📄 Source: Model.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\Bigquery;
class Model extends \Google\Collection
{
/**
* Default value.
*/
public const MODEL_TYPE_MODEL_TYPE_UNSPECIFIED = 'MODEL_TYPE_UNSPECIFIED';
/**
* Linear regression model.
*/
public const MODEL_TYPE_LINEAR_REGRESSION = 'LINEAR_REGRESSION';
/**
* Logistic regression based classification model.
*/
public const MODEL_TYPE_LOGISTIC_REGRESSION = 'LOGISTIC_REGRESSION';
/**
* K-means clustering model.
*/
public const MODEL_TYPE_KMEANS = 'KMEANS';
/**
* Matrix factorization model.
*/
public const MODEL_TYPE_MATRIX_FACTORIZATION = 'MATRIX_FACTORIZATION';
/**
* DNN classifier model.
*/
public const MODEL_TYPE_DNN_CLASSIFIER = 'DNN_CLASSIFIER';
/**
* An imported TensorFlow model.
*/
public const MODEL_TYPE_TENSORFLOW = 'TENSORFLOW';
/**
* DNN regressor model.
*/
public const MODEL_TYPE_DNN_REGRESSOR = 'DNN_REGRESSOR';
/**
* An imported XGBoost model.
*/
public const MODEL_TYPE_XGBOOST = 'XGBOOST';
/**
* Boosted tree regressor model.
*/
public const MODEL_TYPE_BOOSTED_TREE_REGRESSOR = 'BOOSTED_TREE_REGRESSOR';
/**
* Boosted tree classifier model.
*/
public const MODEL_TYPE_BOOSTED_TREE_CLASSIFIER = 'BOOSTED_TREE_CLASSIFIER';
/**
* ARIMA model.
*/
public const MODEL_TYPE_ARIMA = 'ARIMA';
/**
* AutoML Tables regression model.
*/
public const MODEL_TYPE_AUTOML_REGRESSOR = 'AUTOML_REGRESSOR';
/**
* AutoML Tables classification model.
*/
public const MODEL_TYPE_AUTOML_CLASSIFIER = 'AUTOML_CLASSIFIER';
/**
* Prinpical Component Analysis model.
*/
public const MODEL_TYPE_PCA = 'PCA';
/**
* Wide-and-deep classifier model.
*/
public const MODEL_TYPE_DNN_LINEAR_COMBINED_CLASSIFIER = 'DNN_LINEAR_COMBINED_CLASSIFIER';
/**
* Wide-and-deep regressor model.
*/
public const MODEL_TYPE_DNN_LINEAR_COMBINED_REGRESSOR = 'DNN_LINEAR_COMBINED_REGRESSOR';
/**
* Autoencoder model.
*/
public const MODEL_TYPE_AUTOENCODER = 'AUTOENCODER';
/**
* New name for the ARIMA model.
*/
public const MODEL_TYPE_ARIMA_PLUS = 'ARIMA_PLUS';
/**
* ARIMA with external regressors.
*/
public const MODEL_TYPE_ARIMA_PLUS_XREG = 'ARIMA_PLUS_XREG';
/**
* Random forest regressor model.
*/
public const MODEL_TYPE_RANDOM_FOREST_REGRESSOR = 'RANDOM_FOREST_REGRESSOR';
/**
* Random forest classifier model.
*/
public const MODEL_TYPE_RANDOM_FOREST_CLASSIFIER = 'RANDOM_FOREST_CLASSIFIER';
/**
* An imported TensorFlow Lite model.
*/
public const MODEL_TYPE_TENSORFLOW_LITE = 'TENSORFLOW_LITE';
/**
* An imported ONNX model.
*/
public const MODEL_TYPE_ONNX = 'ONNX';
/**
* Model to capture the columns and logic in the TRANSFORM clause along with
* statistics useful for ML analytic functions.
*/
public const MODEL_TYPE_TRANSFORM_ONLY = 'TRANSFORM_ONLY';
/**
* The contribution analysis model.
