// Copyright 2026 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 v1.35.2
// 	protoc        v4.25.7
// source: google/cloud/aiplatform/v1/dataset.proto

package aiplatformpb

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"
	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)
)

// ExportUse indicates the usage of the exported files. It restricts file
// destination, format, annotations to be exported, whether to allow
// unannotated data to be exported and whether to clone files to temp Cloud
// Storage bucket.
type ExportDataConfig_ExportUse int32

const (
	// Regular user export.
	ExportDataConfig_EXPORT_USE_UNSPECIFIED ExportDataConfig_ExportUse = 0
	// Export for custom code training.
	ExportDataConfig_CUSTOM_CODE_TRAINING ExportDataConfig_ExportUse = 6
)

// Enum value maps for ExportDataConfig_ExportUse.
var (
	ExportDataConfig_ExportUse_name = map[int32]string{
		0: "EXPORT_USE_UNSPECIFIED",
		6: "CUSTOM_CODE_TRAINING",
	}
	ExportDataConfig_ExportUse_value = map[string]int32{
		"EXPORT_USE_UNSPECIFIED": 0,
		"CUSTOM_CODE_TRAINING":   6,
	}
)

func (x ExportDataConfig_ExportUse) Enum() *ExportDataConfig_ExportUse {
	p := new(ExportDataConfig_ExportUse)
	*p = x
	return p
}

func (x ExportDataConfig_ExportUse) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (ExportDataConfig_ExportUse) Descriptor() protoreflect.EnumDescriptor {
	return file_google_cloud_aiplatform_v1_dataset_proto_enumTypes[0].Descriptor()
}

func (ExportDataConfig_ExportUse) Type() protoreflect.EnumType {
	return &file_google_cloud_aiplatform_v1_dataset_proto_enumTypes[0]
}

func (x ExportDataConfig_ExportUse) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use ExportDataConfig_ExportUse.Descriptor instead.
func (ExportDataConfig_ExportUse) EnumDescriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{2, 0}
}

