A PyTorch implementation for paper Unsupervised Domain Adaptation by Backpropagation
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from torch.autograd import Function
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class ReverseLayerF(Function):
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@staticmethod
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def forward(ctx, x, alpha):
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ctx.alpha = alpha
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return x.view_as(x)
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@staticmethod
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def backward(ctx, grad_output):
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output = grad_output.neg() * ctx.alpha
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#print("reverse gradient is {}".format(output))
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return output, None
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