optim

Source code: tianshou/highlevel/optim.py

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class OptimizerWithLearningRateProtocol(*args, **kwargs)

Bases: Protocol

class OptimizerFactory

Bases: ABC, ToStringMixin

create_optimizer(module: Module, lr: float) → Optimizer

abstract create_optimizer_for_params(params: Iterable[Tensor] | Iterable[dict[str, Any]], lr: float) → Optimizer

class OptimizerFactoryTorch(optim_class: OptimizerWithLearningRateProtocol, **kwargs: Any)

Bases: OptimizerFactory

Factory for torch optimizers.

Parameters:

• optim_class – the optimizer class (e.g. subclass of torch.optim.Optimizer), which will be passed the module parameters, the learning rate as lr and the kwargs provided.

• kwargs – keyword arguments to provide at optimizer construction

create_optimizer_for_params(params: Iterable[Tensor] | Iterable[dict[str, Any]], lr: float) → Optimizer

class OptimizerFactoryAdam(betas: tuple[float, float] = (0.9, 0.999), eps: float = 1e-08, weight_decay: float = 0)

Bases: OptimizerFactory

create_optimizer_for_params(params: Iterable[Tensor] | Iterable[dict[str, Any]], lr: float) → Optimizer

class OptimizerFactoryRMSprop(alpha: float = 0.99, eps: float = 1e-08, weight_decay: float = 0, momentum: float = 0, centered: bool = False)

Bases: OptimizerFactory

create_optimizer_for_params(params: Iterable[Tensor] | Iterable[dict[str, Any]], lr: float) → Optimizer