Trainer Basics

Core trainer classes and builder utilities.

Trainer and hooks

Trainer(*args, **kwargs)	A generic Trainer class.
TrainerHookBase()	An abstract hooking class for torchrl Trainer class.

Algorithm-specific trainers

PPOTrainer(*args, **kwargs)	PPO (Proximal Policy Optimization) trainer implementation.
SACTrainer(*args, **kwargs)	A trainer class for Soft Actor-Critic (SAC) algorithm.

Builders

make_collector_offpolicy(make_env, ...[, ...])	Returns a data collector for off-policy sota-implementations.
make_collector_onpolicy(make_env, ...[, ...])	Makes a collector in on-policy settings.
make_dqn_loss(model, cfg)	Builds the DQN loss module.
make_replay_buffer(device, cfg)	Builds a replay buffer using the config built from ReplayArgsConfig.
make_target_updater(cfg, loss_module)	Builds a target network weight update object.
make_trainer(collector, loss_module[, ...])	Creates a Trainer instance given its constituents.
parallel_env_constructor(cfg, **kwargs)	Returns a parallel environment from an argparse.Namespace built with the appropriate parser constructor.
sync_async_collector(env_fns, env_kwargs[, ...])	Runs asynchronous collectors, each running synchronous environments.
sync_sync_collector(env_fns, env_kwargs[, ...])	Runs synchronous collectors, each running synchronous environments.
transformed_env_constructor(cfg[, ...])	Returns an environment creator from an argparse.Namespace built with the appropriate parser constructor.

Utils

correct_for_frame_skip(cfg)	Correct the arguments for the input frame_skip, by dividing all the arguments that reflect a count of frames by the frame_skip.
get_stats_random_rollout(cfg[, ...])	Gathers stas (loc and scale) from an environment using random rollouts.