code: def init_compression(
      model, deepspeed_config, teacher_model=None, mpu=None
  ):
      """
      Compress a model: replace linear/conv2d layer with deepspeed compression-aware modules
      Args:
          model (`torch.nn.Module`)
              The model to compress.
          deepspeed_config (`DeepSpeedConfig`)
              The path of ds_config
          mpu
              The mpu module for Row/Column parallelism
      """
      compress_methods = get_compression_config(
          check_deepspeed_config(deepspeed_config)
      )
      if hasattr(model, "module"):
          c_model = model.module
      else:
          c_model = model
  
      # For layer reduction
      if compress_methods[LAYER_REDUCTION][LAYER_REDUCTION_ENABLED]:
          assert (
              teacher_model is not None
          ), "Teacher model is required for layer reduction"
          student_initialization(
              c_model, teacher_model, deepspeed_config
          )
  
      layer_added_compress_methods = get_compress_methods(
          c_model, compress_methods, mpu=mpu
      )
      compression_preparation(
          c_model, layer_added_compress_methods, mpu
      )
  
      return model
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/deepspeed/compression/compress.py
imports: import re
  from .helper import compression_preparation, fix_compression, recursive_getattr, is_module_compressible
  from .config import get_compression_config
  from ..runtime.config_utils import dict_raise_error_on_duplicate_keys
  from .constants import *
  import os
  import json
label_desc: Use image node_id 4 for calling a global function with example usage: init_compression(model, deepspeed_config, teacher_model, mpu) and returns: model