// A collection of DataItems and Annotations on them.
type Dataset struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Output only. Identifier. The resource name of the Dataset.
	// Format:
	// `projects/{project}/locations/{location}/datasets/{dataset}`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// Required. The user-defined name of the Dataset.
	// The name can be up to 128 characters long and can consist of any UTF-8
	// characters.
	DisplayName string `protobuf:"bytes,2,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"`
	// The description of the Dataset.
	Description string `protobuf:"bytes,16,opt,name=description,proto3" json:"description,omitempty"`
	// Required. Points to a YAML file stored on Google Cloud Storage describing
	// additional information about the Dataset. The schema is defined as an
	// OpenAPI 3.0.2 Schema Object. The schema files that can be used here are
	// found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
	MetadataSchemaUri string `protobuf:"bytes,3,opt,name=metadata_schema_uri,json=metadataSchemaUri,proto3" json:"metadata_schema_uri,omitempty"`
	// Required. Additional information about the Dataset.
	Metadata *structpb.Value `protobuf:"bytes,8,opt,name=metadata,proto3" json:"metadata,omitempty"`
	// Output only. The number of DataItems in this Dataset. Only apply for
	// non-structured Dataset.
	DataItemCount int64 `protobuf:"varint,10,opt,name=data_item_count,json=dataItemCount,proto3" json:"data_item_count,omitempty"`
	// Output only. Timestamp when this Dataset was created.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,4,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only. Timestamp when this Dataset was last updated.
	UpdateTime *timestamppb.Timestamp `protobuf:"bytes,5,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"`
	// Used to perform consistent read-modify-write updates. If not set, a blind
	// "overwrite" update happens.
	Etag string `protobuf:"bytes,6,opt,name=etag,proto3" json:"etag,omitempty"`
	// The labels with user-defined metadata to organize your Datasets.
	//
	// 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.
	// No more than 64 user labels can be associated with one Dataset (System
	// labels are excluded).
	//
	// See https://goo.gl/xmQnxf for more information and examples of labels.
	// System reserved label keys are prefixed with "aiplatform.googleapis.com/"
	// and are immutable. Following system labels exist for each Dataset:
	//
	//   - "aiplatform.googleapis.com/dataset_metadata_schema": output only, its
	//     value is the
	//     [metadata_schema's][google.cloud.aiplatform.v1.Dataset.metadata_schema_uri]
	//     title.
	Labels map[string]string `protobuf:"bytes,7,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
	// All SavedQueries belong to the Dataset will be returned in List/Get
	// Dataset response. The annotation_specs field
	// will not be populated except for UI cases which will only use
	// [annotation_spec_count][google.cloud.aiplatform.v1.SavedQuery.annotation_spec_count].
	// In CreateDataset request, a SavedQuery is created together if
	// this field is set, up to one SavedQuery can be set in CreateDatasetRequest.
	// The SavedQuery should not contain any AnnotationSpec.
	SavedQueries []*SavedQuery `protobuf:"bytes,9,rep,name=saved_queries,json=savedQueries,proto3" json:"saved_queries,omitempty"`
	// Customer-managed encryption key spec for a Dataset. If set, this Dataset
	// and all sub-resources of this Dataset will be secured by this key.
	EncryptionSpec *EncryptionSpec `protobuf:"bytes,11,opt,name=encryption_spec,json=encryptionSpec,proto3" json:"encryption_spec,omitempty"`
	// Output only. The resource name of the Artifact that was created in
	// MetadataStore when creating the Dataset. The Artifact resource name pattern
	// is
	// `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
	MetadataArtifact string `protobuf:"bytes,17,opt,name=metadata_artifact,json=metadataArtifact,proto3" json:"metadata_artifact,omitempty"`
	// Optional. Reference to the public base model last used by the dataset. Only
	// set for prompt datasets.
	ModelReference string `protobuf:"bytes,18,opt,name=model_reference,json=modelReference,proto3" json:"model_reference,omitempty"`
	// Output only. Reserved for future use.
	SatisfiesPzs bool `protobuf:"varint,19,opt,name=satisfies_pzs,json=satisfiesPzs,proto3" json:"satisfies_pzs,omitempty"`
	// Output only. Reserved for future use.
	SatisfiesPzi bool `protobuf:"varint,20,opt,name=satisfies_pzi,json=satisfiesPzi,proto3" json:"satisfies_pzi,omitempty"`
}

func (x *Dataset) Reset() {
	*x = Dataset{}
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[0]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *Dataset) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*Dataset) ProtoMessage() {}

func (x *Dataset) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[0]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use Dataset.ProtoReflect.Descriptor instead.
func (*Dataset) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{0}
}

func (x *Dataset) GetName() string {
	if x != nil {
		return x.Name
	}
	return ""
}

func (x *Dataset) GetDisplayName() string {
	if x != nil {
		return x.DisplayName
	}
	return ""
}

func (x *Dataset) GetDescription() string {
	if x != nil {
		return x.Description
	}
	return ""
}

func (x *Dataset) GetMetadataSchemaUri() string {
	if x != nil {
		return x.MetadataSchemaUri
	}
	return ""
}

func (x *Dataset) GetMetadata() *structpb.Value {
	if x != nil {
		return x.Metadata
	}
	return nil
}

func (x *Dataset) GetDataItemCount() int64 {
	if x != nil {
		return x.DataItemCount
	}
	return 0
}

func (x *Dataset) GetCreateTime() *timestamppb.Timestamp {
	if x != nil {
		return x.CreateTime
	}
	return nil
}

func (x *Dataset) GetUpdateTime() *timestamppb.Timestamp {
	if x != nil {
		return x.UpdateTime
	}
	return nil
}

func (x *Dataset) GetEtag() string {
	if x != nil {
		return x.Etag
	}
	return ""
}

