code: def argwhere(a: NdarrayTensor) -> NdarrayTensor:
      """`np.argwhere` with equivalent implementation for torch.
  
      Args:
          a: input data.
  
      Returns:
          Indices of elements that are non-zero. Indices are grouped by element.
          This array will have shape (N, a.ndim) where N is the number of non-zero items.
      """
      if isinstance(a, np.ndarray):
          return np.argwhere(a)  # type: ignore
      return torch.argwhere(a)
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from typing import TypeVar
  import numpy
  import torch
  from monai.config.type_definitions import NdarrayOrTensor, NdarrayTensor
  from monai.utils.misc import is_module_ver_at_least
  from monai.utils.type_conversion import convert_data_type, convert_to_dst_type
label_desc: Use image node_id 7 for calling a global function with example usage: argwhere(a) and returns: torch, np