code: def norm(
      input, p="fro", dim=None, keepdim=False, out=None, dtype=None
  ):
      if dtype is None or not ivy.is_float_dtype(dtype):
          dtype = "float64" if "128" in str(dtype) else "float32"
      if (
          p == "fro"
          and (dim is None or isinstance(dim, int) or len(dim) <= 2)
      ) or p is None:
          p = 2
      if isinstance(p, str):
          if dim is None:
              dim = tuple(range(input.dim()))
          return ivy.matrix_norm(
              input, ord=p, axis=dim, keepdims=keepdim, out=out
          ).astype(dtype)
      else:
          return ivy.vector_norm(
              input,
              ord=p,
              axis=dim,
              keepdims=keepdim,
              dtype=dtype,
              out=out,
          )
  
imports: import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back, numpy_to_torch_style_args
  from collections import namedtuple
  import ivy.functional.frontends.torch
label_desc: Use image node_id 19 for calling a global function with example usage: norm(input, p, dim, keepdim, out, dtype) and returns: ivy, ivy