add_module(name: str, module: torch.nn.modules.module.Module) → None

apply(fn: Callable[Module, None]) → T

bfloat16() → T

buffers(recurse: bool = True) → Iterator[torch.Tensor]

children() → Iterator[torch.nn.modules.module.Module]

cpu() → T

cuda(device: Union[int, torch.device, None] = None) → T

double() → T

dump_patches: BOOL = FALSE

eval() → T

extra_repr() → str

float() → T

half() → T

load_state_dict(state_dict: Dict[str, torch.Tensor], strict: bool = True)

modules() → Iterator[torch.nn.modules.module.Module]

named_buffers(prefix: str = ‘’, recurse: bool = True) → Iterator[Tuple[str, torch.Tensor]]

named_children() → Iterator[Tuple[str, torch.nn.modules.module.Module]]

named_modules(memo: Optional[Set[Module]] = None, prefix: str = ‘’)

named_parameters(prefix: str = ‘’, recurse: bool = True) → Iterator[Tuple[str, torch.Tensor]]

parameters(recurse: bool = True) → Iterator[torch.nn.parameter.Parameter]

register_backward_hook(hook: Callable[[Module, Union[Tuple[torch.Tensor, …], torch.Tensor], Union[Tuple[torch.Tensor, …], torch.Tensor]], Union[None, torch.Tensor]]) → torch.utils.hooks.RemovableHandle

register_buffer(name: str, tensor: torch.Tensor, persistent: bool = True) → None

register_forward_hook(hook: Callable[…, None]) → torch.utils.hooks.RemovableHandle

register_forward_pre_hook(hook: Callable[…, None]) → torch.utils.hooks.RemovableHandle

register_parameter(name: str, param: torch.nn.parameter.Parameter) → None

requires_grad_(requires_grad: bool = True) → T

state_dict(destination=None, prefix=’’, keep_vars=False)

to(*args, **kwargs)

train(mode: bool = True) → T

type(dst_type: Union[torch.dtype, str]) → T

zero_grad() → None