code: def min(*input, dim=None, keepdim=False, out=None):
      if len(input) == 1:
          input = input[0]
      elif len(input) == 2:
          return torch_frontend.minimum(*input)
      if dim is None:
          return ivy.min(input, axis=dim, keepdims=keepdim, out=out)
      elif out is not None:
          ivy.min(input, axis=dim, keepdims=keepdim, out=out[0])
          ivy.argmin(input, axis=dim, keepdims=keepdim, out=out[1])
          return out
      else:
          min_tuple = namedtuple("min", ["values", "indices"])
          return min_tuple(
              ivy.min(input, axis=dim, keepdims=keepdim),
              ivy.argmin(input, axis=dim, keepdims=keepdim),
          )
  
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 14 for calling a global function with example usage: min() and returns: ivy, torch_frontend, out, min_tuple