estimator Package

Contains base estimator classes and the generic estimator class in Azure Machine Learning.

Classes

Estimator	Represents a generic estimator to train data using any supplied framework. DEPRECATED. Use the ScriptRunConfig object with your own defined environment or an Azure ML curated environment. For an introduction to configuring experiment runs with ScriptRunConfig, see Configure and submit training runs. This class is designed for use with machine learning frameworks that do not already have an Azure Machine Learning pre-configured estimator. Pre-configured estimators exist for Chainer, PyTorch, TensorFlow, and SKLearn. To create an Estimator that is not preconfigured, see Train models with Azure Machine Learning using estimator. The Estimator class wraps run configuration information to help simplify the tasks of specifying how a script is executed. It supports single-node as well as multi-node execution. Running the estimator produces a model in the output directory specified in your training script. Initialize the estimator. azureml.core.environment._DEFAULT_SHM_SIZE is used. For more information, see Docker run reference. :type shm_size: str :param resume_from: The data path containing the checkpoint or model files from which to resume the experiment. :type resume_from: azureml.data.datapath.DataPath :param max_run_duration_seconds: The maximum allowed time for the run. Azure ML will attempt to automatically cancel the run if it takes longer than this value.
Gloo	Manages Gloo settings for distributed training jobs. DEPRECATED. Use the PyTorchConfiguration class. Gloo can be specified for a training job with the distributed_training parameter of the preconfigured PyTorch estimator or any generic Estimator supporting Gloo. A class for managing Gloo settings for jobs.
MMLBaseEstimator	Abstract base class for all estimators. DEPRECATED. Use the ScriptRunConfig object with your own defined environment or an Azure ML curated environment. Initialize properties common to all estimators.
MMLBaseEstimatorRunConfig	Abstract base class for all Estimator run configs. DEPRECATED. Use the RunConfiguration class. Initialize the MMLBaseEstimatorRunConfig.
Mpi	Manages Message Passing Interface (MPI) settings for distributed training jobs. DEPRECATED. Use the MpiConfiguration class. MPI can be specified for a job with the distributed_training parameter of preconfigured estimators Chainer, PyTorch, and TensorFlow, or with a generic Estimator. A class for managing MPI settings for jobs.
Nccl	Manages Nccl settings for distributed training jobs. DEPRECATED. Use the PyTorchConfiguration class. Nccl can be specified for a training job with the distributed_training parameter of the preconfigured PyTorch estimator or any generic Estimator supporting Nccl. A class for managing Nccl settings for jobs.
ParameterServer	Manages Parameter Server settings for training jobs. DEPRECATED. Use the TensorflowConfiguration class. A class for managing parameter server settings for jobs. DEPRECATED. Use the TensorflowConfiguration class.