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<?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 GoogleCloudAiplatformV1ModelDeploymentMonitoringJob extends \Google\Collection
{
/**
* Unspecified state.
*/
public const SCHEDULE_STATE_MONITORING_SCHEDULE_STATE_UNSPECIFIED = 'MONITORING_SCHEDULE_STATE_UNSPECIFIED';
/**
* The pipeline is picked up and wait to run.
*/
public const SCHEDULE_STATE_PENDING = 'PENDING';
/**
* The pipeline is offline and will be scheduled for next run.
*/
public const SCHEDULE_STATE_OFFLINE = 'OFFLINE';
/**
* The pipeline is running.
*/
public const SCHEDULE_STATE_RUNNING = 'RUNNING';
/**
* The job state is unspecified.
*/
public const STATE_JOB_STATE_UNSPECIFIED = 'JOB_STATE_UNSPECIFIED';
/**
* The job has been just created or resumed and processing has not yet begun.
*/
public const STATE_JOB_STATE_QUEUED = 'JOB_STATE_QUEUED';
/**
* The service is preparing to run the job.
*/
public const STATE_JOB_STATE_PENDING = 'JOB_STATE_PENDING';
/**
* The job is in progress.
*/
public const STATE_JOB_STATE_RUNNING = 'JOB_STATE_RUNNING';
/**
* The job completed successfully.
*/
public const STATE_JOB_STATE_SUCCEEDED = 'JOB_STATE_SUCCEEDED';
/**
* The job failed.
*/
public const STATE_JOB_STATE_FAILED = 'JOB_STATE_FAILED';
/**
* The job is being cancelled. From this state the job may only go to either
* `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
*/
public const STATE_JOB_STATE_CANCELLING = 'JOB_STATE_CANCELLING';
/**
* The job has been cancelled.
*/
public const STATE_JOB_STATE_CANCELLED = 'JOB_STATE_CANCELLED';
/**
* The job has been stopped, and can be resumed.
*/
public const STATE_JOB_STATE_PAUSED = 'JOB_STATE_PAUSED';
/**
* The job has expired.
*/
public const STATE_JOB_STATE_EXPIRED = 'JOB_STATE_EXPIRED';
/**
* The job is being updated. Only jobs in the `RUNNING` state can be updated.
* After updating, the job goes back to the `RUNNING` state.
*/
public const STATE_JOB_STATE_UPDATING = 'JOB_STATE_UPDATING';
/**
* The job is partially succeeded, some results may be missing due to errors.
*/
public const STATE_JOB_STATE_PARTIALLY_SUCCEEDED = 'JOB_STATE_PARTIALLY_SUCCEEDED';
protected $collection_key = 'modelDeploymentMonitoringObjectiveConfigs';
/**
* YAML schema file uri describing the format of a single instance that you
* want Tensorflow Data Validation (TFDV) to analyze. If this field is empty,
* all the feature data types are inferred from predict_instance_schema_uri,
* meaning that TFDV will use the data in the exact format(data type) as
* prediction request/response. If there are any data type differences between
* predict instance and TFDV instance, this field can be used to override the
* schema. For models trained with Vertex AI, this field must be set as all
* the fields in predict instance formatted as string.
*
* @var string
*/
public $analysisInstanceSchemaUri;
protected $bigqueryTablesType = GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable::class;
protected $bigqueryTablesDataType = 'array';
/**
* Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
*
* @var string
*/
public $createTime;
/**
* Required. The user-defined name of the ModelDeploymentMonitoringJob. The
* name can be up to 128 characters long and can consist of any UTF-8
* characters. Display name of a ModelDeploymentMonitoringJob.
*
* @var string
*/
public $displayName;
/**
* If true, the scheduled monitoring pipeline logs are sent to Google Cloud
* Logging, including pipeline status and anomalies detected. Please note the
* logs incur cost, which are subject to [Cloud Logging
* pricing](https://cloud.google.com/logging#pricing).
*
* @var bool
*/
public $enableMonitoringPipelineLogs;
protected $encryptionSpecType = GoogleCloudAiplatformV1EncryptionSpec::class;
protected $encryptionSpecDataType = '';
/**
* Required. Endpoint resource name. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
*
* @var string
*/
public $endpoint;
protected $errorType = GoogleRpcStatus::class;
protected $errorDataType = '';
/**
* The labels with user-defined metadata to organize your
* ModelDeploymentMonitoringJob. 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. See https://goo.gl/xmQnxf for more information and examples of
* labels.
*
* @var string[]
*/
public $labels;
protected $latestMonitoringPipelineMetadataType = GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata::class;
protected $latestMonitoringPipelineMetadataDataType = '';
/**
* The TTL of BigQuery tables in user projects which stores logs. A day is the
* basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. {
* second: 3600} indicates ttl = 1 day.
