Compute the Intersection over Union (IoU) of two bounding boxes. Parameters: - box1 (list of float): Bounding box [x_min, y_min, x_max,

Compute the Intersection over Union (IoU) of two bounding boxes. Parameters: - box1 (list of float): Bounding box [x_min, y_min, x_max,

Compute the Intersection over Union (IoU) of two bounding boxes. Parameters: - box1 (list of float): Bounding box [x_min, y_min, x_max,

Compute the Intersection over Union (IoU) of two bounding boxes. Parameters: - box1 (list of float): Bounding box [x_min, y_min, x_max,

Compute the value. When current unit is larger than previous unit, current unit * all previous units will be used as all previous uni

(Recursively) calculates groups' aggregated metrics and updates the results and versions dictionaries with this info. @return: a tuple [resu

@param eval_tasks: list(TaskOutput). @return: A tuple containing the consolidated results, samples, configs, versions, and num_fewshot.

Uses RequestFactory to construct Requests and returns an iterable of Requests which will be sent to the LMM. :param doc_id: int

Given a list of table rows, build the corresponding html string, which is used to compute the TEDS score. We use the official code of PubTabN

Copy current averaged parameters into given collection of parameters. Args: parameters: Iterable of `torch.nn.Parame

Copy current averaged parameters into given collection of parameters. Args: parameters: Iterable of `torch.nn.Parame

一百八 to 一百八十 一亿一千三百万 to 一亿 一千万 三百万

Count the number of syllables in a piece of text.

Creates an instance of the LMM class using the given argument string and additional config. Parameters: - arg_string: A stri

Method for creating a (potentially) sliced and limited iterator from a raw document iterator. Used for splitting data among ranks in mult

Utility function

Utility function

Utility function

Custom lemmatization to handle special cases like 'puppies' -> 'puppy'.

Returns a Unicode object on success, or None on failure

Default decoding function from LLaDA paper

Calculate keyword-based statistics for skills, input_format, and output_format.

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

Disable the redundant torch default initialization to accelerate model creation.

Download 'punkt' if not already installed

Encode an image into base64 and return its mime type.