Class ValDataLoaderIter

monai/optimizers/lr_finder.py:97–131

This iterator will reset itself **only** when it is acquired by the syntax of normal `iterator`. That is, this iterator just works like a `torch.data.DataLoader`. If you want to restart it, you should use it like: ``` loader_iter = ValDataLoaderIter(data_loader)

class ValDataLoaderIter(DataLoaderIter):
    """This iterator will reset itself **only** when it is acquired by
    the syntax of normal `iterator`. That is, this iterator just works
    like a `torch.data.DataLoader`. If you want to restart it, you
    should use it like:

        ```
        loader_iter = ValDataLoaderIter(data_loader)
        for batch in loader_iter:
            ...

        # `loader_iter` should run out of values now, you can restart it by:
        # 1. the way we use a `torch.data.DataLoader`
        for batch in loader_iter:        # __iter__ is called implicitly
            ...

        # 2. passing it into `iter()` manually
        loader_iter = iter(loader_iter)  # __iter__ is called by `iter()`
        ```
    """

    def __init__(self, data_loader: DataLoader, image_extractor: Callable, label_extractor: Callable) -> None:
        super().__init__(data_loader, image_extractor, label_extractor)
        self.run_limit = len(self.data_loader)
        self.run_counter = 0

    def __iter__(self):
        if self.run_counter >= self.run_limit:
            self._iterator = iter(self.data_loader)
            self.run_counter = 0
        return self

    def __next__(self):
        self.run_counter += 1
        return super().__next__()


def default_image_extractor(x: Any) -> torch.Tensor: