Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1InputDataConfig

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb

Overview

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1InputDataConfig

Returns a new instance of GoogleCloudAiplatformV1InputDataConfig.



19012
19013
19014
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19012

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#annotation_schema_uri ⇒ String

Applicable only to custom training with Datasets that have DataItems and Annotations. 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 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. Corresponds to the JSON property annotationSchemaUri

Returns:

  • (String) 


18912
18913
18914
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18912

def annotation_schema_uri
  @annotation_schema_uri
end

#annotations_filter ⇒ String

Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter 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 (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem. Corresponds to the JSON property annotationsFilter

Returns:

  • (String) 


18924
18925
18926
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18924

def annotations_filter
  @annotations_filter
end

#bigquery_destination ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1BigQueryDestination

The BigQuery location for the output content. Corresponds to the JSON property bigqueryDestination

Returns:



18929
18930
18931
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18929

def bigquery_destination
  @bigquery_destination
end

#dataset_id ⇒ String

Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from. Corresponds to the JSON property datasetId

Returns:

  • (String) 


18938
18939
18940
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18938

def dataset_id
  @dataset_id
end

#filter_split ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1FilterSplit

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. Corresponds to the JSON property filterSplit

Returns:



18947
18948
18949
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18947

def filter_split
  @filter_split
end

#fraction_split ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1FractionSplit

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. Corresponds to the JSON property fractionSplit

Returns:



18957
18958
18959
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18957

def fraction_split
  @fraction_split
end

#gcs_destination ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1GcsDestination

The Google Cloud Storage location where the output is to be written to. Corresponds to the JSON property gcsDestination

Returns:



18962
18963
18964
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18962

def gcs_destination
  @gcs_destination
end

#persist_ml_use_assignment ⇒ Boolean Also known as: persist_ml_use_assignment?

Whether to persist the ML use assignment to data item system labels. Corresponds to the JSON property persistMlUseAssignment

Returns:

  • (Boolean) 


18967
18968
18969
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18967

def persist_ml_use_assignment
  @persist_ml_use_assignment
end

#predefined_split ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1PredefinedSplit

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets. Corresponds to the JSON property predefinedSplit

Returns:



18974
18975
18976
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18974

def predefined_split
  @predefined_split
end

#saved_query_id ⇒ String

Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery ( annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. 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. Corresponds to the JSON property savedQueryId

Returns:

  • (String) 


18986
18987
18988
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 18986

def saved_query_id
  @saved_query_id
end

#stratified_split ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1StratifiedSplit

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the key field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C" , and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets. Corresponds to the JSON property stratifiedSplit

Returns:



19002
19003
19004
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19002

def stratified_split
  @stratified_split
end

#timestamp_split ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1TimestampSplit

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets. Corresponds to the JSON property timestampSplit

Returns:



19010
19011
19012
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19010

def timestamp_split
  @timestamp_split
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



19017
19018
19019
19020
19021
19022
19023
19024
19025
19026
19027
19028
19029
19030
 
# File 'lib/google/apis/aiplatform_v1/classes.rb', line 19017

def update!(**args)
  @annotation_schema_uri = args[:annotation_schema_uri] if args.key?(:annotation_schema_uri)
  @annotations_filter = args[:annotations_filter] if args.key?(:annotations_filter)
  @bigquery_destination = args[:bigquery_destination] if args.key?(:bigquery_destination)
  @dataset_id = args[:dataset_id] if args.key?(:dataset_id)
  @filter_split = args[:filter_split] if args.key?(:filter_split)
  @fraction_split = args[:fraction_split] if args.key?(:fraction_split)
  @gcs_destination = args[:gcs_destination] if args.key?(:gcs_destination)
  @persist_ml_use_assignment = args[:persist_ml_use_assignment] if args.key?(:persist_ml_use_assignment)
  @predefined_split = args[:predefined_split] if args.key?(:predefined_split)
  @saved_query_id = args[:saved_query_id] if args.key?(:saved_query_id)
  @stratified_split = args[:stratified_split] if args.key?(:stratified_split)
  @timestamp_split = args[:timestamp_split] if args.key?(:timestamp_split)
end