train_tools.data_utils.datasetter

Module Contents

train_tools.data_utils.datasetter.get_dataloaders_labeled(root, mapping_file, mapping_file_tuning, join_mapping_file=None, valid_portion=0.0, batch_size=8, amplified=False, relabel=False)[source]

Set DataLoaders for labeled datasets.

Parameters:
  • root (str) – root directory

  • mapping_file (str) – json file for mapping dataset

  • valid_portion (float, optional) – portion of valid datasets. Defaults to 0.1.

  • batch_size (int, optional) – batch size. Defaults to 8.

  • shuffle (bool, optional) – shuffles dataloader. Defaults to True.

  • num_workers (int, optional) – number of workers for each datalaoder. Defaults to 5.

Returns:

dictionary of data loaders.

Return type:

dict

train_tools.data_utils.datasetter.get_dataloaders_public(root, mapping_file, valid_portion=0.0, batch_size=8)[source]

Set DataLoaders for labeled datasets.

Parameters:
  • root (str) – root directory

  • mapping_file (str) – json file for mapping dataset

  • valid_portion (float, optional) – portion of valid datasets. Defaults to 0.1.

  • batch_size (int, optional) – batch size. Defaults to 8.

  • shuffle (bool, optional) – shuffles dataloader. Defaults to True.

Returns:

dictionary of data loaders.

Return type:

dict

train_tools.data_utils.datasetter.get_dataloaders_unlabeled(root, mapping_file, batch_size=8, shuffle=True, num_workers=5)[source]

Set dataloaders for unlabeled dataset.