Constructs a BertTokenizer. Args: **vocab_file**: Path to a one-wordpiece-per-line vocabulary file **do_lower_cas

Constructs a BasicTokenizer. Args: **do_lower_case**: Whether to lower case the input. **never_split**: (`option

Args: json_file (str): path to the json file. New data will be appended if the file exists. window_size (int): the wi

Args: log_dir (str): the directory to save the output events window_size (int): the scalars will be median-smoothed b

Args: max_iter: the maximum number of iterations to train. Used to compute ETA. If not given, ETA will not be pri

Args: start_iter (int): the iteration number to start with

Each argument is a function that takes one argument: the trainer.

Args: warmup_iter (int): the number of iterations at the beginning to exclude from timing.

Args: writers (list[EventWriter]): a list of EventWriter objects period (int):

Args: optimizer (torch.optim.Optimizer): scheduler (torch.optim.LRScheduler): If any argument is not given,

Args: enable_predicate (callable[trainer -> bool]): a function which takes a trainer, and returns whether to enab

Args: period (int): the period this hook is run, or 0 to not run during training. The hook will always run in the

Args: cfg (CfgNode):

Args: lst (list): a list which contains elements to produce. copy (bool): whether to deepcopy the element when produc

singular instance