1. main.py: train_data = MyDataset(txt_path=train_txt_path, ...˅ --->
2. main.py: train_loader = DataLoader(dataset=train_data, ...) --->
3. main.py: for i, data in enumerate(train_loader, 0) --->
4. dataloder.py: class DataLoader(): def __iter__(self): return _DataLoaderIter(self) --->
5. dataloder.py: class _DataLoderIter(): def __next__(self): batch = self.collate_fn([self.dataset[i] for i in indices]) --->
6. tool.py: class MyDataset(): def __getitem__(): img = Image.open(fn).convert('RGB') --->
7. tool.py: class MyDataset(): img = self.transform(img) --->
8. main.py: inputs, labels = data inputs, labels = Variable(inputs), Variable(labels) outputs = net(inputs)
