code: def test_real_compression():
      torch.manual_seed(0)
      a = torch.normal(0, 1, (32, 1, 1), dtype=torch.float16).cuda()
  
      config = CompressionConfig(
          num_bits=4, group_size=32, group_dim=0, symmetric=False
      )
      dev = TorchDevice("cuda:0", 0, 0).compressed_device
      packed = dev.compress(a, config)
      b = dev.decompress(packed)
  
      print(a.flatten())
      print(b.flatten())
  
imports: import dataclasses
  import torch
  import numpy
  from flexgen.pytorch_backend import TorchTensor, TorchDevice, DeviceType, general_copy, fix_recursive_import
  from flexgen.utils import np_dtype_to_torch_dtype
label_desc: Use image node_id 9 for calling a global function with example usage: test_real_compression() without return types