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batch_prediction_job.pb.go
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batch_prediction_job.pb.go
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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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.26.0
// protoc v3.21.5
// source: google/cloud/aiplatform/v1beta1/batch_prediction_job.proto
package aiplatformpb
import (
reflect "reflect"
sync "sync"
_ "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"
structpb "google.golang.org/protobuf/types/known/structpb"
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)
)
// A job that uses a [Model][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model] to produce predictions
// on multiple [input instances][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If
// predictions for significant portion of the instances fail, the job may finish
// without attempting predictions for all remaining instances.
type BatchPredictionJob struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Output only. Resource name of the BatchPredictionJob.
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
// Required. The user-defined name of this BatchPredictionJob.
DisplayName string `protobuf:"bytes,2,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"`
// The name of the Model resource that produces the predictions via this job,
// must share the same ancestor Location.
// Starting this job has no impact on any existing deployments of the Model
// and their resources.
// Exactly one of model and unmanaged_container_model must be set.
//
// The model resource name may contain version id or version alias to specify
// the version, if no version is specified, the default version will be used.
Model string `protobuf:"bytes,3,opt,name=model,proto3" json:"model,omitempty"`
// Output only. The version ID of the Model that produces the predictions via this job.
ModelVersionId string `protobuf:"bytes,30,opt,name=model_version_id,json=modelVersionId,proto3" json:"model_version_id,omitempty"`
// Contains model information necessary to perform batch prediction without
// requiring uploading to model registry.
// Exactly one of model and unmanaged_container_model must be set.
UnmanagedContainerModel *UnmanagedContainerModel `protobuf:"bytes,28,opt,name=unmanaged_container_model,json=unmanagedContainerModel,proto3" json:"unmanaged_container_model,omitempty"`
// Required. Input configuration of the instances on which predictions are performed.
// The schema of any single instance may be specified via
// the [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
InputConfig *BatchPredictionJob_InputConfig `protobuf:"bytes,4,opt,name=input_config,json=inputConfig,proto3" json:"input_config,omitempty"`
// The parameters that govern the predictions. The schema of the parameters
// may be specified via the [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
ModelParameters *structpb.Value `protobuf:"bytes,5,opt,name=model_parameters,json=modelParameters,proto3" json:"model_parameters,omitempty"`
// Required. The Configuration specifying where output predictions should
// be written.
// The schema of any single prediction may be specified as a concatenation
// of [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
// and
// [prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri].
OutputConfig *BatchPredictionJob_OutputConfig `protobuf:"bytes,6,opt,name=output_config,json=outputConfig,proto3" json:"output_config,omitempty"`
// The config of resources used by the Model during the batch prediction. If
// the Model [supports][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types]
// DEDICATED_RESOURCES this config may be provided (and the job will use these
// resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config
// must be provided.
DedicatedResources *BatchDedicatedResources `protobuf:"bytes,7,opt,name=dedicated_resources,json=dedicatedResources,proto3" json:"dedicated_resources,omitempty"`
// The service account that the DeployedModel's container runs as. If not
// specified, a system generated one will be used, which
// has minimal permissions and the custom container, if used, may not have
// enough permission to access other GCP resources.
//
// Users deploying the Model must have the `iam.serviceAccounts.actAs`
// permission on this service account.
ServiceAccount string `protobuf:"bytes,29,opt,name=service_account,json=serviceAccount,proto3" json:"service_account,omitempty"`
// Immutable. Parameters configuring the batch behavior. Currently only applicable when
// [dedicated_resources][google.cloud.aiplatform.v1beta1.BatchPredictionJob.dedicated_resources] are used (in other cases Vertex AI does
// the tuning itself).
ManualBatchTuningParameters *ManualBatchTuningParameters `protobuf:"bytes,8,opt,name=manual_batch_tuning_parameters,json=manualBatchTuningParameters,proto3" json:"manual_batch_tuning_parameters,omitempty"`
// Generate explanation with the batch prediction results.
//
// When set to `true`, the batch prediction output changes based on the
// `predictions_format` field of the
// [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config] object:
//
// - `bigquery`: output includes a column named `explanation`. The value
// is a struct that conforms to the [Explanation][google.cloud.aiplatform.v1beta1.Explanation] object.
