Spaces:
Paused
Paused
File size: 1,499 Bytes
78db0f1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS
@DATASETS.register_module()
class ConcatDataset(_ConcatDataset):
"""A wrapper of concatenated dataset.
Same as :obj:`torch.utils.data.dataset.ConcatDataset`, but
concat the group flag for image aspect ratio.
Args:
datasets (list[:obj:`Dataset`]): A list of datasets.
"""
def __init__(self, datasets):
super(ConcatDataset, self).__init__(datasets)
self.CLASSES = datasets[0].CLASSES
self.PALETTE = datasets[0].PALETTE
@DATASETS.register_module()
class RepeatDataset(object):
"""A wrapper of repeated dataset.
The length of repeated dataset will be `times` larger than the original
dataset. This is useful when the data loading time is long but the dataset
is small. Using RepeatDataset can reduce the data loading time between
epochs.
Args:
dataset (:obj:`Dataset`): The dataset to be repeated.
times (int): Repeat times.
"""
def __init__(self, dataset, times):
self.dataset = dataset
self.times = times
self.CLASSES = dataset.CLASSES
self.PALETTE = dataset.PALETTE
self._ori_len = len(self.dataset)
def __getitem__(self, idx):
"""Get item from original dataset."""
return self.dataset[idx % self._ori_len]
def __len__(self):
"""The length is multiplied by ``times``"""
return self.times * self._ori_len
|