Orchestrates compilation and execution.

Extract answer from toolbench format.

提取 \\boxed{...} 中的表达式（支持嵌套括号）。

r"""{ "answer": "A|B|C|D" }

r"""{ "answer": "A|B|C|D" }

r"""{ "answer": "A|B|C|D" }

r"""{ "answer": "A|B|C|D" }

extract the command name from a bracket.

Extract Cpp Code.

extract the first numeric score from the score text Args: score_text (str): the text containing the score Returns:

Extract the content after the last occurrence of specific mathematical comparison or assignment operators. :param strip_whitespace: If True,

This function is designed for calculating the extraction rate. Args: results (dict): The result dict, include the information

Given a response from PerspectiveAPI, return scores in dict. Args: text: Text to perform evaluation. Returns:

fast implementation of the greedy algorithm reference: https://github.com/laming-chen/fast-map-dpp/blob/master/dpp_test.py paper: Fast Greedy

Find first valid option for text.

Perform the first stage of LaTeX string preprocessing. if not brackets_balanced(s): raise ValueError("The input string has unbalanced bra

Fit multiple sets of Elo ratings on different samples of the data at the same time.

Flips the two levels of a nested dictionary so that dict[lvl1][lvl2] becomes dict[lvl2][lvl1]. Args: original_dict (dict)

Format chat history for the LLaDA model Args: history: List of [user_message, assistant_message] pairs Returns:

This function is responsible for formatting prediction details. Args: predictions (list): The prediction list. refere

Use the form of "assert func_name(input) == ".

Check if the given GCP instance is feasible with k_colors. :param dimacs_str: The DIMACS format string of the GCP instance. :param an

Provides a greedy solution to the GCP problem. :param adjacency_list: A dictionary of the adjacency list. :return: A tuple of (num_co

Args: model: Mask predictor. prompt: A tensor of shape (1, l). steps: Sampling steps, less than or equal to gen_lengt

Generate results given a list of inputs. Args: inputs (List[str]): A list of strings. max_out_len (int): The maximum

Generate results given a list of inputs. Args: inputs (List[PromptType]): A list of strings or PromptDicts. The P

生成请求头参数. :param content_type: :param accept: :return:

Generate a prompt for the input field based on the provided :obj:`entry` data. Args: entry (:obj:`Dict`): A piece of data

Generate a prompt for the output field based on the provided :obj:`entry` data. Args: entry (:obj:`Dict`): A piece of dat

Generate the prompt and the label info for one test example in generative evaluation with `prompt_template`. If `prompt_template` is n

Generates a list of questions from the dataset based on the specified prompt style. Args: dataset_path (str): The path to the dataset

生成随机串. :param length: 随机串长度，默认为 16 :return: 随机串

Generate text with LLaDA model with visualization using the same sampling as in generate.py Args: messages: List of message dict

返回在定义域内的样本点 (x0, x1)

生成签名. :param method: :param accept: :param content_type: :param date: :param url_path: :return:

Final visualization version (completely borderless)

Generate visualization for specific step