// - `jsonl`: The JSON objects on each line include an additional entry
// keyed `explanation`. The value of the entry is a JSON object that
// conforms to the [Explanation][google.cloud.aiplatform.v1beta1.Explanation] object.
// - `csv`: Generating explanations for CSV format is not supported.
//
// If this field is set to true, either the [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] or
// [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] must be populated.
GenerateExplanation bool `protobuf:"varint,23,opt,name=generate_explanation,json=generateExplanation,proto3" json:"generate_explanation,omitempty"`
// Explanation configuration for this BatchPredictionJob. Can be
// specified only if [generate_explanation][google.cloud.aiplatform.v1beta1.BatchPredictionJob.generate_explanation] is set to `true`.
//
// This value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]. All fields of
// [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] are optional in the request. If a field of the
// [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] object is not populated, the corresponding field of
// the [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] object is inherited.
ExplanationSpec *ExplanationSpec `protobuf:"bytes,25,opt,name=explanation_spec,json=explanationSpec,proto3" json:"explanation_spec,omitempty"`
// Output only. Information further describing the output of this job.
OutputInfo *BatchPredictionJob_OutputInfo `protobuf:"bytes,9,opt,name=output_info,json=outputInfo,proto3" json:"output_info,omitempty"`
// Output only. The detailed state of the job.
State JobState `protobuf:"varint,10,opt,name=state,proto3,enum=google.cloud.aiplatform.v1beta1.JobState" json:"state,omitempty"`
// Output only. Only populated when the job's state is JOB_STATE_FAILED or
// JOB_STATE_CANCELLED.
Error *status.Status `protobuf:"bytes,11,opt,name=error,proto3" json:"error,omitempty"`
// Output only. Partial failures encountered.
// For example, single files that can't be read.
// This field never exceeds 20 entries.
// Status details fields contain standard GCP error details.
PartialFailures []*status.Status `protobuf:"bytes,12,rep,name=partial_failures,json=partialFailures,proto3" json:"partial_failures,omitempty"`
// Output only. Information about resources that had been consumed by this job.
// Provided in real time at best effort basis, as well as a final value
// once the job completes.
//
// Note: This field currently may be not populated for batch predictions that
// use AutoML Models.
ResourcesConsumed *ResourcesConsumed `protobuf:"bytes,13,opt,name=resources_consumed,json=resourcesConsumed,proto3" json:"resources_consumed,omitempty"`
// Output only. Statistics on completed and failed prediction instances.
CompletionStats *CompletionStats `protobuf:"bytes,14,opt,name=completion_stats,json=completionStats,proto3" json:"completion_stats,omitempty"`
// Output only. Time when the BatchPredictionJob was created.
CreateTime *timestamppb.Timestamp `protobuf:"bytes,15,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
// Output only. Time when the BatchPredictionJob for the first time entered the
// `JOB_STATE_RUNNING` state.
StartTime *timestamppb.Timestamp `protobuf:"bytes,16,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
// Output only. Time when the BatchPredictionJob entered any of the following states:
// `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
EndTime *timestamppb.Timestamp `protobuf:"bytes,17,opt,name=end_time,json=endTime,proto3" json:"end_time,omitempty"`
// Output only. Time when the BatchPredictionJob was most recently updated.
UpdateTime *timestamppb.Timestamp `protobuf:"bytes,18,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"`
// The labels with user-defined metadata to organize BatchPredictionJobs.
//
// Label keys and values can be no longer than 64 characters
// (Unicode codepoints), can only contain lowercase letters, numeric
// characters, underscores and dashes. International characters are allowed.
//
// See https://goo.gl/xmQnxf for more information and examples of labels.
Labels map[string]string `protobuf:"bytes,19,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// Customer-managed encryption key options for a BatchPredictionJob. If this
// is set, then all resources created by the BatchPredictionJob will be
// encrypted with the provided encryption key.
EncryptionSpec *EncryptionSpec `protobuf:"bytes,24,opt,name=encryption_spec,json=encryptionSpec,proto3" json:"encryption_spec,omitempty"`
// Model monitoring config will be used for analysis model behaviors, based on
// the input and output to the batch prediction job, as well as the provided
// training dataset.
