code: def logcumsumexp(input, dim, *, out=None):
      if len(input.shape) == 0:
          ret = input
      else:
          # For numerical stability, cast to float64
          # We cast back to the original type at the end.
          original_dtype = input.dtype
          exp_input = ivy.exp(input.astype("float64"))
          summed_exp_input = ivy.cumsum(exp_input, axis=dim)
          ret = ivy.log(summed_exp_input).astype(original_dtype)
      if ivy.exists(out):
          ivy.inplace_update(out, ret)
      return ret
  
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
  from ivy.functional.frontends.torch import promote_types_of_torch_inputs
  import ivy.functional.frontends.torch
label_desc: Use image node_id 28 for calling a global function with example usage: logcumsumexp(input, dim) and returns: ret