code: def run_ref_dequantize(
      quantized_data, params, num_groups, q_bits, is_symmetric_quant
  ):
      if q_bits == 4:
          quantized_data = int4x2to2xint4(quantized_data)
  
      quantized_data = quantized_data.reshape(num_groups, -1).to(
          torch.float32
      )
  
      if is_symmetric_quant:
          return (quantized_data * params).to(torch.float16)
      else:
          scales = params[:, 0].reshape(-1, 1)
          offsets = params[:, 1].reshape(-1, 1)
          return (quantized_data * scales + offsets).to(torch.float16)
  
imports: import pytest
  import torch
  from deepspeed.ops import op_builder
label_desc: Use image node_id 4 for calling a global function with example usage: run_ref_dequantize(quantized_data, params, num_groups, q_bits, is_symmetric_quant) and returns: unknown, unknown