0c63b9dcd7ee3da39c74379a01d16e3a360d3506,niftynet/layer/resampler.py,ResamplerLayer,_resample_inv_dst_weighting,#ResamplerLayer#,178

Before Change

        point_weights = tf.expand_dims(point_weights, axis=-1)

        // find N neighbours associated to each output point
        knots_id = tf.gather_nd(all_coords, weight_id)
        knots_id = tf.transpose(
            knots_id, [0] + range(2, out_spatial_rank + 3) + [1])
        // get values of N neighbours
        samples = [

After Change

        // gather_nd for both matrix, the same as:
        // point_weights = tf.gather_nd(diff, weight_id)
        // knots_id = tf.gather_nd(all_coords_f, weight_id)
        n_val = tf.gather_nd(tf.stack([diff, all_coords_f], axis=-1), weight_id)
        n_val = tf.unstack(n_val, axis=-1)
        point_weights, knots_id = n_val[0], n_val[1]

        point_weights = tf.reduce_sum(point_weights, axis=1)
        // skip this as power = 2:
        // self.power = 2

Instances