abacusai.model_version — AbacusAI documentation

# `abacusai.model_version`

## Module Contents

### Classes

`ModelVersion` | 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)

  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

  __repr__(self)

    Return repr(self).

  to_dict(self)

    Get a dict representation of the parameters in this class

    Returns

      The dict value representation of the class parameters

    Return type

      dict

  delete(self)

    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.

  refresh(self)

    Calls describe and refreshes the current object’s fields

    Returns

      The current object

    Return type

      ModelVersion

  describe(self)

    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

      ModelVersion

  get_training_logs(self, stdout=False, stderr=False)

    Returns training 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

  wait_for_training(self, 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.

  get_status(self)

    Gets the status of the model version under training.

    Returns

      A string describing the status of a model training (pending, complete, etc.).

    Return type

      str