# Runs torch.einsum(ijk,ijk->jk, tensor1, tensor2)
im.dot("height", im2).shape
OrderedDict([('width',...96), ('channels', 3)])
# Runs torch.einsum(ijk,ijk->il, tensor1, tensor2)
im.dot("width", im2).shape...OrderedDict([('height', 96), ('channels', 3)])
# Runs torch.einsum(ijk,ijk->l, tensor1, tensor2)
im.dot...("ijk,ij->ik", [Y, at]) + \
torch.tanh(torch.einsum("ij,jk->ik", [rt1, params.Wt.values]) +...与 PyTorch 模块交互:我们是否可以通过类型注释「lift」PyTorch 模块,从而了解它们是如何改变输入的?