*/
public const MODEL_TYPE_CONTRIBUTION_ANALYSIS = 'CONTRIBUTION_ANALYSIS';
protected $collection_key = 'transformColumns';
/**
* The best trial_id across all training runs.
*
* @deprecated
* @var string
*/
public $bestTrialId;
/**
* Output only. The time when this model was created, in millisecs since the
* epoch.
*
* @var string
*/
public $creationTime;
/**
* Output only. The default trial_id to use in TVFs when the trial_id is not
* passed in. For single-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best trial
* ID. For multi-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, this is the smallest
* trial ID among all Pareto optimal trials.
*
* @var string
*/
public $defaultTrialId;
/**
* Optional. A user-friendly description of this model.
*
* @var string
*/
public $description;
protected $encryptionConfigurationType = EncryptionConfiguration::class;
protected $encryptionConfigurationDataType = '';
/**
* Output only. A hash of this resource.
*
* @var string
*/
public $etag;
/**
* Optional. The time when this model expires, in milliseconds since the
* epoch. If not present, the model will persist indefinitely. Expired models
* will be deleted and their storage reclaimed. The defaultTableExpirationMs
* property of the encapsulating dataset can be used to set a default
* expirationTime on newly created models.
*
* @var string
*/
public $expirationTime;
protected $featureColumnsType = StandardSqlField::class;
protected $featureColumnsDataType = 'array';
/**
* Optional. A descriptive name for this model.
*
* @var string
*/
public $friendlyName;
protected $hparamSearchSpacesType = HparamSearchSpaces::class;
protected $hparamSearchSpacesDataType = '';
protected $hparamTrialsType = HparamTuningTrial::class;
protected $hparamTrialsDataType = 'array';
protected $labelColumnsType = StandardSqlField::class;
protected $labelColumnsDataType = 'array';
/**
* The labels associated with this model. You can use these to organize and
* group your models. Label keys and values can be no longer than 63
* characters, can only contain lowercase letters, numeric characters,
* underscores and dashes. International characters are allowed. Label values
* are optional. Label keys must start with a letter and each label in the
* list must have a different key.
*
* @var string[]
*/
public $labels;
/**
* Output only. The time when this model was last modified, in millisecs since
* the epoch.
*
* @var string
*/
public $lastModifiedTime;
/**
* Output only. The geographic location where the model resides. This value is
* inherited from the dataset.
*
* @var string
*/
public $location;
protected $modelReferenceType = ModelReference::class;
protected $modelReferenceDataType = '';
/**
* Output only. Type of the model resource.
*
* @var string
*/
public $modelType;
/**
* Output only. For single-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best
* trial. For multi-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all Pareto
* optimal trials sorted by trial_id.
*
* @var string[]
*/
public $optimalTrialIds;
protected $remoteModelInfoType = RemoteModelInfo::class;
protected $remoteModelInfoDataType = '';
protected $trainingRunsType = TrainingRun::class;
protected $trainingRunsDataType = 'array';
protected $transformColumnsType = TransformColumn::class;
protected $transformColumnsDataType = 'array';
/**
* The best trial_id across all training runs.
*
* @deprecated
* @param string $bestTrialId
*/
public function setBestTrialId($bestTrialId)
{
$this->bestTrialId = $bestTrialId;
}
/**
* @deprecated
* @return string
*/
public function getBestTrialId()
{
return $this->bestTrialId;
}
/**
* Output only. The time when this model was created, in millisecs since the
* epoch.
*
* @param string $creationTime
*/
public function setCreationTime($creationTime)
{
$this->creationTime = $creationTime;
}
/**
* @return string
*/
public function getCreationTime()
{
return $this->creationTime;
}
/**
* Output only. The default trial_id to use in TVFs when the trial_id is not
* passed in. For single-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best trial
* ID. For multi-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, this is the smallest
* trial ID among all Pareto optimal trials.
