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| # select device (whether GPU or CPU) | |
| device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu') | |
| # DataLoader is iterable over Dataset | |
| for imgs, annotations in data_loader: | |
| imgs = list(img.to(device) for img in imgs) | |
| annotations = [{k: v.to(device) for k, v in t.items()} for t in annotations] | |
| print(annotations) |
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