dataeval.utils.dataset.read_dataset
===================================

.. py:function:: dataeval.utils.dataset.read_dataset(dataset)

   Extract information from a dataset at each index into individual lists of each information position

   :param dataset: Input dataset
   :type dataset: torch.utils.data.Dataset

   :returns: All objects in individual lists based on return position from dataset
   :rtype: List[List[Any]]

   .. warning:: No type checking is done between lists or data inside lists

   .. seealso:: :obj:`torch.utils.data.Dataset`

   .. rubric:: Examples

   >>> import numpy as np
   >>> data = np.ones((10, 1, 3, 3))
   >>> labels = np.ones((10,))
   >>> class ICDataset:
   ...     def __init__(self, data, labels):
   ...         self.data = data
   ...         self.labels = labels
   ...
   ...     def __getitem__(self, idx):
   ...         return self.data[idx], self.labels[idx]

   >>> ds = ICDataset(data, labels)

   >>> result = read_dataset(ds)
   >>> len(result)  # images and labels
   2
   >>> np.asarray(result[0]).shape  # images
   (10, 1, 3, 3)
   >>> np.asarray(result[1]).shape  # labels
   (10,)