code: def arange(start, stop=None, step=1.0, *args, **kwargs):
      if stop is None:
          return torch.arange(
              start=0.0,
              end=float(start),
              step=float(step),
              *args,
              **kwargs,
          )
      else:
          return torch.arange(
              float(start), float(stop), float(step), *args, **kwargs
          )
  
imports: from packaging.version import Version
  import numpy
  from .core import Backend, backend_types, backend_basic_math, backend_array
label_desc: Use image node_id 6 for calling the PyTorchBackend obj's underlying member method code with example usage: obj.arange(start, stop, step) and returns: torch, torch