*
* @param string $defaultTrialId
*/
public function setDefaultTrialId($defaultTrialId)
{
$this->defaultTrialId = $defaultTrialId;
}
/**
* @return string
*/
public function getDefaultTrialId()
{
return $this->defaultTrialId;
}
/**
* Optional. A user-friendly description of this model.
*
* @param string $description
*/
public function setDescription($description)
{
$this->description = $description;
}
/**
* @return string
*/
public function getDescription()
{
return $this->description;
}
/**
* Custom encryption configuration (e.g., Cloud KMS keys). This shows the
* encryption configuration of the model data while stored in BigQuery
* storage. This field can be used with PatchModel to update encryption key
* for an already encrypted model.
*
* @param EncryptionConfiguration $encryptionConfiguration
*/
public function setEncryptionConfiguration(EncryptionConfiguration $encryptionConfiguration)
{
$this->encryptionConfiguration = $encryptionConfiguration;
}
/**
* @return EncryptionConfiguration
*/
public function getEncryptionConfiguration()
{
return $this->encryptionConfiguration;
}
/**
* Output only. A hash of this resource.
*
* @param string $etag
*/
public function setEtag($etag)
{
$this->etag = $etag;
}
/**
* @return string
*/
public function getEtag()
{
return $this->etag;
}
/**
* Optional. The time when this model expires, in milliseconds since the
* epoch. If not present, the model will persist indefinitely. Expired models
* will be deleted and their storage reclaimed. The defaultTableExpirationMs
* property of the encapsulating dataset can be used to set a default
* expirationTime on newly created models.
*
* @param string $expirationTime
*/
public function setExpirationTime($expirationTime)
{
$this->expirationTime = $expirationTime;
}
/**
* @return string
*/
public function getExpirationTime()
{
return $this->expirationTime;
}
/**
* Output only. Input feature columns for the model inference. If the model is
* trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
*
* @param StandardSqlField[] $featureColumns
*/
public function setFeatureColumns($featureColumns)
{
$this->featureColumns = $featureColumns;
}
/**
* @return StandardSqlField[]
*/
public function getFeatureColumns()
{
return $this->featureColumns;
}
/**
* Optional. A descriptive name for this model.
*
* @param string $friendlyName
*/
public function setFriendlyName($friendlyName)
{
$this->friendlyName = $friendlyName;
}
/**
* @return string
*/
public function getFriendlyName()
{
return $this->friendlyName;
}
/**
* Output only. All hyperparameter search spaces in this model.
*
* @param HparamSearchSpaces $hparamSearchSpaces
*/
public function setHparamSearchSpaces(HparamSearchSpaces $hparamSearchSpaces)
{
$this->hparamSearchSpaces = $hparamSearchSpaces;
}
/**
* @return HparamSearchSpaces
*/
public function getHparamSearchSpaces()
{
return $this->hparamSearchSpaces;
}
/**
* Output only. Trials of a [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) model sorted by trial_id.
*
* @param HparamTuningTrial[] $hparamTrials
*/
public function setHparamTrials($hparamTrials)
{
$this->hparamTrials = $hparamTrials;
}
/**
* @return HparamTuningTrial[]
*/
public function getHparamTrials()
{
return $this->hparamTrials;
}
/**
* Output only. Label columns that were used to train this model. The output
* of the model will have a "predicted_" prefix to these columns.
*
* @param StandardSqlField[] $labelColumns
*/
public function setLabelColumns($labelColumns)
{
$this->labelColumns = $labelColumns;
}
/**
* @return StandardSqlField[]
*/
public function getLabelColumns()
{
return $this->labelColumns;
}
/**
* The labels associated with this model. You can use these to organize and
* group your models. Label keys and values can be no longer than 63
* characters, can only contain lowercase letters, numeric characters,
* underscores and dashes. International characters are allowed. Label values
* are optional. Label keys must start with a letter and each label in the
* list must have a different key.
*
* @param string[] $labels
*/
public function setLabels($labels)
{
$this->labels = $labels;
}
/**
* @return string[]
*/
public function getLabels()
{
return $this->labels;
}
/**
* Output only. The time when this model was last modified, in millisecs since
* the epoch.
