abacusai.model_version
Module Contents
Classes
A version of a model |
- class abacusai.model_version.ModelVersion(client, modelVersion=None, status=None, modelId=None, modelConfig=None, modelPredictionConfig=None, trainingStartedAt=None, trainingCompletedAt=None, datasetVersions=None, featureGroupVersions=None, error=None, pendingDeploymentIds=None, failedDeploymentIds=None, cpuSize=None, memory=None, automlComplete=None, trainingFeatureGroupIds=None, codeSource={})
Bases:
abacusai.return_class.AbstractApiClass
A version of a model
- Parameters
client (ApiClient) – An authenticated API Client instance
modelVersion (str) – The unique identifier of a model version.
status (str) – The current status of the model.
modelId (str) – A reference to the model this version belongs to.
modelConfig (dict) – The training config options used to train this model.
modelPredictionConfig (dict) – The prediction config options for the model.
trainingStartedAt (str) – The start time and date of the training process.
trainingCompletedAt (str) – The end time and date of the training process.
datasetVersions (list of unique string identifiers) – Comma separated list of Dataset version IDs that this refresh pipeline run is monitoring.
featureGroupVersions (list) –
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.
cpuSize (str) – Cpu size specified for the python model training.
memory (int) – Memory in GB specified for the python model training.
automlComplete (bool) – If true, all algorithms have compelted training
trainingFeatureGroupIds (list of unique string identifiers) – The unique identifiers of the feature group used as the inputs during training to create this ModelVersion.
codeSource (CodeSource) – If a python model, information on where the source code
- __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
- delete()
Deletes the specified model version. Model Versions which are currently used in deployments cannot be deleted.
- Parameters
model_version (str) – The ID of the model version to delete.
- export_model_artifact_as_feature_group(table_name, artifact_type)
Exports metric artifact data for a model as a feature group.
- Parameters
- Returns
The created feature group.
- Return type
- refresh()
Calls describe and refreshes the current object’s fields
- Returns
The current object
- Return type
- describe()
Retrieves a full description of the specified model version
- Parameters
model_version (str) – The unique version ID of the model version
- Returns
A model version.
- Return type
- get_training_data_logs()
Retrieves the data preparation logs during model training.
- Parameters
model_version (str) – The unique version ID of the model version
- Returns
A list of logs.
- Return type
- get_training_logs(stdout=False, stderr=False)
Returns training logs for the model.
- Parameters
- Returns
A function logs.
- Return type
- wait_for_training(timeout=None)
A waiting call until model gets trained.
- 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.