Optimization, Pytorch, Machine Learning, Deep Learning, Tensorboard.
len(self.data) transform = T.Compose([T.PILToTensor()]) train_set = FakePatches(transform=transform) train_loader = torch.utils.data.DataLoader(train_set, batch_size=128, shuffle=True, num_workers=8, pin_memory=True) device = torch.device("cuda:0") model = Net().cuda(device) criterion =