*
* @param string $lastModifiedTime
*/
public function setLastModifiedTime($lastModifiedTime)
{
$this->lastModifiedTime = $lastModifiedTime;
}
/**
* @return string
*/
public function getLastModifiedTime()
{
return $this->lastModifiedTime;
}
/**
* Output only. The geographic location where the model resides. This value is
* inherited from the dataset.
*
* @param string $location
*/
public function setLocation($location)
{
$this->location = $location;
}
/**
* @return string
*/
public function getLocation()
{
return $this->location;
}
/**
* Required. Unique identifier for this model.
*
* @param ModelReference $modelReference
*/
public function setModelReference(ModelReference $modelReference)
{
$this->modelReference = $modelReference;
}
/**
* @return ModelReference
*/
public function getModelReference()
{
return $this->modelReference;
}
/**
* Output only. Type of the model resource.
*
* Accepted values: MODEL_TYPE_UNSPECIFIED, LINEAR_REGRESSION,
* LOGISTIC_REGRESSION, KMEANS, MATRIX_FACTORIZATION, DNN_CLASSIFIER,
* TENSORFLOW, DNN_REGRESSOR, XGBOOST, BOOSTED_TREE_REGRESSOR,
* BOOSTED_TREE_CLASSIFIER, ARIMA, AUTOML_REGRESSOR, AUTOML_CLASSIFIER, PCA,
* DNN_LINEAR_COMBINED_CLASSIFIER, DNN_LINEAR_COMBINED_REGRESSOR, AUTOENCODER,
* ARIMA_PLUS, ARIMA_PLUS_XREG, RANDOM_FOREST_REGRESSOR,
* RANDOM_FOREST_CLASSIFIER, TENSORFLOW_LITE, ONNX, TRANSFORM_ONLY,
* CONTRIBUTION_ANALYSIS
*
* @param self::MODEL_TYPE_* $modelType
*/
public function setModelType($modelType)
{
$this->modelType = $modelType;
}
/**
* @return self::MODEL_TYPE_*
*/
public function getModelType()
{
return $this->modelType;
}
/**
* Output only. For single-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best
* trial. For multi-objective [hyperparameter
* tuning](https://cloud.google.com/bigquery-ml/docs/reference/standard-
* sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all Pareto
* optimal trials sorted by trial_id.
*
* @param string[] $optimalTrialIds
*/
public function setOptimalTrialIds($optimalTrialIds)
{
$this->optimalTrialIds = $optimalTrialIds;
}
/**
* @return string[]
*/
public function getOptimalTrialIds()
{
return $this->optimalTrialIds;
}
/**
* Output only. Remote model info
*
* @param RemoteModelInfo $remoteModelInfo
*/
public function setRemoteModelInfo(RemoteModelInfo $remoteModelInfo)
{
$this->remoteModelInfo = $remoteModelInfo;
}
/**
* @return RemoteModelInfo
*/
public function getRemoteModelInfo()
{
return $this->remoteModelInfo;
}
/**
* Information for all training runs in increasing order of start_time.
*
* @param TrainingRun[] $trainingRuns
*/
public function setTrainingRuns($trainingRuns)
{
$this->trainingRuns = $trainingRuns;
}
/**
* @return TrainingRun[]
*/
public function getTrainingRuns()
{
return $this->trainingRuns;
}
/**
* Output only. This field will be populated if a TRANSFORM clause was used to
* train a model. TRANSFORM clause (if used) takes feature_columns as input
* and outputs transform_columns. transform_columns then are used to train the
* model.
*
* @param TransformColumn[] $transformColumns
*/
public function setTransformColumns($transformColumns)
{
$this->transformColumns = $transformColumns;
}
/**
* @return TransformColumn[]
*/
public function getTransformColumns()
{
return $this->transformColumns;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(Model::class, 'Google_Service_Bigquery_Model');
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