299392c6e0618088e4f3deeb50dd23094c5e8261,se3_cnn/non_linearities/scalar_activation.py,BiasRelu,__init__,#BiasRelu#Any#Any#,6

Before Change

            self.batch_norms = []
            for d, on in self.enable:
                if on:
                    bn = torch.nn.BatchNorm3d(d, affine=False)
                    setattr(self, "bn{}".format(len(self.batch_norms)), bn)
                    self.batch_norms.append(bn)

        nbias = sum([d for d, on in self.enable if on])
        self.bias = Parameter(torch.FloatTensor(nbias)) if nbias > 0 else None

After Change

        nbias = sum([d for d, on in self.enable if on])
        if nbias > 0:
            self.bias = Parameter(torch.FloatTensor(nbias))
            self.bias.data[:] = 0
        else:
            self.bias = None

        self.normalize = normalize

Instances