*
* @var string
*/
public $logTtl;
protected $loggingSamplingStrategyType = GoogleCloudAiplatformV1SamplingStrategy::class;
protected $loggingSamplingStrategyDataType = '';
protected $modelDeploymentMonitoringObjectiveConfigsType = GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig::class;
protected $modelDeploymentMonitoringObjectiveConfigsDataType = 'array';
protected $modelDeploymentMonitoringScheduleConfigType = GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig::class;
protected $modelDeploymentMonitoringScheduleConfigDataType = '';
protected $modelMonitoringAlertConfigType = GoogleCloudAiplatformV1ModelMonitoringAlertConfig::class;
protected $modelMonitoringAlertConfigDataType = '';
/**
* Output only. Resource name of a ModelDeploymentMonitoringJob.
*
* @var string
*/
public $name;
/**
* Output only. Timestamp when this monitoring pipeline will be scheduled to
* run for the next round.
*
* @var string
*/
public $nextScheduleTime;
/**
* YAML schema file uri describing the format of a single instance, which are
* given to format this Endpoint's prediction (and explanation). If not set,
* we will generate predict schema from collected predict requests.
*
* @var string
*/
public $predictInstanceSchemaUri;
/**
* Sample Predict instance, same format as PredictRequest.instances, this can
* be set as a replacement of
* ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we
* will generate predict schema from collected predict requests.
*
* @var array
*/
public $samplePredictInstance;
/**
* Output only. Reserved for future use.
*
* @var bool
*/
public $satisfiesPzi;
/**
* Output only. Reserved for future use.
*
* @var bool
*/
public $satisfiesPzs;
/**
* Output only. Schedule state when the monitoring job is in Running state.
*
* @var string
*/
public $scheduleState;
/**
* Output only. The detailed state of the monitoring job. When the job is
* still creating, the state will be 'PENDING'. Once the job is successfully
* created, the state will be 'RUNNING'. Pause the job, the state will be
* 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
*
* @var string
*/
public $state;
protected $statsAnomaliesBaseDirectoryType = GoogleCloudAiplatformV1GcsDestination::class;
protected $statsAnomaliesBaseDirectoryDataType = '';
/**
* Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
* most recently.
*
* @var string
*/
public $updateTime;
/**
* YAML schema file uri describing the format of a single instance that you
* want Tensorflow Data Validation (TFDV) to analyze. If this field is empty,
* all the feature data types are inferred from predict_instance_schema_uri,
* meaning that TFDV will use the data in the exact format(data type) as
* prediction request/response. If there are any data type differences between
* predict instance and TFDV instance, this field can be used to override the
* schema. For models trained with Vertex AI, this field must be set as all
* the fields in predict instance formatted as string.
*
* @param string $analysisInstanceSchemaUri
*/
public function setAnalysisInstanceSchemaUri($analysisInstanceSchemaUri)
{
$this->analysisInstanceSchemaUri = $analysisInstanceSchemaUri;
}
/**
* @return string
*/
public function getAnalysisInstanceSchemaUri()
{
return $this->analysisInstanceSchemaUri;
}
/**
* Output only. The created bigquery tables for the job under customer
* project. Customer could do their own query & analysis. There could be 4 log
* tables in maximum: 1. Training data logging predict request/response 2.
* Serving data logging predict request/response
*
* @param GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable[] $bigqueryTables
*/
public function setBigqueryTables($bigqueryTables)
{
$this->bigqueryTables = $bigqueryTables;
}
/**
* @return GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTable[]
*/
public function getBigqueryTables()
{
return $this->bigqueryTables;
}
/**
* Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
*
* @param string $createTime
*/
public function setCreateTime($createTime)
{
$this->createTime = $createTime;
}
/**
* @return string
*/
public function getCreateTime()
{
return $this->createTime;
}
/**
* Required. The user-defined name of the ModelDeploymentMonitoringJob. The
* name can be up to 128 characters long and can consist of any UTF-8
* characters. Display name of a ModelDeploymentMonitoringJob.
*
* @param string $displayName
*/
public function setDisplayName($displayName)
{
$this->displayName = $displayName;
}
/**
* @return string
*/
public function getDisplayName()
{
return $this->displayName;
}
/**
* If true, the scheduled monitoring pipeline logs are sent to Google Cloud
* Logging, including pipeline status and anomalies detected. Please note the
* logs incur cost, which are subject to [Cloud Logging
* pricing](https://cloud.google.com/logging#pricing).
