code: def get_data(batch_size, seq_len, vocab_size):
      input_ids = torch.randint(
          0,
          vocab_size,
          (batch_size, seq_len),
          device=torch.cuda.current_device(),
      )
      attention_mask = torch.ones_like(input_ids)
      return input_ids, attention_mask
  
file_path: ColossalAI/examples/language/opt/opt_benchmark.py
imports: import time
  import torch
  import tqdm
  import transformers
  from args import parse_benchmark_args
  from transformers import AutoConfig, OPTForCausalLM
  from transformers.utils.versions import require_version
  import colossalai
  from colossalai.booster import Booster
  from colossalai.booster.plugin import GeminiPlugin, LowLevelZeroPlugin, TorchDDPPlugin
  from colossalai.cluster import DistCoordinator
  from colossalai.logging import disable_existing_loggers, get_dist_logger
  from colossalai.nn.optimizer import HybridAdam
label_desc: Use image node_id 2 for calling a global function with example usage: get_data(batch_size, seq_len, vocab_size) and returns: input_ids,  attention_mask