code: def _quantize_param(param: nn.Parameter, quant_config: Dict):
      assert not hasattr(
          param, "weight_quantized"
      ), "Parameter has already been quantized."
      quantizer = Quantizer(quant_config)
      dequantizer = DeQuantizer(quant_config, param.dtype)
  
      quantized_weight, quant_scale, quant_min = quantizer.quantize(
          param.data
      )
  
      quantized_weight = quantized_weight.view(param.dtype)
      quant_scale = quant_scale.view(param.dtype)
      quant_min = quant_min.view(param.dtype)
  
      quantized_compat_tensor = concat_to_compat_param(
          quantized_weight, quant_scale, quant_min
      )
      param.data = quantized_compat_tensor
      param.deconcat = quantized_compat_tensor.deconcat
  
      param.quantizer = quantizer
      param.dequantizer = dequantizer
      setattr(param, "weight_quantized", True)
  
imports: import torch
  import deepspeed
  from torch import Tensor
  from typing import Tuple
  import torch.nn
  from typing import Dict, Callable, Union
  from deepspeed.accelerator import get_accelerator
  import functools
label_desc: Use image node_id 7 for calling a global function with example usage: _quantize_param(param, quant_config) without return types