func (x *Dataset) GetLabels() map[string]string {
	if x != nil {
		return x.Labels
	}
	return nil
}

func (x *Dataset) GetSavedQueries() []*SavedQuery {
	if x != nil {
		return x.SavedQueries
	}
	return nil
}

func (x *Dataset) GetEncryptionSpec() *EncryptionSpec {
	if x != nil {
		return x.EncryptionSpec
	}
	return nil
}

func (x *Dataset) GetMetadataArtifact() string {
	if x != nil {
		return x.MetadataArtifact
	}
	return ""
}

func (x *Dataset) GetModelReference() string {
	if x != nil {
		return x.ModelReference
	}
	return ""
}

func (x *Dataset) GetSatisfiesPzs() bool {
	if x != nil {
		return x.SatisfiesPzs
	}
	return false
}

func (x *Dataset) GetSatisfiesPzi() bool {
	if x != nil {
		return x.SatisfiesPzi
	}
	return false
}

// Describes the location from where we import data into a Dataset, together
// with the labels that will be applied to the DataItems and the Annotations.
type ImportDataConfig struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The source of the input.
	//
	// Types that are assignable to Source:
	//
	//	*ImportDataConfig_GcsSource
	Source isImportDataConfig_Source `protobuf_oneof:"source"`
	// Labels that will be applied to newly imported DataItems. If an identical
	// DataItem as one being imported already exists in the Dataset, then these
	// labels will be appended to these of the already existing one, and if labels
	// with identical key is imported before, the old label value will be
	// overwritten. If two DataItems are identical in the same import data
	// operation, the labels will be combined and if key collision happens in this
	// case, one of the values will be picked randomly. Two DataItems are
	// considered identical if their content bytes are identical (e.g. image bytes
	// or pdf bytes).
	// These labels will be overridden by Annotation labels specified inside index
	// file referenced by
	// [import_schema_uri][google.cloud.aiplatform.v1.ImportDataConfig.import_schema_uri],
	// e.g. jsonl file.
	DataItemLabels map[string]string `protobuf:"bytes,2,rep,name=data_item_labels,json=dataItemLabels,proto3" json:"data_item_labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
	// Labels that will be applied to newly imported Annotations. If two
	// Annotations are identical, one of them will be deduped. Two Annotations are
	// considered identical if their
	// [payload][google.cloud.aiplatform.v1.Annotation.payload],
	// [payload_schema_uri][google.cloud.aiplatform.v1.Annotation.payload_schema_uri]
	// and all of their [labels][google.cloud.aiplatform.v1.Annotation.labels] are
	// the same. These labels will be overridden by Annotation labels specified
	// inside index file referenced by
	// [import_schema_uri][google.cloud.aiplatform.v1.ImportDataConfig.import_schema_uri],
	// e.g. jsonl file.
	AnnotationLabels map[string]string `protobuf:"bytes,3,rep,name=annotation_labels,json=annotationLabels,proto3" json:"annotation_labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
	// Required. Points to a YAML file stored on Google Cloud Storage describing
	// the import format. Validation will be done against the schema. The schema
	// is defined as an [OpenAPI 3.0.2 Schema
	// Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
	ImportSchemaUri string `protobuf:"bytes,4,opt,name=import_schema_uri,json=importSchemaUri,proto3" json:"import_schema_uri,omitempty"`
}

func (x *ImportDataConfig) Reset() {
	*x = ImportDataConfig{}
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[1]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *ImportDataConfig) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*ImportDataConfig) ProtoMessage() {}

func (x *ImportDataConfig) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[1]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ImportDataConfig.ProtoReflect.Descriptor instead.
func (*ImportDataConfig) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{1}
}

func (m *ImportDataConfig) GetSource() isImportDataConfig_Source {
	if m != nil {
		return m.Source
	}
	return nil
}

func (x *ImportDataConfig) GetGcsSource() *GcsSource {
	if x, ok := x.GetSource().(*ImportDataConfig_GcsSource); ok {
		return x.GcsSource
	}
	return nil
}