ModelMonitoringConfig *ModelMonitoringConfig `protobuf:"bytes,26,opt,name=model_monitoring_config,json=modelMonitoringConfig,proto3" json:"model_monitoring_config,omitempty"`
// Get batch prediction job monitoring statistics.
ModelMonitoringStatsAnomalies []*ModelMonitoringStatsAnomalies `protobuf:"bytes,31,rep,name=model_monitoring_stats_anomalies,json=modelMonitoringStatsAnomalies,proto3" json:"model_monitoring_stats_anomalies,omitempty"`
// Output only. The running status of the model monitoring pipeline.
ModelMonitoringStatus *status.Status `protobuf:"bytes,32,opt,name=model_monitoring_status,json=modelMonitoringStatus,proto3" json:"model_monitoring_status,omitempty"`
}
func (x *BatchPredictionJob) Reset() {
*x = BatchPredictionJob{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictionJob) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictionJob) ProtoMessage() {}
func (x *BatchPredictionJob) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_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 BatchPredictionJob.ProtoReflect.Descriptor instead.
func (*BatchPredictionJob) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_rawDescGZIP(), []int{0}
}
func (x *BatchPredictionJob) GetName() string {
if x != nil {
return x.Name
}
return ""
}
func (x *BatchPredictionJob) GetDisplayName() string {
if x != nil {
return x.DisplayName
}
return ""
}
func (x *BatchPredictionJob) GetModel() string {
if x != nil {
return x.Model
}
return ""
}
func (x *BatchPredictionJob) GetModelVersionId() string {
if x != nil {
return x.ModelVersionId
}
return ""
}
func (x *BatchPredictionJob) GetUnmanagedContainerModel() *UnmanagedContainerModel {
if x != nil {
return x.UnmanagedContainerModel
}
return nil
}
func (x *BatchPredictionJob) GetInputConfig() *BatchPredictionJob_InputConfig {
if x != nil {
return x.InputConfig
}
return nil
}
func (x *BatchPredictionJob) GetModelParameters() *structpb.Value {
if x != nil {
return x.ModelParameters
}
return nil
}
func (x *BatchPredictionJob) GetOutputConfig() *BatchPredictionJob_OutputConfig {
if x != nil {
return x.OutputConfig
}
return nil
}
func (x *BatchPredictionJob) GetDedicatedResources() *BatchDedicatedResources {
if x != nil {
return x.DedicatedResources
}
return nil
}
func (x *BatchPredictionJob) GetServiceAccount() string {
if x != nil {
return x.ServiceAccount
}
return ""
}
func (x *BatchPredictionJob) GetManualBatchTuningParameters() *ManualBatchTuningParameters {
if x != nil {
return x.ManualBatchTuningParameters
}
return nil
}
func (x *BatchPredictionJob) GetGenerateExplanation() bool {
if x != nil {
return x.GenerateExplanation
}
return false
}
func (x *BatchPredictionJob) GetExplanationSpec() *ExplanationSpec {
if x != nil {
return x.ExplanationSpec
}
return nil
}
func (x *BatchPredictionJob) GetOutputInfo() *BatchPredictionJob_OutputInfo {
if x != nil {
return x.OutputInfo
}
return nil
}
func (x *BatchPredictionJob) GetState() JobState {
if x != nil {
return x.State
}
return JobState_JOB_STATE_UNSPECIFIED
}
func (x *BatchPredictionJob) GetError() *status.Status {
if x != nil {
return x.Error
}
return nil
}
func (x *BatchPredictionJob) GetPartialFailures() []*status.Status {
if x != nil {
return x.PartialFailures
}
return nil
}
func (x *BatchPredictionJob) GetResourcesConsumed() *ResourcesConsumed {
if x != nil {
return x.ResourcesConsumed
}
return nil
}
func (x *BatchPredictionJob) GetCompletionStats() *CompletionStats {
if x != nil {
return x.CompletionStats
}
return nil
}
func (x *BatchPredictionJob) GetCreateTime() *timestamppb.Timestamp {
if x != nil {
return x.CreateTime
}
return nil
}
func (x *BatchPredictionJob) GetStartTime() *timestamppb.Timestamp {
if x != nil {
return x.StartTime
}
return nil
}
func (x *BatchPredictionJob) GetEndTime() *timestamppb.Timestamp {
if x != nil {
return x.EndTime
}
return nil
}
func (x *BatchPredictionJob) GetUpdateTime() *timestamppb.Timestamp {
if x != nil {
return x.UpdateTime
}
return nil
}
func (x *BatchPredictionJob) GetLabels() map[string]string {
if x != nil {
