torchrl.trainers.algorithms.configs.trainers.FQLTrainerConfig#
- class torchrl.trainers.algorithms.configs.trainers.FQLTrainerConfig(loss_module: Any, optimizer: Any, replay_buffer: Any, target_net_updater: Any, offline_steps: int, collector: Any = None, total_frames: int = 0, device: str | None = None, batch_size: int | None = None, compile_loss: bool = False, logger: Any = None, clip_grad_norm: bool = True, clip_norm: float | None = None, progress_bar: bool = False, seed: int | None = None, save_trainer_interval: int = 10000, log_interval: int = 10000, save_trainer_file: Any = None, checkpoint: Any = None, checkpoint_rotation: Any = None, checkpoint_metadata: Any = None, log_timings: bool = False, auto_log_optim_steps: bool = True, hooks: list[Any] | None = None, _target_: str = 'torchrl.trainers.algorithms.configs.trainers.make_fql_trainer')[source]#
Hydra configuration for
FQLTrainer.Optimizer and target updater configurations should be partials: they receive the instantiated loss parameters and loss module, respectively.