code: def matrix_norm(
      x: torch.Tensor,
      /,
      *,
      ord: Union[int, float, Literal[inf, -inf, "fro", "nuc"]] = "fro",
      axis: Tuple[int, int] = (-2, -1),
      keepdims: bool = False,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      return torch.linalg.matrix_norm(
          x, ord=ord, dim=axis, keepdim=keepdims, out=out
      )
  
imports: import torch
  from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
  from collections import namedtuple
  import ivy
  from ivy import inf
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from .elementwise import _cast_for_unary_op
label_desc: Use image node_id 10 for calling a global function with example usage: matrix_norm() and returns: torch