code: def named_buffers(
      self,
      prefix: str = "",
      recurse: bool = True,
      remove_duplicate: bool = True,
  ) -> Iterator[Tuple[str, torch.Tensor]]:
      yield from ()
  
file_path: torchrec/torchrec/distributed/grouped_position_weighted.py
imports: from collections import OrderedDict
  from typing import Any, Dict, Iterator, Optional, Tuple
  import torch
  import torch.nn
  from torchrec.distributed.embedding_types import BaseGroupedFeatureProcessor
  from torchrec.distributed.utils import append_prefix
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 4 for calling the GroupedPositionWeightedModule obj's underlying member method code with example usage: obj.named_buffers(prefix, recurse, remove_duplicate) without return types