return x.Labels
}
return nil
}
func (x *BatchPredictionJob) GetEncryptionSpec() *EncryptionSpec {
if x != nil {
return x.EncryptionSpec
}
return nil
}
func (x *BatchPredictionJob) GetModelMonitoringConfig() *ModelMonitoringConfig {
if x != nil {
return x.ModelMonitoringConfig
}
return nil
}
func (x *BatchPredictionJob) GetModelMonitoringStatsAnomalies() []*ModelMonitoringStatsAnomalies {
if x != nil {
return x.ModelMonitoringStatsAnomalies
}
return nil
}
func (x *BatchPredictionJob) GetModelMonitoringStatus() *status.Status {
if x != nil {
return x.ModelMonitoringStatus
}
return nil
}
// Configures the input to [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
// See [Model.supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] for Model's supported input
// formats, and how instances should be expressed via any of them.
type BatchPredictionJob_InputConfig struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The source of the input.
//
// Types that are assignable to Source:
//
// *BatchPredictionJob_InputConfig_GcsSource
// *BatchPredictionJob_InputConfig_BigquerySource
Source isBatchPredictionJob_InputConfig_Source `protobuf_oneof:"source"`
// Required. The format in which instances are given, must be one of the
// [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
// [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats].
InstancesFormat string `protobuf:"bytes,1,opt,name=instances_format,json=instancesFormat,proto3" json:"instances_format,omitempty"`
}
func (x *BatchPredictionJob_InputConfig) Reset() {
*x = BatchPredictionJob_InputConfig{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictionJob_InputConfig) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictionJob_InputConfig) ProtoMessage() {}
func (x *BatchPredictionJob_InputConfig) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_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 BatchPredictionJob_InputConfig.ProtoReflect.Descriptor instead.
func (*BatchPredictionJob_InputConfig) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_rawDescGZIP(), []int{0, 0}
}
func (m *BatchPredictionJob_InputConfig) GetSource() isBatchPredictionJob_InputConfig_Source {
if m != nil {
return m.Source
}
return nil
}
func (x *BatchPredictionJob_InputConfig) GetGcsSource() *GcsSource {
if x, ok := x.GetSource().(*BatchPredictionJob_InputConfig_GcsSource); ok {
return x.GcsSource
}
return nil
}
func (x *BatchPredictionJob_InputConfig) GetBigquerySource() *BigQuerySource {
if x, ok := x.GetSource().(*BatchPredictionJob_InputConfig_BigquerySource); ok {
return x.BigquerySource
}
return nil
}
func (x *BatchPredictionJob_InputConfig) GetInstancesFormat() string {
if x != nil {
return x.InstancesFormat
}
return ""
}
type isBatchPredictionJob_InputConfig_Source interface {
isBatchPredictionJob_InputConfig_Source()
}
type BatchPredictionJob_InputConfig_GcsSource struct {
// The Cloud Storage location for the input instances.
GcsSource *GcsSource `protobuf:"bytes,2,opt,name=gcs_source,json=gcsSource,proto3,oneof"`
}
type BatchPredictionJob_InputConfig_BigquerySource struct {
// The BigQuery location of the input table.
// The schema of the table should be in the format described by the given
// context OpenAPI Schema, if one is provided. The table may contain
// additional columns that are not described by the schema, and they will
// be ignored.
BigquerySource *BigQuerySource `protobuf:"bytes,3,opt,name=bigquery_source,json=bigquerySource,proto3,oneof"`
}
func (*BatchPredictionJob_InputConfig_GcsSource) isBatchPredictionJob_InputConfig_Source() {}
func (*BatchPredictionJob_InputConfig_BigquerySource) isBatchPredictionJob_InputConfig_Source() {}
// Configures the output of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
// See [Model.supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats] for supported output
// formats, and how predictions are expressed via any of them.
type BatchPredictionJob_OutputConfig struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The destination of the output.
