJobConfig) GetExampleCount() int32 { |
| if x != nil { |
| return x.ExampleCount |
| } |
| return 0 |
| } |
| |
| func (x *EvaluationJobConfig) GetExampleSamplePercentage() float64 { |
| if x != nil { |
| return x.ExampleSamplePercentage |
| } |
| return 0 |
| } |
| |
| func (x *EvaluationJobConfig) GetEvaluationJobAlertConfig() *EvaluationJobAlertConfig { |
| if x != nil { |
| return x.EvaluationJobAlertConfig |
| } |
| return nil |
| } |
| |
| type isEvaluationJobConfig_HumanAnnotationRequestConfig interface { |
| isEvaluationJobConfig_HumanAnnotationRequestConfig() |
| } |
| |
| type EvaluationJobConfig_ImageClassificationConfig struct { |
| // Specify this field if your model version performs image classification or |
| // general classification. |
| // |
| // `annotationSpecSet` in this configuration must match |
| // [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. |
| // `allowMultiLabel` in this configuration must match |
| // `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config]. |
| ImageClassificationConfig *ImageClassificationConfig `protobuf:"bytes,4,opt,name=image_classification_config,json=imageClassificationConfig,proto3,oneof"` |
| } |
| |
| type EvaluationJobConfig_BoundingPolyConfig struct { |
| // Specify this field if your model version performs image object detection |
| // (bounding box detection). |
| // |
| // `annotationSpecSet` in this configuration must match |
| // [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. |
| BoundingPolyConfig *BoundingPolyConfig `protobuf:"bytes,5,opt,name=bounding_poly_config,json=boundingPolyConfig,proto3,oneof"` |
| } |
| |
| type EvaluationJobConfig_TextClassificationConfig struct { |
| // Specify this field if your model version performs text classification. |
| // |
| // `annotationSpecSet` in this configuration must match |
| // [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. |
| // `allowMultiLabel` in this configuration must match |
| // `classificationMetadata.isMultiLabel` in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config]. |
| TextClassificationConfig *TextClassificationConfig `protobuf:"bytes,8,opt,name=text_classification_config,json=textClassificationConfig,proto3,oneof"` |
| } |
| |
| func (*EvaluationJobConfig_ImageClassificationConfig) isEvaluationJobConfig_HumanAnnotationRequestConfig() { |
| } |
| |
| func (*EvaluationJobConfig_BoundingPolyConfig) isEvaluationJobConfig_HumanAnnotationRequestConfig() {} |
| |
| func (*EvaluationJobConfig_TextClassificationConfig) isEvaluationJobConfig_HumanAnnotationRequestConfig() { |
| } |
| |
| // Provides details for how an evaluation job sends email alerts based on the |
| // results of a run. |
| type EvaluationJobAlertConfig struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Required. An email address to send alerts to. |
| Email string `protobuf:"bytes,1,opt,name=email,proto3" json:"email,omitempty"` |
| // Required. A number between 0 and 1 that describes a minimum mean average |
| // precision threshold. When the evaluation job runs, if it calculates that |
| // your model version's predictions from the recent interval have |
| // [meanAveragePrecision][google.cloud.datalabeling.v1beta1.PrCurve.mean_average_precision] below this |
| // threshold, then it sends an alert to your specified email. |
| MinAcceptableMeanAveragePrecision float64 `protobuf:"fixed64,2,opt,name=min_acceptable_mean_average_precision,json=minAcceptableMeanAveragePrecision,proto3" json:"min_acceptable_mean_average_precision,omitempty"` |
| } |
| |
| func (x *EvaluationJobAlertConfig) Reset() { |
| *x = EvaluationJobAlertConfig{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[2] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *EvaluationJobAlertConfig) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*EvaluationJobAlertConfig) ProtoMessage() {} |
| |
| func (x *EvaluationJobAlertConfig) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[2] |
| 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 EvaluationJobAlertConfig.ProtoReflect.Descriptor instead. |
| func (*EvaluationJobAlertConfig) Descriptor() ([]byte, []int) { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP(), []int{2} |
