code: def main(args):
      now = datetime.now()
      current_date = now.strftime("%m/%d/%Y")
  
      all_num_prompt_tokens = [1, 256, 512, 1024, 1536]
      all_num_output_tokens = [1, 2, 4, 8, 16, 32, 64]
  
      scenario = "synthetic_efficiency"
      all_models_and_tokenizers = []
      for tokenizer_provider in args.tokenizer_providers:
          if tokenizer_provider == "ai21":
              all_models_and_tokenizers.append(
                  ("ai21_tokenizer", "ai21/j1")
              )
          elif tokenizer_provider == "openai":
              all_models_and_tokenizers.append(
                  ("gpt2_tokenizer", "huggingface/gpt2")
              )
          elif tokenizer_provider == "cohere":
              all_models_and_tokenizers.append(
                  ("cohere_tokenizer", "cohere/cohere")
              )
          elif tokenizer_provider == "opt":
              all_models_and_tokenizers.append(
                  ("opt_tokenizer", "meta/opt")
              )
          elif tokenizer_provider == "yandex":
              all_models_and_tokenizers.append(
                  ("together/yalm", "yandex/yalm")
              )
          elif tokenizer_provider == "bloom":
              all_models_and_tokenizers.append(
                  ("together/bloom", "bigscience/bloom")
              )
          elif tokenizer_provider == "t5":
              all_models_and_tokenizers.append(
                  ("together/t5-11b", "google/t5")
              )
          elif tokenizer_provider == "t0":
              all_models_and_tokenizers.append(
                  ("together/t0pp", "bigscience/t0pp")
              )
          elif tokenizer_provider == "ul2":
              all_models_and_tokenizers.append(
                  ("together/ul2", "google/ul2")
              )
          elif tokenizer_provider == "glm":
              all_models_and_tokenizers.append(
                  ("together/glm", "tsinghua/glm")
              )
          elif tokenizer_provider == "gptj":
              all_models_and_tokenizers.append(
                  ("together/gpt-j-6b", "eleutherai/gptj")
              )
          elif tokenizer_provider == "gptneox":
              all_models_and_tokenizers.append(
                  ("together/gpt-neox-20b", "eleutherai/gptneox")
              )
  
      specs = []
      num_specs = (
          len(all_models_and_tokenizers)
          * len(all_num_prompt_tokens)
          * len(all_num_output_tokens)
      )
      print(f"Generating {num_specs} specs...")
      for model, tokenizer in all_models_and_tokenizers:
          for num_prompt_tokens in all_num_prompt_tokens:
              for num_output_tokens in all_num_output_tokens:
                  if args.no_random:
                      random = None
                  else:
                      random = current_date
                  spec = generate_spec(
                      scenario,
                      model,
                      tokenizer,
                      num_prompt_tokens,
                      num_output_tokens,
                      random=random,
                  )
                  specs.append(spec)
  
      print(f"Writing out {len(specs)} specs...")
      with open(args.output_path, "w") as f:
          for spec in specs:
              f.write(f"{spec}\n")
  
imports: import argparse
  from datetime import datetime
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) without return types