func (x *ImportDataConfig) GetDataItemLabels() map[string]string {
	if x != nil {
		return x.DataItemLabels
	}
	return nil
}

func (x *ImportDataConfig) GetAnnotationLabels() map[string]string {
	if x != nil {
		return x.AnnotationLabels
	}
	return nil
}

func (x *ImportDataConfig) GetImportSchemaUri() string {
	if x != nil {
		return x.ImportSchemaUri
	}
	return ""
}

type isImportDataConfig_Source interface {
	isImportDataConfig_Source()
}

type ImportDataConfig_GcsSource struct {
	// The Google Cloud Storage location for the input content.
	GcsSource *GcsSource `protobuf:"bytes,1,opt,name=gcs_source,json=gcsSource,proto3,oneof"`
}

func (*ImportDataConfig_GcsSource) isImportDataConfig_Source() {}

// Describes what part of the Dataset is to be exported, the destination of
// the export and how to export.
type ExportDataConfig struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The destination of the output.
	//
	// Types that are assignable to Destination:
	//
	//	*ExportDataConfig_GcsDestination
	Destination isExportDataConfig_Destination `protobuf_oneof:"destination"`
	// The instructions how the export data should be split between the
	// training, validation and test sets.
	//
	// Types that are assignable to Split:
	//
	//	*ExportDataConfig_FractionSplit
	//	*ExportDataConfig_FilterSplit
	Split isExportDataConfig_Split `protobuf_oneof:"split"`
	// An expression for filtering what part of the Dataset is to be exported.
	// Only Annotations that match this filter will be exported. The filter syntax
	// is the same as in
	// [ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
	AnnotationsFilter string `protobuf:"bytes,2,opt,name=annotations_filter,json=annotationsFilter,proto3" json:"annotations_filter,omitempty"`
	// The ID of a SavedQuery (annotation set) under the Dataset specified by
	// [ExportDataRequest.name][google.cloud.aiplatform.v1.ExportDataRequest.name]
	// used for filtering Annotations for training.
	//
	// Only used for custom training data export use cases.
	// Only applicable to Datasets that have SavedQueries.
	//
	// Only Annotations that are associated with this SavedQuery are used in
	// respectively training. When used in conjunction with
	// [annotations_filter][google.cloud.aiplatform.v1.ExportDataConfig.annotations_filter],
	// the Annotations used for training are filtered by both
	// [saved_query_id][google.cloud.aiplatform.v1.ExportDataConfig.saved_query_id]
	// and
	// [annotations_filter][google.cloud.aiplatform.v1.ExportDataConfig.annotations_filter].
	//
	// Only one of
	// [saved_query_id][google.cloud.aiplatform.v1.ExportDataConfig.saved_query_id]
	// and
	// [annotation_schema_uri][google.cloud.aiplatform.v1.ExportDataConfig.annotation_schema_uri]
	// should be specified as both of them represent the same thing: problem type.
	SavedQueryId string `protobuf:"bytes,11,opt,name=saved_query_id,json=savedQueryId,proto3" json:"saved_query_id,omitempty"`
	// The Cloud Storage URI that points to a YAML file describing the annotation
	// schema. The schema is defined as an OpenAPI 3.0.2 [Schema
	// Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
	// The schema files that can be used here are found in
	// gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the
	// chosen schema must be consistent with
	// [metadata][google.cloud.aiplatform.v1.Dataset.metadata_schema_uri] of the
	// Dataset specified by
	// [ExportDataRequest.name][google.cloud.aiplatform.v1.ExportDataRequest.name].
	//
	// Only used for custom training data export use cases.
	// Only applicable to Datasets that have DataItems and Annotations.
	//
	// Only Annotations that both match this schema and belong to DataItems not
	// ignored by the split method are used in respectively training, validation
	// or test role, depending on the role of the DataItem they are on.
	//
	// When used in conjunction with
	// [annotations_filter][google.cloud.aiplatform.v1.ExportDataConfig.annotations_filter],
	// the Annotations used for training are filtered by both
	// [annotations_filter][google.cloud.aiplatform.v1.ExportDataConfig.annotations_filter]
	// and
	// [annotation_schema_uri][google.cloud.aiplatform.v1.ExportDataConfig.annotation_schema_uri].
	AnnotationSchemaUri string `protobuf:"bytes,12,opt,name=annotation_schema_uri,json=annotationSchemaUri,proto3" json:"annotation_schema_uri,omitempty"`
	// Indicates the usage of the exported files.
	ExportUse ExportDataConfig_ExportUse `protobuf:"varint,4,opt,name=export_use,json=exportUse,proto3,enum=google.cloud.aiplatform.v1.ExportDataConfig_ExportUse" json:"export_use,omitempty"`
}

