Pytorch, Optimization, Deep Learning, Artificial Intelligence, Tensorboard.
__len__(self): return 1000000 def __getitem__(self, index): rand_image = torch.randn([3, 224, 224], dtype=torch.float32) label = torch.tensor(data=[index % 1000], dtype=torch.int64) return rand_image, label train_set = FakeDataset() train_loader = torch.utils.data.DataLoader(train_set,