| } |
| |
| func (x *EvaluationJobAlertConfig) GetEmail() string { |
| if x != nil { |
| return x.Email |
| } |
| return "" |
| } |
| |
| func (x *EvaluationJobAlertConfig) GetMinAcceptableMeanAveragePrecision() float64 { |
| if x != nil { |
| return x.MinAcceptableMeanAveragePrecision |
| } |
| return 0 |
| } |
| |
| // Records a failed evaluation job run. |
| type Attempt struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| AttemptTime *timestamp.Timestamp `protobuf:"bytes,1,opt,name=attempt_time,json=attemptTime,proto3" json:"attempt_time,omitempty"` |
| // Details of errors that occurred. |
| PartialFailures []*status.Status `protobuf:"bytes,2,rep,name=partial_failures,json=partialFailures,proto3" json:"partial_failures,omitempty"` |
| } |
| |
| func (x *Attempt) Reset() { |
| *x = Attempt{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[3] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *Attempt) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*Attempt) ProtoMessage() {} |
| |
| func (x *Attempt) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[3] |
| 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 Attempt.ProtoReflect.Descriptor instead. |
| func (*Attempt) Descriptor() ([]byte, []int) { |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP(), []int{3} |
| } |
| |
| func (x *Attempt) GetAttemptTime() *timestamp.Timestamp { |
| if x != nil { |
| return x.AttemptTime |
| } |
| return nil |
| } |
| |
| func (x *Attempt) GetPartialFailures() []*status.Status { |
| if x != nil { |
| return x.PartialFailures |
| } |
| return nil |
| } |
| |
| var File_google_cloud_datalabeling_v1beta1_evaluation_job_proto protoreflect.FileDescriptor |
| |
| var file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDesc = []byte{ |
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| } |
| |
| var ( |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescOnce sync.Once |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescData = file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDesc |
| ) |
| |
| func file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescGZIP() []byte { |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescOnce.Do(func() { |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescData) |
| }) |
| return file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDescData |
| } |
| |
| var file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_enumTypes = make([]protoimpl.EnumInfo, 1) |
| var file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes = make([]protoimpl.MessageInfo, 5) |
| var file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_goTypes = []interface{}{ |
| (EvaluationJob_State)(0), // 0: google.cloud.datalabeling.v1beta1.EvaluationJob.State |
| (*EvaluationJob)(nil), // 1: google.cloud.datalabeling.v1beta1.EvaluationJob |
| (*EvaluationJobConfig)(nil), // 2: google.cloud.datalabeling.v1beta1.EvaluationJobConfig |
| (*EvaluationJobAlertConfig)(nil), // 3: google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig |
| (*Attempt)(nil), // 4: google.cloud.datalabeling.v1beta1.Attempt |
| nil, // 5: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.BigqueryImportKeysEntry |
| (*timestamp.Timestamp)(nil), // 6: google.protobuf.Timestamp |
| (*ImageClassificationConfig)(nil), // 7: google.cloud.datalabeling.v1beta1.ImageClassificationConfig |
| (*BoundingPolyConfig)(nil), // 8: google.cloud.datalabeling.v1beta1.BoundingPolyConfig |
| (*TextClassificationConfig)(nil), // 9: google.cloud.datalabeling.v1beta1.TextClassificationConfig |
| (*InputConfig)(nil), // 10: google.cloud.datalabeling.v1beta1.InputConfig |
| (*EvaluationConfig)(nil), // 11: google.cloud.datalabeling.v1beta1.EvaluationConfig |
| (*HumanAnnotationConfig)(nil), // 12: google.cloud.datalabeling.v1beta1.HumanAnnotationConfig |
| (*status.Status)(nil), // 13: google.rpc.Status |
| } |
| var file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_depIdxs = []int32{ |
| 0, // 0: google.cloud.datalabeling.v1beta1.EvaluationJob.state:type_name -> google.cloud.datalabeling.v1beta1.EvaluationJob.State |