func (x *ExportDataConfig) Reset() {
	*x = ExportDataConfig{}
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[2]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *ExportDataConfig) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*ExportDataConfig) ProtoMessage() {}

func (x *ExportDataConfig) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[2]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ExportDataConfig.ProtoReflect.Descriptor instead.
func (*ExportDataConfig) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{2}
}

func (m *ExportDataConfig) GetDestination() isExportDataConfig_Destination {
	if m != nil {
		return m.Destination
	}
	return nil
}

func (x *ExportDataConfig) GetGcsDestination() *GcsDestination {
	if x, ok := x.GetDestination().(*ExportDataConfig_GcsDestination); ok {
		return x.GcsDestination
	}
	return nil
}

func (m *ExportDataConfig) GetSplit() isExportDataConfig_Split {
	if m != nil {
		return m.Split
	}
	return nil
}

func (x *ExportDataConfig) GetFractionSplit() *ExportFractionSplit {
	if x, ok := x.GetSplit().(*ExportDataConfig_FractionSplit); ok {
		return x.FractionSplit
	}
	return nil
}

func (x *ExportDataConfig) GetFilterSplit() *ExportFilterSplit {
	if x, ok := x.GetSplit().(*ExportDataConfig_FilterSplit); ok {
		return x.FilterSplit
	}
	return nil
}

func (x *ExportDataConfig) GetAnnotationsFilter() string {
	if x != nil {
		return x.AnnotationsFilter
	}
	return ""
}

func (x *ExportDataConfig) GetSavedQueryId() string {
	if x != nil {
		return x.SavedQueryId
	}
	return ""
}

func (x *ExportDataConfig) GetAnnotationSchemaUri() string {
	if x != nil {
		return x.AnnotationSchemaUri
	}
	return ""
}

func (x *ExportDataConfig) GetExportUse() ExportDataConfig_ExportUse {
	if x != nil {
		return x.ExportUse
	}
	return ExportDataConfig_EXPORT_USE_UNSPECIFIED
}

type isExportDataConfig_Destination interface {
	isExportDataConfig_Destination()
}

type ExportDataConfig_GcsDestination struct {
	// The Google Cloud Storage location where the output is to be written to.
	// In the given directory a new directory will be created with name:
	// `export-data-<dataset-display-name>-<timestamp-of-export-call>` where
	// timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All export
	// output will be written into that directory. Inside that directory,
	// annotations with the same schema will be grouped into sub directories
	// which are named with the corresponding annotations' schema title. Inside
	// these sub directories, a schema.yaml will be created to describe the
	// output format.
	GcsDestination *GcsDestination `protobuf:"bytes,1,opt,name=gcs_destination,json=gcsDestination,proto3,oneof"`
}

func (*ExportDataConfig_GcsDestination) isExportDataConfig_Destination() {}

type isExportDataConfig_Split interface {
	isExportDataConfig_Split()
}

type ExportDataConfig_FractionSplit struct {
	// Split based on fractions defining the size of each set.
	FractionSplit *ExportFractionSplit `protobuf:"bytes,5,opt,name=fraction_split,json=fractionSplit,proto3,oneof"`
}