//
// Types that are assignable to Destination:
//
// *BatchPredictionJob_OutputConfig_GcsDestination
// *BatchPredictionJob_OutputConfig_BigqueryDestination
Destination isBatchPredictionJob_OutputConfig_Destination `protobuf_oneof:"destination"`
// Required. The format in which Vertex AI gives the predictions, must be one of the
// [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
// [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
PredictionsFormat string `protobuf:"bytes,1,opt,name=predictions_format,json=predictionsFormat,proto3" json:"predictions_format,omitempty"`
}
func (x *BatchPredictionJob_OutputConfig) Reset() {
*x = BatchPredictionJob_OutputConfig{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictionJob_OutputConfig) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictionJob_OutputConfig) ProtoMessage() {}
func (x *BatchPredictionJob_OutputConfig) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_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 BatchPredictionJob_OutputConfig.ProtoReflect.Descriptor instead.
func (*BatchPredictionJob_OutputConfig) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_rawDescGZIP(), []int{0, 1}
}
func (m *BatchPredictionJob_OutputConfig) GetDestination() isBatchPredictionJob_OutputConfig_Destination {
if m != nil {
return m.Destination
}
return nil
}
func (x *BatchPredictionJob_OutputConfig) GetGcsDestination() *GcsDestination {
if x, ok := x.GetDestination().(*BatchPredictionJob_OutputConfig_GcsDestination); ok {
return x.GcsDestination
}
return nil
}
func (x *BatchPredictionJob_OutputConfig) GetBigqueryDestination() *BigQueryDestination {
if x, ok := x.GetDestination().(*BatchPredictionJob_OutputConfig_BigqueryDestination); ok {
return x.BigqueryDestination
}
return nil
}
func (x *BatchPredictionJob_OutputConfig) GetPredictionsFormat() string {
if x != nil {
return x.PredictionsFormat
}
return ""
}
type isBatchPredictionJob_OutputConfig_Destination interface {
isBatchPredictionJob_OutputConfig_Destination()
}
type BatchPredictionJob_OutputConfig_GcsDestination struct {
// The Cloud Storage location of the directory where the output is
// to be written to. In the given directory a new directory is created.
// Its name is `prediction-<model-display-name>-<job-create-time>`,
// where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
// Inside of it files `predictions_0001.<extension>`,
// `predictions_0002.<extension>`, ..., `predictions_N.<extension>`
// are created where `<extension>` depends on chosen
// [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format], and N may equal 0001 and depends on the total
// number of successfully predicted instances.
// If the Model has both [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
// and [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri] schemata
// defined then each such file contains predictions as per the
// [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format].
// If prediction for any instance failed (partially or completely), then
// an additional `errors_0001.<extension>`, `errors_0002.<extension>`,...,
// `errors_N.<extension>` files are created (N depends on total number
// of failed predictions). These files contain the failed instances,
// as per their schema, followed by an additional `error` field which as
// value has [google.rpc.Status][google.rpc.Status]
// containing only `code` and `message` fields.
GcsDestination *GcsDestination `protobuf:"bytes,2,opt,name=gcs_destination,json=gcsDestination,proto3,oneof"`
}
type BatchPredictionJob_OutputConfig_BigqueryDestination struct {
// The BigQuery project or dataset location where the output is to be
// written to. If project is provided, a new dataset is created with name
// `prediction_<model-display-name>_<job-create-time>`
// where <model-display-name> is made
// BigQuery-dataset-name compatible (for example, most special characters
// become underscores), and timestamp is in
// YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
// two tables will be created, `predictions`, and `errors`.
// If the Model has both [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
// and [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri] schemata
// defined then the tables have columns as follows: The `predictions`
// table contains instances for which the prediction succeeded, it
// has columns as per a concatenation of the Model's instance and
// prediction schemata. The `errors` table contains rows for which the
// prediction has failed, it has instance columns, as per the
// instance schema, followed by a single "errors" column, which as values
// has [google.rpc.Status][google.rpc.Status]
// represented as a STRUCT, and containing only `code` and `message`.
