Deep Learning, Sora, Computer Vision, Transformers, Attention.
i in enumerate(timg): ax.flat[n].imshow(i) ax.flat[n].axis("off") plt.show() images padded to preserve aspect ratio we will create patch embeddings for [3x32x32]. For this we can use a simple convolution layer with kernel and stride as patch_size timg = [torch.from_numpy(x).float().permute((2, 0,