Source code for ding.utils.data.base_dataloader

from typing import Optional, Callable, List, Any, Iterable
import torch


def example_get_data_fn() -> Any:
    """
    Overview:
        Get data from file or other middleware
    .. note::
        staticmethod or static function, all the operation is on CPU
    """
    # 1. read data from file or other middleware
    # 2. data post-processing(e.g.: normalization, to tensor)
    # 3. return data
    pass


class IDataLoader:
    """
    Overview:
        Base class of data loader
    Interfaces:
        ``__init__``, ``__next__``, ``__iter__``, ``_get_data``, ``close``
    """

    def __next__(self, batch_size: Optional[int] = None) -> torch.Tensor:
        """
        Overview:
            Get one batch data
        Arguments:
            - batch_size (:obj:`Optional[int]`): sometimes, batch_size is specified by each iteration, \
                if batch_size is None, use default batch_size value
        """
        # get one batch train data
        if batch_size is None:
            batch_size = self._batch_size
        data = self._get_data(batch_size)
        return self._collate_fn(data)

    def __iter__(self) -> Iterable:
        """
        Overview:
            Get data iterator
        """

        return self

    def _get_data(self, batch_size: Optional[int] = None) -> List[torch.Tensor]:
        """
        Overview:
            Get one batch data
        Arguments:
            - batch_size (:obj:`Optional[int]`): sometimes, batch_size is specified by each iteration, \
                if batch_size is None, use default batch_size value
        """

        raise NotImplementedError

    def close(self) -> None:
        """
        Overview:
            Close data loader
        """

        # release resource
        pass