86a4393efb842ad65bd170c8beacd40119fd27be,pointcnn.py,PointCNN,__init__,#PointCNN#Any#Any#Any#Any#Any#Any#,53

Before Change

            fts_xconv = xconv(pts, fts, qrs, tag, N, K, D, P, C, C_pts_fts, is_training, with_X_transformation,
                              depth_multiplier, sorting_method)
            if links:
                fts_list = [tf.slice(self.layer_fts[link], (0, 0, 0), (-1, P, -1), name=tag + "fts_list"+str(link))
                            for link in links if self.layer_fts[link] is not None]
                fts_list.append(fts_xconv)
                self.layer_fts.append(tf.concat(fts_list, axis=-1, name=tag + "fts_list_concat"))
            else:
                self.layer_fts.append(fts_xconv)

After Change

                    fts_from_link = self.layer_fts[link]
                    if fts_from_link is not None:
                        fts_slice = tf.slice(fts_from_link, (0, 0, 0), (-1, P, -1), name=tag + "fts_slice_"+str(-link))
                        C_forward = math.ceil(fts_slice.get_shape().as_list()[-1] / (-link))
                        fts_forward = pf.dense(fts_slice, C_forward, tag + "fts_forward_"+str(-link), is_training)
                        fts_list.append(fts_forward)
                self.layer_fts.append(tf.concat(fts_list, axis=-1, name=tag + "fts_list_concat"))

Instances