:py:mod:`kosmos.ml.dataloader`
==============================

.. py:module:: kosmos.ml.dataloader








Functions
---------

.. py:function:: make_train_test_dataloaders(dataset: kosmos.ml.datasets.dataset.SLDataset, train_split: float, batch_size: int, num_train_subsets: int = 1) -> tuple[list[torch.utils.data.DataLoader], torch.utils.data.DataLoader]

   Split a dataset into training and test subsets and wrap them in DataLoaders.

   The training loaders shuffle their subset each epoch; the test loader does not.

   :param dataset: The dataset to be split.
   :param train_split: Fraction of dataset for training. Test split is 1 - train_split.
   :param batch_size: Number of samples per batch in both loaders.
   :param num_train_subsets: Number of partitions to split the training subset into. Defaults to 1.

   :returns:

             A tuple containing:

                 - list[DataLoader]: DataLoaders for the partitions of the training subset.
                 - DataLoader: DataLoader for the test subset.
   :rtype: tuple[list[DataLoader], DataLoader]