manuel-delverme · August 29, 2021 18:11
diff --git a/mnist_classifier.py b/mnist_classifier.py
        def closure():
            output = model(data)
            loss = F.nll_loss(output, target)
            layer_norm = torch.mean(torch.tensor([p.norm() for p in model.parameters()]))
            ineq_defect = [
                (layer_norm - 0.025).reshape(1, -1),
            ]
            return loss, None, ineq_defect
	def closure():
	output = model(data)
	loss = F.nll_loss(output, target)
	layer_norm = torch.mean(torch.tensor([p.norm() for p in model.parameters()]))
	ineq_defect = [
	(layer_norm - 0.025).reshape(1, -1),
	]
	return loss, None, ineq_defect