a1f8ebb0c6d04e6583ed9d9f06a89b8d5d53e8f0,niftynet/network/interventional_affine_net.py,INetAffine,layer_op,#INetAffine#,43

Before Change

        img = tf.concat([moving_image, fixed_image], axis=-1)
        res_1, _ = DownRes(self.fea[0], **self.res_param)(img, is_training)
        res_2, _ = DownRes(self.fea[1], **self.res_param)(res_1, is_training)
        res_3, _ = DownRes(self.fea[2], **self.res_param)(res_2, is_training)
        res_4, _ = DownRes(self.fea[3], **self.res_param)(res_3, is_training)

        conv_5 = Conv(n_output_chns=self.fea[4],
                      kernel_size=self.k_conv,

After Change

        moving_image = Resize(spatial_shape)(moving_image)
        img = tf.concat([moving_image, fixed_image], axis=-1)
        res_1 = DownRes(self.fea[0], **self.res_param)(img, is_training)[0]
        res_2 = DownRes(self.fea[1], **self.res_param)(res_1, is_training)[0]
        res_3 = DownRes(self.fea[2], **self.res_param)(res_2, is_training)[0]
        res_4 = DownRes(self.fea[3], **self.res_param)(res_3, is_training)[0]

        conv_5 = Conv(n_output_chns=self.fea[4],
                      kernel_size=self.k_conv,

Instances