Class SampleIterableDataset

src/transformers/tests/trainer/test_trainer.py:274–280

if is_torch_available():

    class SampleIterableDataset(IterableDataset):
        def __init__(self, a=2, b=3, length=64, seed=42, label_names=None):
            self.dataset = RegressionDataset(a=a, b=b, length=length, seed=seed, label_names=label_names)

        def __iter__(self):
            for i in range(len(self.dataset)):
                yield self.dataset[i]

    class FiniteIterableDataset(SampleIterableDataset):
        def __init__(self, a=2, b=3, length=64, seed=42, label_names=None):