📄 Source: GoogleCloudAiplatformV1InputDataConfig.php
<?php
/*
* Copyright 2014 Google Inc.
*
* 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.
*/
namespace Google\Service\Aiplatform;
class GoogleCloudAiplatformV1InputDataConfig extends \Google\Model
{
/**
* 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](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 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.
*
* @var string
*/
public $annotationSchemaUri;
/**
* 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.
*
* @var string
*/
public $annotationsFilter;
protected $bigqueryDestinationType = GoogleCloudAiplatformV1BigQueryDestination::class;
protected $bigqueryDestinationDataType = '';
/**
* 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.
*
* @var string
*/
public $datasetId;
protected $filterSplitType = GoogleCloudAiplatformV1FilterSplit::class;
protected $filterSplitDataType = '';
protected $fractionSplitType = GoogleCloudAiplatformV1FractionSplit::class;
protected $fractionSplitDataType = '';
protected $gcsDestinationType = GoogleCloudAiplatformV1GcsDestination::class;
protected $gcsDestinationDataType = '';
/**
* Whether to persist the ML use assignment to data item system labels.
*
* @var bool
*/
public $persistMlUseAssignment;
protected $predefinedSplitType = GoogleCloudAiplatformV1PredefinedSplit::class;
protected $predefinedSplitDataType = '';
/**
* 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.
*
* @var string
*/
public $savedQueryId;
protected $stratifiedSplitType = GoogleCloudAiplatformV1StratifiedSplit::class;
protected $stratifiedSplitDataType = '';
protected $timestampSplitType = GoogleCloudAiplatformV1TimestampSplit::class;
protected $timestampSplitDataType = '';
/**
* 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](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 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.
*
* @param string $annotationSchemaUri
*/
public function setAnnotationSchemaUri($annotationSchemaUri)
{
$this->annotationSchemaUri = $annotationSchemaUri;
}
/**
* @return string
*/
public function getAnnotationSchemaUri()
{
return $this->annotationSchemaUri;
}
/**
* 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.
*
* @param string $annotationsFilter
*/
public function setAnnotationsFilter($annotationsFilter)
{
$this->annotationsFilter = $annotationsFilter;
}
/**
* @return string
*/
public function getAnnotationsFilter()
{
return $this->annotationsFilter;
}
/**
* Only applicable to custom training with tabular Dataset with BigQuery
* source. The BigQuery project location where the training data is to be
* written to. In the given project a new dataset is created with name
* `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All
* training input data is written into that dataset. In the dataset three
* tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT
* = "bigquery". * AIP_TRAINING_DATA_URI =
* "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI =
* "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI =
* "bigquery_destination.dataset___.test"
*
* @param GoogleCloudAiplatformV1BigQueryDestination $bigqueryDestination
*/
public function setBigqueryDestination(GoogleCloudAiplatformV1BigQueryDestination $bigqueryDestination)
{
$this->bigqueryDestination = $bigqueryDestination;
}
/**
* @return GoogleCloudAiplatformV1BigQueryDestination
*/
public function getBigqueryDestination()
{
return $this->bigqueryDestination;
}
/**
* 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.
*
* @param string $datasetId
*/
public function setDatasetId($datasetId)
{
$this->datasetId = $datasetId;
}
/**
* @return string
*/
public function getDatasetId()
{
return $this->datasetId;
}
/**
* Split based on the provided filters for each set.
*
* @param GoogleCloudAiplatformV1FilterSplit $filterSplit
*/
public function setFilterSplit(GoogleCloudAiplatformV1FilterSplit $filterSplit)
{
$this->filterSplit = $filterSplit;
}
/**
* @return GoogleCloudAiplatformV1FilterSplit
*/
public function getFilterSplit()
{
return $this->filterSplit;
}
/**
* Split based on fractions defining the size of each set.
*
* @param GoogleCloudAiplatformV1FractionSplit $fractionSplit
*/
public function setFractionSplit(GoogleCloudAiplatformV1FractionSplit $fractionSplit)
{
$this->fractionSplit = $fractionSplit;
}
/**
* @return GoogleCloudAiplatformV1FractionSplit
*/
public function getFractionSplit()
{
return $this->fractionSplit;
}
/**
* The Cloud Storage location where the training data is to be written to. In
* the given directory a new directory is created with name: `dataset---`
* where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All
* training input data is written into that directory. The Vertex AI
* environment variables representing Cloud Storage data URIs are represented
* in the Cloud Storage wildcard format to support sharded data. e.g.:
* "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular
* data, "csv" for tabular data * AIP_TRAINING_DATA_URI =
* "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" *
* AIP_VALIDATION_DATA_URI =
* "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" *
* AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"
*
* @param GoogleCloudAiplatformV1GcsDestination $gcsDestination
*/
public function setGcsDestination(GoogleCloudAiplatformV1GcsDestination $gcsDestination)
{
$this->gcsDestination = $gcsDestination;
}
/**
* @return GoogleCloudAiplatformV1GcsDestination
*/
public function getGcsDestination()
{
return $this->gcsDestination;
}
/**
* Whether to persist the ML use assignment to data item system labels.
*
* @param bool $persistMlUseAssignment
*/
public function setPersistMlUseAssignment($persistMlUseAssignment)
{
$this->persistMlUseAssignment = $persistMlUseAssignment;
}
/**
* @return bool
*/
public function getPersistMlUseAssignment()
{
return $this->persistMlUseAssignment;
}
/**
* Supported only for tabular Datasets. Split based on a predefined key.
*
* @param GoogleCloudAiplatformV1PredefinedSplit $predefinedSplit
*/
public function setPredefinedSplit(GoogleCloudAiplatformV1PredefinedSplit $predefinedSplit)
{
$this->predefinedSplit = $predefinedSplit;
}
/**
* @return GoogleCloudAiplatformV1PredefinedSplit
*/
public function getPredefinedSplit()
{
return $this->predefinedSplit;
}
/**
* 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.
*
* @param string $savedQueryId
*/
public function setSavedQueryId($savedQueryId)
{
$this->savedQueryId = $savedQueryId;
}
/**
* @return string
*/
public function getSavedQueryId()
{
return $this->savedQueryId;
}
/**
* Supported only for tabular Datasets. Split based on the distribution of the
* specified column.
*
* @param GoogleCloudAiplatformV1StratifiedSplit $stratifiedSplit
*/
public function setStratifiedSplit(GoogleCloudAiplatformV1StratifiedSplit $stratifiedSplit)
{
$this->stratifiedSplit = $stratifiedSplit;
}
/**
* @return GoogleCloudAiplatformV1StratifiedSplit
*/
public function getStratifiedSplit()
{
return $this->stratifiedSplit;
}
/**
* Supported only for tabular Datasets. Split based on the timestamp of the
* input data pieces.
*
* @param GoogleCloudAiplatformV1TimestampSplit $timestampSplit
*/
public function setTimestampSplit(GoogleCloudAiplatformV1TimestampSplit $timestampSplit)
{
$this->timestampSplit = $timestampSplit;
}
/**
* @return GoogleCloudAiplatformV1TimestampSplit
*/
public function getTimestampSplit()
{
return $this->timestampSplit;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1InputDataConfig::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1InputDataConfig');
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