Parses the 'predict' string and returns a dictionary. Handles nested dictionaries and missing or unparseable content gracefully. Paramet

根据数字系统类型返回创建相应的数字系统，默认为 mid NUMBERING_TYPES = ['low', 'mid', 'high']: 中文数字系统类型 low: '兆' = '亿' * '十' = $10^{9}$, '京' = '兆' * '十', et

Decode the video and return the RGB frames

`torch.device`: The device on which the module is (assuming that all the module parameters are on the same device).

Returns a dictionary representing the task's config. :returns: str The fewshot context.

Evaluate a multiple choice instance. https://github.com/MMMU-Benchmark/MMMU/blob/51ce7f3e829c16bb44bc5445782686b4c3508794/eval/eval_utils.py#

Parameters: - args: Arguments. - results: Results to evaluate. - eval_method: The evaluation method. either "openai".

Evaluates the mathematical expressions within tuples or lists represented as strings. Args: s (str): The string representation of a

Evaluates the functional correctness of a model.

Overrides `generate` function to be able to use the model as a conditional generator. Args: pixel_values (`torch.Flo

Function to generate all possible combinations of values from a dictionary.

Divides an iterable into chunks of specified size or based on a given function. Useful for batching Parameters: - it

Given the sample results filenames, extracts and returns the task name.

Returns the keyward args of `build_description`.

In the reverse process, the interval [0, 1] is uniformly discretized into steps intervals. Furthermore, because LLaDA employs a linear nois

In the reverse process, the interval [0, 1] is uniformly discretized into steps intervals. Furthermore, because LLaDA employs a linear nois