code: def test_simulated_compression():
      torch.manual_seed(0)
      a = torch.normal(0, 1, (64, 64, 64), dtype=torch.float16).cuda()
  
      config = CompressionConfig(
          num_bits=4, group_size=32, group_dim=0, symmetric=False
      )
      packed_data = compress(a, config)
      b = decompress(packed_data, config)
      print(a[0])
      print(b[0])
  
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 8 for calling a global function with example usage: test_simulated_compression() without return types