class_docstr: A class that provides a way to access the submodules and parameters/buffers of a module.
  
  It provides caching mechanism to speed up submodule lookups.
  This is useful for functional programming to manipulate the module state.
class_docstr_tok: ["A","class","that","provides","a","way","to","access","the","submodules","and","parameters\/buffers","of","a","module",".","It","provides","caching","mechanism","to","speed","up","submodule","lookups",".","This","is","useful","for","functional","programming","to","manipulate","the","module","state","."]
docstr: Iterate over all the buffers in the module.
docstr_tok: ["Iterate","over","all","the","buffers","in","the","module","."]
code: def named_buffers(
      self,
      remove_duplicate: bool = True,
  ) -> Iterable[Tuple[str, torch.Tensor]]:
      """Iterate over all the buffers in the module."""
      yield from self.module.named_buffers(
          remove_duplicate=remove_duplicate
      )
  
imports: from typing import Dict, Iterable, List, Tuple
  import torch
label_desc: Use image node_id 16 for calling the NamedMemberAccessor obj's underlying member method code with example usage: obj.named_buffers(remove_duplicate) without return types