code: def torch_arange(*args, **kwargs):
      n = len(args)
      step = 1
      if n == 1:
          start = 0
          end = args[0]
      elif n == 2:
          start, end = args
      else:
          start, end, step = args
      if isinstance(start, float):
          start = int(start)
      if isinstance(end, float):
          start = int(end)
      if isinstance(step, float):
          step = int(step)
      step = kwargs.get("step", step)
      dtype = kwargs.get("dtype")
      return torch.empty(
          (end - start) // step, dtype=dtype, device="meta"
      )
  
file_path: ColossalAI/colossalai/fx/tracer/meta_patch/patched_function/torch_ops.py
imports: import torch
  from ...registry import meta_patched_function
label_desc: Use image node_id 1 for calling a global function with example usage: torch_arange() and returns: torch