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Bug fixes to LinearWithAuxLoss
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@ -404,8 +404,15 @@ class LinearWithAuxLossFunction(torch.autograd.Function):
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@staticmethod
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def backward(ctx, ans_grad: Tensor) -> Tuple[Tensor, Tensor, Tensor, None]:
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x, weight, alpha = ctx.saved_tensors
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x_grad = torch.matmul(ans_grad, weight.to(ans_grad.dtype))
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weight_grad = torch.matmul(ans_grad.reshape(-1, ans_grad.shape[-1]).t(),
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x.reshape(-1, x.shape[-1]).to(ans_grad.dtype))
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with torch.cuda.amp.autocast(enabled=False):
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with torch.enable_grad():
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x = x.to(weight.dtype)
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x, weight, alpha = x.detach(), weight.detach(), alpha.detach()
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weight.requires_grad = True
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alpha.requires_grad = True
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@ -423,9 +430,6 @@ class LinearWithAuxLossFunction(torch.autograd.Function):
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weight_aux_grad = weight.grad
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alpha_grad = alpha.grad
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x_grad = torch.matmul(ans_grad, weight.to(ans_grad.dtype))
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weight_grad = torch.matmul(ans_grad.reshape(-1, ans_grad.shape[-1]).t(),
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x.reshape(-1, x.shape[-1]).to(ans_grad.dtype))
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with torch.cuda.amp.autocast(enabled=False):
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weight_grad_norm = weight_grad.to(torch.float32).norm()
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