Optimization, Pytorch, Machine Learning, Deep Learning, Tensorboard.
np.random.randint(low=0,high=num_classes,size=(10000),dtype=np.uint16).tolist() def __getitem__(self, index): img, target = self.data[index], self.targets[index] img = Image.fromarray(img) if self.transform is not None: img = self.transform(img) return img, target def __len__(self) -> int: return