Vote How to implement gradient reversal (GRL) layer in PL?

[M-A-Hassan]

I am training a DA network where I use GRL in the discriminator to train the encoder?
Is the GRL layer implementation in PL similar to the PyTorch one?

`
from torch.autograd import Function
class GradReverse(Function):
@staticmethod
def forward(ctx, x, alpha):
ctx.alpha = alpha
return x.view_as(x)
print(alpha)
@staticmethod
def backward(ctx, grad_output):
output = grad_output * -ctx.alpha

    return output, None

def grad_reverse(x,alpha):
return GradReverse.apply(x,alpha)

#In the discriminator forward pass

def forward(self, y,alpha):
self.alpha=alpha
y = grad_reverse(y,self.alpha)

  y=self.classifier3(y)
  return y

`

[xianyuanliu]

Hi, have you tested GRL in PyTorch-lightning?

[mshooter]

Hi everyone,
has anyone tried this yet ?