(pred_str, data_name, use_last_number=True)

(string, skip_unit=False)

(pred: str)

(model, tokenizer, prompts, batch_size=1, stop_id_sequences=None, add_special_tokens=True, disable_tqdm=False,

(data_name, split, data_dir="./dataset")

(file: Union[str, Path])

(data_name, prompt_type, num_shots)

(example: Dict[str, Any], data_name)

(self, stop_id_sequences)

(string)

(string)

(string)

()

()

(example, data_name, args)

(code_string)

(text: str)

(pred_str: str)

()

(self, client, prompt, problem)

( model_name_or_path, tokenizer_name_or_path=None, device_map="auto", load_

(example)

(llm, tokenizer, data_name, args)

()

(example, data_name)

(data_name, args)

(self, data, num_processes)

(samples, save_path)

(seed: int = 42)

(args)

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs)

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs)

(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs)

(self, api_key, base_url="https://api.openai.com/v1/")

(self, keywords_str, tokenizer)

(self, stop_id_sequences, prompt_length)

(pred_str)

(pred: str, answer_flag: bool = True)

(self, item)

(executor, result, prompt_type, data_name, execute=False)

(sample, print_all_preds=False)