| import torch | |
| from torch.autograd import Function | |
| class GradReverse(Function): | |
| def forward(ctx, x: torch.Tensor, lambd: float) -> torch.Tensor: | |
| ctx.lambd = lambd | |
| return x.view_as(x) | |
| def backward(ctx, grad_output: torch.Tensor) -> torch.Tensor: | |
| return grad_output.neg() * ctx.lambd, None | |
| def grad_reverse(x: torch.Tensor, lambd: float = 1.0) -> torch.Tensor: | |
| return GradReverse.apply(x, lambd) | |