MnistModel.named_buffers#
- MnistModel.named_buffers(prefix: str = '', recurse: bool = True, remove_duplicate: bool = True) Iterator[Tuple[str, Tensor]]#
Return an iterator over module buffers, yielding both the name of the buffer as well as the buffer itself.
- Args:
prefix (str): prefix to prepend to all buffer names. recurse (bool, optional): if True, then yields buffers of this module
and all submodules. Otherwise, yields only buffers that are direct members of this module. Defaults to True.
remove_duplicate (bool, optional): whether to remove the duplicated buffers in the result. Defaults to True.
- Yields:
(str, torch.Tensor): Tuple containing the name and buffer
Example:
>>> # xdoctest: +SKIP("undefined vars") >>> for name, buf in self.named_buffers(): >>> if name in ['running_var']: >>> print(buf.size())