type ExportDataConfig_FilterSplit struct {
	// Split based on the provided filters for each set.
	FilterSplit *ExportFilterSplit `protobuf:"bytes,7,opt,name=filter_split,json=filterSplit,proto3,oneof"`
}

func (*ExportDataConfig_FractionSplit) isExportDataConfig_Split() {}

func (*ExportDataConfig_FilterSplit) isExportDataConfig_Split() {}

// Assigns the input data to training, validation, and test sets as per the
// given fractions. Any of `training_fraction`, `validation_fraction` and
// `test_fraction` may optionally be provided, they must sum to up to 1. If the
// provided ones sum to less than 1, the remainder is assigned to sets as
// decided by Vertex AI. If none of the fractions are set, by default roughly
// 80% of data is used for training, 10% for validation, and 10% for test.
type ExportFractionSplit struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction float64 `protobuf:"fixed64,1,opt,name=training_fraction,json=trainingFraction,proto3" json:"training_fraction,omitempty"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction float64 `protobuf:"fixed64,2,opt,name=validation_fraction,json=validationFraction,proto3" json:"validation_fraction,omitempty"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction float64 `protobuf:"fixed64,3,opt,name=test_fraction,json=testFraction,proto3" json:"test_fraction,omitempty"`
}

func (x *ExportFractionSplit) Reset() {
	*x = ExportFractionSplit{}
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[3]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *ExportFractionSplit) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*ExportFractionSplit) ProtoMessage() {}

func (x *ExportFractionSplit) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[3]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ExportFractionSplit.ProtoReflect.Descriptor instead.
func (*ExportFractionSplit) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{3}
}

func (x *ExportFractionSplit) GetTrainingFraction() float64 {
	if x != nil {
		return x.TrainingFraction
	}
	return 0
}

func (x *ExportFractionSplit) GetValidationFraction() float64 {
	if x != nil {
		return x.ValidationFraction
	}
	return 0
}

func (x *ExportFractionSplit) GetTestFraction() float64 {
	if x != nil {
		return x.TestFraction
	}
	return 0
}

// Assigns input data to training, validation, and test sets based on the given
// filters, data pieces not matched by any filter are ignored. Currently only
// supported for Datasets containing DataItems.
// If any of the filters in this message are to match nothing, then they can be
// set as '-' (the minus sign).
//
// Supported only for unstructured Datasets.
type ExportFilterSplit struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. A filter on DataItems of the Dataset. DataItems that match
	// this filter are used to train the Model. A filter with same syntax
	// as the one used in
	// [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems]
	// may be used. If a single DataItem is matched by more than one of the
	// FilterSplit filters, then it is assigned to the first set that applies to
	// it in the training, validation, test order.
	TrainingFilter string `protobuf:"bytes,1,opt,name=training_filter,json=trainingFilter,proto3" json:"training_filter,omitempty"`
	// Required. A filter on DataItems of the Dataset. DataItems that match
	// this filter are used to validate the Model. A filter with same syntax
	// as the one used in
	// [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems]
	// may be used. If a single DataItem is matched by more than one of the
	// FilterSplit filters, then it is assigned to the first set that applies to
	// it in the training, validation, test order.
	ValidationFilter string `protobuf:"bytes,2,opt,name=validation_filter,json=validationFilter,proto3" json:"validation_filter,omitempty"`
	// Required. A filter on DataItems of the Dataset. DataItems that match
	// this filter are used to test the Model. A filter with same syntax
	// as the one used in
	// [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems]
	// may be used. If a single DataItem is matched by more than one of the
	// FilterSplit filters, then it is assigned to the first set that applies to
	// it in the training, validation, test order.
	TestFilter string `protobuf:"bytes,3,opt,name=test_filter,json=testFilter,proto3" json:"test_filter,omitempty"`
}

