code: def nanmean(
      a: torch.Tensor,
      /,
      *,
      axis: Optional[Union[int, Tuple[int]]] = None,
      keepdims: bool = False,
      dtype: Optional[torch.dtype] = None,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      return torch.nanmean(
          a, dim=axis, keepdim=keepdims, dtype=dtype, out=out
      )
  
imports: from typing import Optional, Union, Tuple, Sequence
  import torch
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  import ivy
  from ..statistical import _infer_dtype
  from copy import deepcopy
label_desc: Use image node_id 3 for calling a global function with example usage: nanmean() and returns: torch