code: def corrcoef(
      x: torch.Tensor,
      /,
      *,
      y: Optional[torch.Tensor] = None,
      rowvar: bool = True,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if y is None:
          xarr = x
      else:
          axis = 0 if rowvar else 1
          xarr = torch.concat([x, y], dim=axis)
          xarr = xarr.T if not rowvar else xarr
  
      return torch.corrcoef(xarr)
  
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 12 for calling a global function with example usage: corrcoef() and returns: torch