func (x *ExportFilterSplit) Reset() {
	*x = ExportFilterSplit{}
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[4]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *ExportFilterSplit) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*ExportFilterSplit) ProtoMessage() {}

func (x *ExportFilterSplit) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[4]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ExportFilterSplit.ProtoReflect.Descriptor instead.
func (*ExportFilterSplit) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP(), []int{4}
}

func (x *ExportFilterSplit) GetTrainingFilter() string {
	if x != nil {
		return x.TrainingFilter
	}
	return ""
}

func (x *ExportFilterSplit) GetValidationFilter() string {
	if x != nil {
		return x.ValidationFilter
	}
	return ""
}

func (x *ExportFilterSplit) GetTestFilter() string {
	if x != nil {
		return x.TestFilter
	}
	return ""
}

var File_google_cloud_aiplatform_v1_dataset_proto protoreflect.FileDescriptor

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}

var (
	file_google_cloud_aiplatform_v1_dataset_proto_rawDescOnce sync.Once
	file_google_cloud_aiplatform_v1_dataset_proto_rawDescData = file_google_cloud_aiplatform_v1_dataset_proto_rawDesc
)

func file_google_cloud_aiplatform_v1_dataset_proto_rawDescGZIP() []byte {
	file_google_cloud_aiplatform_v1_dataset_proto_rawDescOnce.Do(func() {
		file_google_cloud_aiplatform_v1_dataset_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1_dataset_proto_rawDescData)
	})
	return file_google_cloud_aiplatform_v1_dataset_proto_rawDescData
}

var file_google_cloud_aiplatform_v1_dataset_proto_enumTypes = make([]protoimpl.EnumInfo, 1)
var file_google_cloud_aiplatform_v1_dataset_proto_msgTypes = make([]protoimpl.MessageInfo, 8)
var file_google_cloud_aiplatform_v1_dataset_proto_goTypes = []any{
	(ExportDataConfig_ExportUse)(0), // 0: google.cloud.aiplatform.v1.ExportDataConfig.ExportUse
	(*Dataset)(nil),                 // 1: google.cloud.aiplatform.v1.Dataset
	(*ImportDataConfig)(nil),        // 2: google.cloud.aiplatform.v1.ImportDataConfig
	(*ExportDataConfig)(nil),        // 3: google.cloud.aiplatform.v1.ExportDataConfig
	(*ExportFractionSplit)(nil),     // 4: google.cloud.aiplatform.v1.ExportFractionSplit
	(*ExportFilterSplit)(nil),       // 5: google.cloud.aiplatform.v1.ExportFilterSplit
	nil,                             // 6: google.cloud.aiplatform.v1.Dataset.LabelsEntry
	nil,                             // 7: google.cloud.aiplatform.v1.ImportDataConfig.DataItemLabelsEntry
	nil,                             // 8: google.cloud.aiplatform.v1.ImportDataConfig.AnnotationLabelsEntry
	(*structpb.Value)(nil),          // 9: google.protobuf.Value
	(*timestamppb.Timestamp)(nil),   // 10: google.protobuf.Timestamp
	(*SavedQuery)(nil),              // 11: google.cloud.aiplatform.v1.SavedQuery
	(*EncryptionSpec)(nil),          // 12: google.cloud.aiplatform.v1.EncryptionSpec
	(*GcsSource)(nil),               // 13: google.cloud.aiplatform.v1.GcsSource
	(*GcsDestination)(nil),          // 14: google.cloud.aiplatform.v1.GcsDestination
}
var file_google_cloud_aiplatform_v1_dataset_proto_depIdxs = []int32{
	9,  // 0: google.cloud.aiplatform.v1.Dataset.metadata:type_name -> google.protobuf.Value
	10, // 1: google.cloud.aiplatform.v1.Dataset.create_time:type_name -> google.protobuf.Timestamp
	10, // 2: google.cloud.aiplatform.v1.Dataset.update_time:type_name -> google.protobuf.Timestamp
	6,  // 3: google.cloud.aiplatform.v1.Dataset.labels:type_name -> google.cloud.aiplatform.v1.Dataset.LabelsEntry
	11, // 4: google.cloud.aiplatform.v1.Dataset.saved_queries:type_name -> google.cloud.aiplatform.v1.SavedQuery
	12, // 5: google.cloud.aiplatform.v1.Dataset.encryption_spec:type_name -> google.cloud.aiplatform.v1.EncryptionSpec
	13, // 6: google.cloud.aiplatform.v1.ImportDataConfig.gcs_source:type_name -> google.cloud.aiplatform.v1.GcsSource
	7,  // 7: google.cloud.aiplatform.v1.ImportDataConfig.data_item_labels:type_name -> google.cloud.aiplatform.v1.ImportDataConfig.DataItemLabelsEntry
	8,  // 8: google.cloud.aiplatform.v1.ImportDataConfig.annotation_labels:type_name -> google.cloud.aiplatform.v1.ImportDataConfig.AnnotationLabelsEntry
	14, // 9: google.cloud.aiplatform.v1.ExportDataConfig.gcs_destination:type_name -> google.cloud.aiplatform.v1.GcsDestination
	4,  // 10: google.cloud.aiplatform.v1.ExportDataConfig.fraction_split:type_name -> google.cloud.aiplatform.v1.ExportFractionSplit
	5,  // 11: google.cloud.aiplatform.v1.ExportDataConfig.filter_split:type_name -> google.cloud.aiplatform.v1.ExportFilterSplit
	0,  // 12: google.cloud.aiplatform.v1.ExportDataConfig.export_use:type_name -> google.cloud.aiplatform.v1.ExportDataConfig.ExportUse
	13, // [13:13] is the sub-list for method output_type
	13, // [13:13] is the sub-list for method input_type
	13, // [13:13] is the sub-list for extension type_name
	13, // [13:13] is the sub-list for extension extendee
	0,  // [0:13] is the sub-list for field type_name
}

