1 files changed, 0 insertions, 47 deletions
diff --git a/data/custom_dataset_data_loader.py b/data/custom_dataset_data_loader.py
deleted file mode 100644
index 787946f..0000000
--- a/data/custom_dataset_data_loader.py
+++ /dev/null
@@ -1,47 +0,0 @@
-import torch.utils.data
-from data.base_data_loader import BaseDataLoader
-
-
-def CreateDataset(opt):
-    dataset = None
-    if opt.dataset_mode == 'aligned':
-        from data.aligned_dataset import AlignedDataset
-        dataset = AlignedDataset()
-    elif opt.dataset_mode == 'unaligned':
-        from data.unaligned_dataset import UnalignedDataset
-        dataset = UnalignedDataset()
-    elif opt.dataset_mode == 'single':
-        from data.single_dataset import SingleDataset
-        dataset = SingleDataset()
-    else:
-        raise ValueError("Dataset [%s] not recognized." % opt.dataset_mode)
-
-    print("dataset [%s] was created" % (dataset.name()))
-    dataset.initialize(opt)
-    return dataset
-
-
-class CustomDatasetDataLoader(BaseDataLoader):
-    def name(self):
-        return 'CustomDatasetDataLoader'
-
-    def initialize(self, opt):
-        BaseDataLoader.initialize(self, opt)
-        self.dataset = CreateDataset(opt)
-        self.dataloader = torch.utils.data.DataLoader(
-            self.dataset,
-            batch_size=opt.batchSize,
-            shuffle=not opt.serial_batches,
-            num_workers=int(opt.nThreads))
-
-    def load_data(self):
-        return self
-
-    def __len__(self):
-        return min(len(self.dataset), self.opt.max_dataset_size)
-
-    def __iter__(self):
-        for i, data in enumerate(self.dataloader):
-            if i >= self.opt.max_dataset_size:
-                break
-            yield data