*
* @param bool $enableMonitoringPipelineLogs
*/
public function setEnableMonitoringPipelineLogs($enableMonitoringPipelineLogs)
{
$this->enableMonitoringPipelineLogs = $enableMonitoringPipelineLogs;
}
/**
* @return bool
*/
public function getEnableMonitoringPipelineLogs()
{
return $this->enableMonitoringPipelineLogs;
}
/**
* Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If
* set, this ModelDeploymentMonitoringJob and all sub-resources of this
* ModelDeploymentMonitoringJob will be secured by this key.
*
* @param GoogleCloudAiplatformV1EncryptionSpec $encryptionSpec
*/
public function setEncryptionSpec(GoogleCloudAiplatformV1EncryptionSpec $encryptionSpec)
{
$this->encryptionSpec = $encryptionSpec;
}
/**
* @return GoogleCloudAiplatformV1EncryptionSpec
*/
public function getEncryptionSpec()
{
return $this->encryptionSpec;
}
/**
* Required. Endpoint resource name. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
*
* @param string $endpoint
*/
public function setEndpoint($endpoint)
{
$this->endpoint = $endpoint;
}
/**
* @return string
*/
public function getEndpoint()
{
return $this->endpoint;
}
/**
* Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
* `JOB_STATE_CANCELLED`.
*
* @param GoogleRpcStatus $error
*/
public function setError(GoogleRpcStatus $error)
{
$this->error = $error;
}
/**
* @return GoogleRpcStatus
*/
public function getError()
{
return $this->error;
}
/**
* The labels with user-defined metadata to organize your
* ModelDeploymentMonitoringJob. 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. See https://goo.gl/xmQnxf for more information and examples of
* labels.
*
* @param string[] $labels
*/
public function setLabels($labels)
{
$this->labels = $labels;
}
/**
* @return string[]
*/
public function getLabels()
{
return $this->labels;
}
/**
* Output only. Latest triggered monitoring pipeline metadata.
*
* @param GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata $latestMonitoringPipelineMetadata
*/
public function setLatestMonitoringPipelineMetadata(GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata $latestMonitoringPipelineMetadata)
{
$this->latestMonitoringPipelineMetadata = $latestMonitoringPipelineMetadata;
}
/**
* @return GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata
*/
public function getLatestMonitoringPipelineMetadata()
{
return $this->latestMonitoringPipelineMetadata;
}
/**
* The TTL of BigQuery tables in user projects which stores logs. A day is the
* basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. {
* second: 3600} indicates ttl = 1 day.
*
* @param string $logTtl
*/
public function setLogTtl($logTtl)
{
$this->logTtl = $logTtl;
}
/**
* @return string
*/
public function getLogTtl()
{
return $this->logTtl;
}
/**
* Required. Sample Strategy for logging.
*
* @param GoogleCloudAiplatformV1SamplingStrategy $loggingSamplingStrategy
*/
public function setLoggingSamplingStrategy(GoogleCloudAiplatformV1SamplingStrategy $loggingSamplingStrategy)
{
$this->loggingSamplingStrategy = $loggingSamplingStrategy;
}
/**
* @return GoogleCloudAiplatformV1SamplingStrategy
*/
public function getLoggingSamplingStrategy()
{
return $this->loggingSamplingStrategy;
}
/**
* Required. The config for monitoring objectives. This is a per DeployedModel
* config. Each DeployedModel needs to be configured separately.
*
* @param GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig[] $modelDeploymentMonitoringObjectiveConfigs
*/
public function setModelDeploymentMonitoringObjectiveConfigs($modelDeploymentMonitoringObjectiveConfigs)
{
$this->modelDeploymentMonitoringObjectiveConfigs = $modelDeploymentMonitoringObjectiveConfigs;
}
/**
* @return GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig[]
*/
public function getModelDeploymentMonitoringObjectiveConfigs()
{
return $this->modelDeploymentMonitoringObjectiveConfigs;
}
/**
* Required. Schedule config for running the monitoring job.
*
* @param GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig $modelDeploymentMonitoringScheduleConfig
*/
public function setModelDeploymentMonitoringScheduleConfig(GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig $modelDeploymentMonitoringScheduleConfig)
{
$this->modelDeploymentMonitoringScheduleConfig = $modelDeploymentMonitoringScheduleConfig;
}
/**
* @return GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig
*/
public function getModelDeploymentMonitoringScheduleConfig()
{
return $this->modelDeploymentMonitoringScheduleConfig;
}
/**
* Alert config for model monitoring.
*
* @param GoogleCloudAiplatformV1ModelMonitoringAlertConfig $modelMonitoringAlertConfig
*/
public function setModelMonitoringAlertConfig(GoogleCloudAiplatformV1ModelMonitoringAlertConfig $modelMonitoringAlertConfig)
{
$this->modelMonitoringAlertConfig = $modelMonitoringAlertConfig;
}
/**
* @return GoogleCloudAiplatformV1ModelMonitoringAlertConfig
*/
public function getModelMonitoringAlertConfig()
{
return $this->modelMonitoringAlertConfig;
}
/**
* Output only. Resource name of a ModelDeploymentMonitoringJob.
