code: def data_gen(batch_size: int = 4, seq_len: int = 512):
      input_ids = torch.randint(
          10, 30000, (batch_size, seq_len), device=get_current_device()
      )
      attention_mask = torch.ones_like(input_ids)
      data = dict(input_ids=input_ids, attention_mask=attention_mask)
      return data
  
file_path: ColossalAI/examples/inference/benchmark_llama.py
imports: import argparse
  import time
  import torch
  import torch.distributed
  import transformers
  import colossalai
  import colossalai.utils.device
  from colossalai.inference import InferenceEngine
  from colossalai.testing import clear_cache_before_run, rerun_if_address_is_in_use, spawn
  from colossalai.utils.device import get_current_device
label_desc: Use image node_id 1 for calling a global function with example usage: data_gen(batch_size, seq_len) and returns: data