Pytorch, Deep Learning, Optimization, Tensorboard, Deep Dives.
input as an 8-bit uint8 tensor transform = T.Compose( [T.Resize(224), T.PILToTensor() ]) train_set = FakeCIFAR(transform=transform) train_loader = torch.utils.data.DataLoader(train_set, batch_size=1024, shuffle=True, num_workers=8, pin_memory=True) device = torch.device("cuda:0") model =