*
* @param string $name
*/
public function setName($name)
{
$this->name = $name;
}
/**
* @return string
*/
public function getName()
{
return $this->name;
}
/**
* Output only. Timestamp when this monitoring pipeline will be scheduled to
* run for the next round.
*
* @param string $nextScheduleTime
*/
public function setNextScheduleTime($nextScheduleTime)
{
$this->nextScheduleTime = $nextScheduleTime;
}
/**
* @return string
*/
public function getNextScheduleTime()
{
return $this->nextScheduleTime;
}
/**
* YAML schema file uri describing the format of a single instance, which are
* given to format this Endpoint's prediction (and explanation). If not set,
* we will generate predict schema from collected predict requests.
*
* @param string $predictInstanceSchemaUri
*/
public function setPredictInstanceSchemaUri($predictInstanceSchemaUri)
{
$this->predictInstanceSchemaUri = $predictInstanceSchemaUri;
}
/**
* @return string
*/
public function getPredictInstanceSchemaUri()
{
return $this->predictInstanceSchemaUri;
}
/**
* Sample Predict instance, same format as PredictRequest.instances, this can
* be set as a replacement of
* ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we
* will generate predict schema from collected predict requests.
*
* @param array $samplePredictInstance
*/
public function setSamplePredictInstance($samplePredictInstance)
{
$this->samplePredictInstance = $samplePredictInstance;
}
/**
* @return array
*/
public function getSamplePredictInstance()
{
return $this->samplePredictInstance;
}
/**
* Output only. Reserved for future use.
*
* @param bool $satisfiesPzi
*/
public function setSatisfiesPzi($satisfiesPzi)
{
$this->satisfiesPzi = $satisfiesPzi;
}
/**
* @return bool
*/
public function getSatisfiesPzi()
{
return $this->satisfiesPzi;
}
/**
* Output only. Reserved for future use.
*
* @param bool $satisfiesPzs
*/
public function setSatisfiesPzs($satisfiesPzs)
{
$this->satisfiesPzs = $satisfiesPzs;
}
/**
* @return bool
*/
public function getSatisfiesPzs()
{
return $this->satisfiesPzs;
}
/**
* Output only. Schedule state when the monitoring job is in Running state.
*
* Accepted values: MONITORING_SCHEDULE_STATE_UNSPECIFIED, PENDING, OFFLINE,
* RUNNING
*
* @param self::SCHEDULE_STATE_* $scheduleState
*/
public function setScheduleState($scheduleState)
{
$this->scheduleState = $scheduleState;
}
/**
* @return self::SCHEDULE_STATE_*
*/
public function getScheduleState()
{
return $this->scheduleState;
}
/**
* Output only. The detailed state of the monitoring job. When the job is
* still creating, the state will be 'PENDING'. Once the job is successfully
* created, the state will be 'RUNNING'. Pause the job, the state will be
* 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
*
* Accepted values: JOB_STATE_UNSPECIFIED, JOB_STATE_QUEUED,
* JOB_STATE_PENDING, JOB_STATE_RUNNING, JOB_STATE_SUCCEEDED,
* JOB_STATE_FAILED, JOB_STATE_CANCELLING, JOB_STATE_CANCELLED,
* JOB_STATE_PAUSED, JOB_STATE_EXPIRED, JOB_STATE_UPDATING,
* JOB_STATE_PARTIALLY_SUCCEEDED
*
* @param self::STATE_* $state
*/
public function setState($state)
{
$this->state = $state;
}
/**
* @return self::STATE_*
*/
public function getState()
{
return $this->state;
}
/**
* Stats anomalies base folder path.
*
* @param GoogleCloudAiplatformV1GcsDestination $statsAnomaliesBaseDirectory
*/
public function setStatsAnomaliesBaseDirectory(GoogleCloudAiplatformV1GcsDestination $statsAnomaliesBaseDirectory)
{
$this->statsAnomaliesBaseDirectory = $statsAnomaliesBaseDirectory;
}
/**
* @return GoogleCloudAiplatformV1GcsDestination
*/
public function getStatsAnomaliesBaseDirectory()
{
return $this->statsAnomaliesBaseDirectory;
}
/**
* Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
* most recently.
*
* @param string $updateTime
*/
public function setUpdateTime($updateTime)
{
$this->updateTime = $updateTime;
}
/**
* @return string
*/
public function getUpdateTime()
{
return $this->updateTime;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1ModelDeploymentMonitoringJob::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1ModelDeploymentMonitoringJob');