abacusai.model_monitor_version

Module Contents

Classes

ModelMonitorVersion

A version of a model monitor

class abacusai.model_monitor_version.ModelMonitorVersion(client, modelMonitorVersion=None, status=None, modelMonitorId=None, monitoringStartedAt=None, monitoringCompletedAt=None, trainingFeatureGroupVersion=None, predictionFeatureGroupVersion=None, error=None, pendingDeploymentIds=None, failedDeploymentIds=None, metricConfigs=None, featureGroupMonitorConfigs=None, metricTypes=None, modelVersion=None, batchPredictionVersion=None, edaConfigs=None)

Bases: abacusai.return_class.AbstractApiClass

A version of a model monitor

Parameters:
  • client (ApiClient) – An authenticated API Client instance

  • modelMonitorVersion (str) – The unique identifier of a model monitor version.

  • status (str) – The current status of the model.

  • modelMonitorId (str) – A reference to the model monitor this version belongs to.

  • monitoringStartedAt (str) – The start time and date of the monitoring process.

  • monitoringCompletedAt (str) – The end time and date of the monitoring process.

  • trainingFeatureGroupVersion (unique string identifiers) – Feature group version IDs that this refresh pipeline run is monitoring.

  • predictionFeatureGroupVersion (unique string identifiers) – Feature group version IDs that this refresh pipeline run is monitoring.

  • error (str) – Relevant error if the status is FAILED.

  • pendingDeploymentIds (list) – List of deployment IDs where deployment is pending.

  • failedDeploymentIds (list) – List of failed deployment IDs.

  • metricConfigs (json field) – List of metric configs for the model monitor instance.

  • featureGroupMonitorConfigs (dict) – Configurations for feature group monitor

  • metricTypes (dict) – List of metric types.

  • modelVersion (unique string identifiers) – Model version IDs that this refresh pipeline run is monitoring.

  • batchPredictionVersion (str) –

  • edaConfigs (list) –

__repr__()

Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict

get_prediction_drift()

Gets the label and prediction drifts for a model monitor.

Parameters:

model_monitor_version (str) – The unique identifier to a model monitor version created under the project.

Returns:

An object describing training and prediction output label and prediction distributions.

Return type:

DriftDistributions

refresh()

Calls describe and refreshes the current object’s fields

Returns:

The current object

Return type:

ModelMonitorVersion

describe()

Retrieves a full description of the specified model monitor version

Parameters:

model_monitor_version (str) – The unique version ID of the model monitor version

Returns:

A model monitor version.

Return type:

ModelMonitorVersion

delete()

Deletes the specified model monitor version.

Parameters:

model_monitor_version (str) – The ID of the model monitor version to delete.

metric_data(metric_type, actual_values_to_detail=None)

Provides the data needed for decile metrics associated with the model monitor.

Parameters:
  • metric_type (str) – The metric type to get data for.

  • actual_values_to_detail (list) –

Returns:

Data associated with the metric.

Return type:

ModelMonitorVersionMetricData

list_monitor_alert_versions_for_monitor_version()

Retrieves the list of monitor alerts version for a specified monitor instance

Parameters:

model_monitor_version (str) – The unique ID associated with the model monitor.

Returns:

An array of monitor alerts.

Return type:

MonitorAlertVersion

get_model_monitoring_logs(stdout=False, stderr=False)

Returns monitoring logs for the model.

Parameters:
  • stdout (bool) – Set True to get info logs

  • stderr (bool) – Set True to get error logs

Returns:

A function logs.

Return type:

FunctionLogs

get_drift_for_feature(feature_name)

Gets the feature drift associated with a single feature in an output feature group from a prediction.

Parameters:

feature_name (str) – Name of the feature to view the distribution of.

get_outliers_for_feature(feature_name=None)

Gets a list of outliers measured by a single feature (or overall) in an output feature group from a prediction.

Parameters:

feature_name (str) – Name of the feature to view the distribution of.

wait_for_monitor(timeout=1200)

A waiting call until model monitor version is ready.

Parameters:

timeout (int, optional) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.

get_status()

Gets the status of the model monitor version.

Returns:

A string describing the status of the model monitor version, for e.g., pending, complete, etc.

Return type:

str