hypll.optim.adam

Classes

RiemannianAdam

class hypll.optim.adam.RiemannianAdam

__init__(params: Iterable[ManifoldParameter | ManifoldTensor], lr: float, betas: tuple[float, float] = (0.9, 0.999), eps: float = 1e-08, weight_decay: float = 0, amsgrad: bool = False) → None

step() → None

Performs a single optimization step (parameter update).

Parameters:

closure (Callable) – A closure that reevaluates the model and returns the loss. Optional for most optimizers.

Note

Unless otherwise specified, this function should not modify the .grad field of the parameters.