51940831ed707cec2427bcad984b192c839bb66a,niftynet/contrib/sampler_pairwise/sampler_pairwise_uniform.py,PairwiseUniformSampler,layer_op,#PairwiseUniformSampler#,107

Before Change

            image_id = tf.reshape(image_id, (1,1))
            start_location = tf.zeros((1, self.spatial_rank))
            end_location = tf.constant(self.window_size[:self.spatial_rank])
            end_location = tf.reshape(end_location, (1, self.spatial_rank))
            end_location = tf.to_float(end_location)
            locations = tf.concat([image_id, start_location, end_location], axis=1)
        return windows, locations

After Change

            resampler = ResamplerLayer(
                interpolation="linear", boundary="replicate")
            windows = resampler(combined_volume, computed_grid)
            out_shape = [self.batch_size] + \
                        list(self.window_size[:self.spatial_rank]) + \
                        [window_channels]
            windows.set_shape(out_shape)

Instances