def METHOD_NAME():
    import itertools
    import multiprocessing
    from torch.utils.data import DataLoader
    from composer import Trainer
    multiprocessing.cpu_count = lambda: 2
    original_fit = Trainer.fit
    def new_fit(self: Trainer, *args, **kwargs):
        if 'duration' not in kwargs:
            kwargs['duration'] = '2ep'
        if 'train_subset_num_batches' not in kwargs:
            kwargs['train_subset_num_batches'] = 2
        if 'eval_dataloader' in kwargs and 'eval_subset_num_batches' not in kwargs:
            kwargs['eval_subset_num_batches'] = 1
        original_fit(self, *args, **kwargs)
    Trainer.fit = new_fit
    original_iter = DataLoader.__iter__
    def new_iter(self: DataLoader):
        return itertools.islice(original_iter(self), 2)
    DataLoader.__iter__ = new_iter  # type: ignore  # error: DataLoader has a stricter return type than islice