r""" Returns a list of names of parameters with weight decay. (weights in non-layernorm layers)

r""" Gets arguments to load config/tokenizer/model. Note: including inplace operation of model_args.

r""" Gets the dict to update the components.

r""" Creates reference model for PPO/DPO training. Evaluation mode is not supported. The valuehead parameter is randomly initialized since it

r""" The model is already unwrapped. There are three cases: 1. full tuning without ds_zero3: state_dict = {"model.layers.*": ..., "v_head

r""" Gets the base elements that are commonly used.

r""" Gets logits processor that removes NaN and Inf logits.

Returns an array of tuples, containing the string `input`, sympy `output` using the provided sympy `func`, and `symbolically` boolean for cal

Apply ceil() then return the ceil-ed expression. expr: Expr - sympy expression as an argument to ceil()

Apply floor() then return the floored expression. expr: Expr - sympy expression as an argument to floor()

r""" Loads model config.

r""" Gets the response token-by-token of the chat model.

r""" Converts elements to token ids.

r""" Encodes formatted inputs to pairs of token ids. Turn 0: prefix + system + query resp Turn t: sep + query

r""" Gets the merged datasets in the standard format.

r""" Preprocesses the dataset, including format checking and tokenization.

r""" Computes video sample frames according to fps.

r""" input: a dict with keys {"question", "A", "B", "C", "D", "answer"} output: a tuple of (prompt, response)

r""" Pre-processes a single image.

r""" Regularizes images to avoid error. Including reading and pre-processing.

r""" Asynchronously gets a list of responses of the chat model.

r""" Asynchronously gets a list of scores of the reward model.

r""" Asynchronously gets the response token-by-token of the chat model.

r""" Removes args with NoneType or False or empty string value.