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{ # Request message for DatasetService.ExportData.
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"exportConfig": { # Describes what part of the Dataset is to be exported, the destination of the export and how to export. # Required. The desired output location.
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"annotationsFilter": "A 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.
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"filterSplit": { # 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. # Split based on the provided filters for each set.
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"testFilter": "A String", # Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
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"trainingFilter": "A String", # Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
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"validationFilter": "A String", # Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
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},
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"fractionSplit": { # 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. # Split based on fractions defining the size of each set.
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"testFraction": 3.14, # The fraction of the input data that is to be used to evaluate the Model.
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"trainingFraction": 3.14, # The fraction of the input data that is to be used to train the Model.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.modelDeploymentMonitoringJobs.html
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],
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},
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"enableLogging": True or False, # Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
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"notificationChannels": [ # Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
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"A String",
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],
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},
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"name": "A String", # Output only. Resource name of a ModelDeploymentMonitoringJob.
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"nextScheduleTime": "A String", # Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
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],
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},
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"enableLogging": True or False, # Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
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"notificationChannels": [ # Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
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"A String",
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],
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},
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"name": "A String", # Output only. Resource name of a ModelDeploymentMonitoringJob.
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"nextScheduleTime": "A String", # Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
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],
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},
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"enableLogging": True or False, # Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
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"notificationChannels": [ # Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
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"A String",
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],
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},
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"name": "A String", # Output only. Resource name of a ModelDeploymentMonitoringJob.
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"nextScheduleTime": "A String", # Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
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],
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},
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"enableLogging": True or False, # Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
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"notificationChannels": [ # Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
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"A String",
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],
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},
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"name": "A String", # Output only. Resource name of a ModelDeploymentMonitoringJob.
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"nextScheduleTime": "A String", # Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
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],
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},
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"enableLogging": True or False, # Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
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"notificationChannels": [ # Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
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"A String",
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],
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},
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"name": "A String", # Output only. Resource name of a ModelDeploymentMonitoringJob.
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"nextScheduleTime": "A String", # Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.notebookRuntimeTemplates.html
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"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
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"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
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},
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"notebookRuntimeType": "A String", # Optional. Immutable. The type of the notebook runtime template.
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"serviceAccount": "A String", # The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
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"updateTime": "A String", # Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.
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}
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"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
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"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
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},
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"notebookRuntimeType": "A String", # Optional. Immutable. The type of the notebook runtime template.
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"serviceAccount": "A String", # The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
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"updateTime": "A String", # Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.
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}</pre>
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"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
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"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
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},
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"notebookRuntimeType": "A String", # Optional. Immutable. The type of the notebook runtime template.
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"serviceAccount": "A String", # The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
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"updateTime": "A String", # Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated.
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