Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ExportDataConfig (v0.53.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ExportDataConfig.

Describes what part of the Dataset is to be exported, the destination of the export and how to export.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#annotation_schema_uri

def annotation_schema_uri() -> ::String
Returns
  • (::String) — 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. 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 of the Dataset specified by [dataset_id][].

    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, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

#annotation_schema_uri=

def annotation_schema_uri=(value) -> ::String
Parameter
  • value (::String) — 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. 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 of the Dataset specified by [dataset_id][].

    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, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

Returns
  • (::String) — 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. 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 of the Dataset specified by [dataset_id][].

    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, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

#annotations_filter

def annotations_filter() -> ::String
Returns
  • (::String) — 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.

#annotations_filter=

def annotations_filter=(value) -> ::String
Parameter
  • value (::String) — 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.
Returns
  • (::String) — 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.

#export_use

def export_use() -> ::Google::Cloud::AIPlatform::V1::ExportDataConfig::ExportUse
Returns

#export_use=

def export_use=(value) -> ::Google::Cloud::AIPlatform::V1::ExportDataConfig::ExportUse
Parameter
Returns

#filter_split

def filter_split() -> ::Google::Cloud::AIPlatform::V1::ExportFilterSplit
Returns

#filter_split=

def filter_split=(value) -> ::Google::Cloud::AIPlatform::V1::ExportFilterSplit
Parameter
Returns

#fraction_split

def fraction_split() -> ::Google::Cloud::AIPlatform::V1::ExportFractionSplit
Returns

#fraction_split=

def fraction_split=(value) -> ::Google::Cloud::AIPlatform::V1::ExportFractionSplit
Parameter
Returns

#gcs_destination

def gcs_destination() -> ::Google::Cloud::AIPlatform::V1::GcsDestination
Returns
  • (::Google::Cloud::AIPlatform::V1::GcsDestination) — 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.

#gcs_destination=

def gcs_destination=(value) -> ::Google::Cloud::AIPlatform::V1::GcsDestination
Parameter
  • value (::Google::Cloud::AIPlatform::V1::GcsDestination) — 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.
Returns
  • (::Google::Cloud::AIPlatform::V1::GcsDestination) — 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.

#saved_query_id

def saved_query_id() -> ::String
Returns
  • (::String) — The ID of a SavedQuery (annotation set) under the Dataset specified by [dataset_id][] 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, the Annotations used for training are filtered by both saved_query_id and annotations_filter.

    Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

#saved_query_id=

def saved_query_id=(value) -> ::String
Parameter
  • value (::String) — The ID of a SavedQuery (annotation set) under the Dataset specified by [dataset_id][] 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, the Annotations used for training are filtered by both saved_query_id and annotations_filter.

    Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

Returns
  • (::String) — The ID of a SavedQuery (annotation set) under the Dataset specified by [dataset_id][] 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, the Annotations used for training are filtered by both saved_query_id and annotations_filter.

    Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.