Contains functionality for running reinforcement learning experiments on Azure Machine Learning and associated configuration.
Represents an estimator for training Reinforcement Learning experiments.
A run class to handle and monitor Reinforcement Learning Runs associated with an experiment and an individual run ID.
Represents configuration for reinforcement learning runs targeting Azure Machine Learning compute targets.
ReinforcementLearningConfiguration object encapsulates the information necessary to submit a reinforcement learning run in an experiment. It includes information about head, workers, simulators and compute targets to execute experiment runs on.
WorkerConfiguration is the class that holds all the necessary information for the workers to run.
Defines the version and arguments for the Ray framework.
For more information about Ray, see https://github.com/ray-project/ray.
Contains details of the simulators used during a reinforcement learning run.
Defines methods for interacting with runtime simulator instances.
Simulators are processes that run on a compute target and listen on a process specific port. Instances of this class hold the information necessary to connect to a simulator during execution of a reinforcement learning experiment. This class is typically referenced and used during experiment execution and not during control plane operations in the SDK.