Transforms =================== Data does not always come in its final processed form that is required for training machine learning algorithms. We use **transforms** to perform some manipulation of the data and make it suitable for training. All TorchVision datasets have two parameters -``transform`` to modify the features and ``target_transform`` to modify the labels - that accept callables containing the transformation logic. The `torchvision.transforms <https://pytorch.org/vision/stable/transforms.html>`_ module offers several commonly-used transforms out of the box. The FashionMNIST features are in PIL Image format, and the labels are integers. For training, we need the features as normalized tensors, and the labels as one-hot encoded tensors. To make these transformations, we use ``ToTensor`` and ``Lambda``.