| 2, // 1: google.cloud.datalabeling.v1beta1.EvaluationJob.evaluation_job_config:type_name -> google.cloud.datalabeling.v1beta1.EvaluationJobConfig |
| 4, // 2: google.cloud.datalabeling.v1beta1.EvaluationJob.attempts:type_name -> google.cloud.datalabeling.v1beta1.Attempt |
| 6, // 3: google.cloud.datalabeling.v1beta1.EvaluationJob.create_time:type_name -> google.protobuf.Timestamp |
| 7, // 4: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.image_classification_config:type_name -> google.cloud.datalabeling.v1beta1.ImageClassificationConfig |
| 8, // 5: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.bounding_poly_config:type_name -> google.cloud.datalabeling.v1beta1.BoundingPolyConfig |
| 9, // 6: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.text_classification_config:type_name -> google.cloud.datalabeling.v1beta1.TextClassificationConfig |
| 10, // 7: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config:type_name -> google.cloud.datalabeling.v1beta1.InputConfig |
| 11, // 8: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.evaluation_config:type_name -> google.cloud.datalabeling.v1beta1.EvaluationConfig |
| 12, // 9: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.human_annotation_config:type_name -> google.cloud.datalabeling.v1beta1.HumanAnnotationConfig |
| 5, // 10: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.bigquery_import_keys:type_name -> google.cloud.datalabeling.v1beta1.EvaluationJobConfig.BigqueryImportKeysEntry |
| 3, // 11: google.cloud.datalabeling.v1beta1.EvaluationJobConfig.evaluation_job_alert_config:type_name -> google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig |
| 6, // 12: google.cloud.datalabeling.v1beta1.Attempt.attempt_time:type_name -> google.protobuf.Timestamp |
| 13, // 13: google.cloud.datalabeling.v1beta1.Attempt.partial_failures:type_name -> google.rpc.Status |
| 14, // [14:14] is the sub-list for method output_type |
| 14, // [14:14] is the sub-list for method input_type |
| 14, // [14:14] is the sub-list for extension type_name |
| 14, // [14:14] is the sub-list for extension extendee |
| 0, // [0:14] is the sub-list for field type_name |
| } |
| |
| func init() { file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_init() } |
| func file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_init() { |
| if File_google_cloud_datalabeling_v1beta1_evaluation_job_proto != nil { |
| return |
| } |
| file_google_cloud_datalabeling_v1beta1_dataset_proto_init() |
| file_google_cloud_datalabeling_v1beta1_evaluation_proto_init() |
| file_google_cloud_datalabeling_v1beta1_human_annotation_config_proto_init() |
| if !protoimpl.UnsafeEnabled { |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*EvaluationJob); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*EvaluationJobConfig); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*EvaluationJobAlertConfig); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*Attempt); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| } |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes[1].OneofWrappers = []interface{}{ |
| (*EvaluationJobConfig_ImageClassificationConfig)(nil), |
| (*EvaluationJobConfig_BoundingPolyConfig)(nil), |
| (*EvaluationJobConfig_TextClassificationConfig)(nil), |
| } |
| type x struct{} |
| out := protoimpl.TypeBuilder{ |
| File: protoimpl.DescBuilder{ |
| GoPackagePath: reflect.TypeOf(x{}).PkgPath(), |
| RawDescriptor: file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDesc, |
| NumEnums: 1, |
| NumMessages: 5, |
| NumExtensions: 0, |
| NumServices: 0, |
| }, |
| GoTypes: file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_goTypes, |
| DependencyIndexes: file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_depIdxs, |
| EnumInfos: file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_enumTypes, |
| MessageInfos: file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_msgTypes, |
| }.Build() |
| File_google_cloud_datalabeling_v1beta1_evaluation_job_proto = out.File |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_rawDesc = nil |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_goTypes = nil |
| file_google_cloud_datalabeling_v1beta1_evaluation_job_proto_depIdxs = nil |
| } |
