code: def benchmark_autochunk_gpt(batch=1, seq=512, n_embd=768, n_head=12):
      from test_autochunk_gpt import GPT2Config, GPT2Model, get_data
  
      model = GPT2Model
      config = GPT2Config(
          n_embd=n_embd, n_positions=seq, n_layer=2, n_head=n_head
      )
      model = model(config=config)
      shape = [batch, seq]
      print(
          "\nbatch: %d, seq: %d, n_embd: %d, n_head: %d"
          % (batch, seq, n_embd, n_head)
      )
      max_mem = _benchmark_autochunk_gpt_origin(model, get_data(shape))
      for ratio in [0.5, 0.4, 0.3, 0.2]:
          try:
              _benchmark_autochunk_gpt_gm(
                  model, get_data(shape), max_mem * ratio
              )
          except RuntimeError as e:
              if (
                  e.args[0]
                  == "Search failed. Try a larger memory threshold."
              ):
                  break
          except Exception as e:
              raise e
      _benchmark_autochunk_gpt_gm(model, get_data(shape), None)
  
file_path: ColossalAI/tests/test_autochunk/test_autochunk_transformer/benchmark_autochunk_transformer.py
imports: import time
  from typing import Any
  import torch
  import torch.fx
  import colossalai
  from colossalai.autochunk.autochunk_codegen import AUTOCHUNK_AVAILABLE
  from colossalai.fx.graph_module import ColoGraphModule
  from colossalai.fx.passes.meta_info_prop import MetaInfoProp
  from colossalai.fx.profiler import parameter_size
  from colossalai.utils import free_port
label_desc: Use image node_id 5 for calling a global function with example usage: benchmark_autochunk_gpt(batch, seq, n_embd, n_head) without return types