Deep Learning, Sora, Computer Vision, Transformers, Attention.
1].numpy(), marker='o', linestyle='', s=3) ax.axis("off") plt.show() center of each patch fractional = centers/max(w, h) fractional.shape #torch.Size([432, 2]) pe = nn.Linear(2, 768//2) pe_out = pe(fractional) pe_out.shape #torch.Size([432, 384]) pe_out = 2* torch.pi * pe_out pe_out =