func init() { file_google_cloud_aiplatform_v1_dataset_proto_init() }
func file_google_cloud_aiplatform_v1_dataset_proto_init() {
	if File_google_cloud_aiplatform_v1_dataset_proto != nil {
		return
	}
	file_google_cloud_aiplatform_v1_encryption_spec_proto_init()
	file_google_cloud_aiplatform_v1_io_proto_init()
	file_google_cloud_aiplatform_v1_saved_query_proto_init()
	file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[1].OneofWrappers = []any{
		(*ImportDataConfig_GcsSource)(nil),
	}
	file_google_cloud_aiplatform_v1_dataset_proto_msgTypes[2].OneofWrappers = []any{
		(*ExportDataConfig_GcsDestination)(nil),
		(*ExportDataConfig_FractionSplit)(nil),
		(*ExportDataConfig_FilterSplit)(nil),
	}
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: file_google_cloud_aiplatform_v1_dataset_proto_rawDesc,
			NumEnums:      1,
			NumMessages:   8,
			NumExtensions: 0,
			NumServices:   0,
		},
		GoTypes:           file_google_cloud_aiplatform_v1_dataset_proto_goTypes,
		DependencyIndexes: file_google_cloud_aiplatform_v1_dataset_proto_depIdxs,
		EnumInfos:         file_google_cloud_aiplatform_v1_dataset_proto_enumTypes,
		MessageInfos:      file_google_cloud_aiplatform_v1_dataset_proto_msgTypes,
	}.Build()
	File_google_cloud_aiplatform_v1_dataset_proto = out.File
	file_google_cloud_aiplatform_v1_dataset_proto_rawDesc = nil
	file_google_cloud_aiplatform_v1_dataset_proto_goTypes = nil
	file_google_cloud_aiplatform_v1_dataset_proto_depIdxs = nil
}
