code: def l1_loss(
      input,
      label,
      reduction="mean",
      name=None,
  ):
      sum_diff = ivy.abs(input - label)
      reduction = _get_reduction_func(reduction)
      out = reduction(sum_diff)
      if out.shape == ():
          out = out.expand_dims()
      return paddle.to_tensor(out)
  
imports: import ivy
  from ivy.func_wrapper import with_supported_dtypes
  import ivy.functional.frontends.paddle
  from ivy.utils.exceptions import handle_exceptions
  from ivy.functional.frontends.paddle.func_wrapper import inputs_to_ivy_arrays, to_ivy_arrays_and_back
label_desc: Use image node_id 9 for calling a global function with example usage: l1_loss(input, label, reduction, name) and returns: paddle