BigqueryDestination *BigQueryDestination `protobuf:"bytes,3,opt,name=bigquery_destination,json=bigqueryDestination,proto3,oneof"`
}
func (*BatchPredictionJob_OutputConfig_GcsDestination) isBatchPredictionJob_OutputConfig_Destination() {
}
func (*BatchPredictionJob_OutputConfig_BigqueryDestination) isBatchPredictionJob_OutputConfig_Destination() {
}
// Further describes this job's output.
// Supplements [output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config].
type BatchPredictionJob_OutputInfo struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The output location into which prediction output is written.
//
// Types that are assignable to OutputLocation:
//
// *BatchPredictionJob_OutputInfo_GcsOutputDirectory
// *BatchPredictionJob_OutputInfo_BigqueryOutputDataset
OutputLocation isBatchPredictionJob_OutputInfo_OutputLocation `protobuf_oneof:"output_location"`
// Output only. The name of the BigQuery table created, in
// `predictions_<timestamp>`
// format, into which the prediction output is written.
// Can be used by UI to generate the BigQuery output path, for example.
BigqueryOutputTable string `protobuf:"bytes,4,opt,name=bigquery_output_table,json=bigqueryOutputTable,proto3" json:"bigquery_output_table,omitempty"`
}
func (x *BatchPredictionJob_OutputInfo) Reset() {
*x = BatchPredictionJob_OutputInfo{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *BatchPredictionJob_OutputInfo) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*BatchPredictionJob_OutputInfo) ProtoMessage() {}
func (x *BatchPredictionJob_OutputInfo) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_batch_prediction_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 BatchPredictionJob_OutputInfo.ProtoReflect.Descriptor instead.
func (*BatchPredictionJob_OutputInfo) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto_rawDescGZIP(), []int{0, 2}
}
func (m *BatchPredictionJob_OutputInfo) GetOutputLocation() isBatchPredictionJob_OutputInfo_OutputLocation {
if m != nil {
return m.OutputLocation
}
return nil
}
func (x *BatchPredictionJob_OutputInfo) GetGcsOutputDirectory() string {
if x, ok := x.GetOutputLocation().(*BatchPredictionJob_OutputInfo_GcsOutputDirectory); ok {
return x.GcsOutputDirectory
}
return ""
}
func (x *BatchPredictionJob_OutputInfo) GetBigqueryOutputDataset() string {
if x, ok := x.GetOutputLocation().(*BatchPredictionJob_OutputInfo_BigqueryOutputDataset); ok {
return x.BigqueryOutputDataset
}
return ""
}
func (x *BatchPredictionJob_OutputInfo) GetBigqueryOutputTable() string {
if x != nil {
return x.BigqueryOutputTable
}
return ""
}
type isBatchPredictionJob_OutputInfo_OutputLocation interface {
isBatchPredictionJob_OutputInfo_OutputLocation()
}
type BatchPredictionJob_OutputInfo_GcsOutputDirectory struct {
// Output only. The full path of the Cloud Storage directory created, into which
// the prediction output is written.
GcsOutputDirectory string `protobuf:"bytes,1,opt,name=gcs_output_directory,json=gcsOutputDirectory,proto3,oneof"`
}
type BatchPredictionJob_OutputInfo_BigqueryOutputDataset struct {
// Output only. The path of the BigQuery dataset created, in
// `bq://projectId.bqDatasetId`
// format, into which the prediction output is written.
BigqueryOutputDataset string `protobuf:"bytes,2,opt,name=bigquery_output_dataset,json=bigqueryOutputDataset,proto3,oneof"`
}
func (*BatchPredictionJob_OutputInfo_GcsOutputDirectory) isBatchPredictionJob_OutputInfo_OutputLocation() {
}
func (*BatchPredictionJob_OutputInfo_BigqueryOutputDataset) isBatchPredictionJob_OutputInfo_OutputLocation() {
}
var File_google_cloud_aiplatform_v1beta1_batch_prediction_job_proto protoreflect.FileDescriptor
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