code: def convert_parameter(module: torch.nn.Module, param_name: str):
      # Perform some validation first.
      if not hasattr(module, param_name):
          raise ValueError(
              f"module: {module} does not have parameter with name: {param_name}"
          )
  
      tensor = getattr(module, param_name)
      if not isinstance(tensor, torch.Tensor):
          raise ValueError(
              f"Expected {type(module).__name__}.{param_name} to be a Tensor, but found {type(tensor).__name__}"
          )
  
      if not tensor.is_contiguous():
          raise ValueError(
              f"param: {param_name} is not a contiguous Tensor"
          )
  
      st = _convert_tensor(tensor)
  
      # Replace param with ColoTensor.
  
      # Need to delete the attribute first since param_name might be
      # torch.nn.Parameter and can't be replaced with ColoTensor which is
      # not torch.nn.Parameter.
      delattr(module, param_name)
  
      # Now we can set the attribute appropriately.
      setattr(module, param_name, st)
  
file_path: colossalai/colossalai/tensor/utils.py
imports: from typing import Dict, Iterator, List, Tuple, Union
  import torch
  import torch.nn
  from colossalai.tensor.colo_tensor import ColoTensor
label_desc: Use image node_id 7 for calling a global function with example usage: convert_parameter(module, param_name) without return types