code: def get_data(shape: tuple) -> Tuple[List, List]:
      input_ids = torch.zeros(shape, dtype=torch.int64)
      token_type_ids = torch.zeros(shape, dtype=torch.int64)
      attention_mask = torch.ones(shape, dtype=torch.int64)
      meta_args = dict(
          input_ids=input_ids,
          token_type_ids=token_type_ids,
          attention_mask=attention_mask,
      )
      concrete_args = {"past_key_values": None}
      sequence = [
          "input_ids",
          "past_key_values",
          "attention_mask",
          "token_type_ids",
      ]
      return meta_args, concrete_args, sequence
  
file_path: ColossalAI/tests/test_autochunk/test_autochunk_transformer/test_autochunk_gpt.py
imports: from typing import List, Tuple
  import pytest
  import torch
  from test_autochunk_transformer_utils import run_test
  from colossalai.autochunk.autochunk_codegen import AUTOCHUNK_AVAILABLE
  from colossalai.testing import clear_cache_before_run, parameterize, spawn
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(shape) and returns: meta_args,  concrete_args,  sequence