def _global_pooling()

in scripts/modules/deeplab.py [0:0]

• 22 lines of code
• 5 McCabe index (conditional complexity)

    def _global_pooling(self, x):
        if self.training or self.pooling_size is None:
            pool = x.view(x.size(0), x.size(1), -1).mean(dim=-1)
            pool = pool.view(x.size(0), x.size(1), 1, 1)
        else:
            pooling_size = (
                min(try_index(self.pooling_size, 0), x.shape[2]),
                min(try_index(self.pooling_size, 1), x.shape[3]),
            )
            padding = (
                (pooling_size[1] - 1) // 2,
                (pooling_size[1] - 1) // 2
                if pooling_size[1] % 2 == 1
                else (pooling_size[1] - 1) // 2 + 1,
                (pooling_size[0] - 1) // 2,
                (pooling_size[0] - 1) // 2
                if pooling_size[0] % 2 == 1
                else (pooling_size[0] - 1) // 2 + 1,
            )

            pool = functional.avg_pool2d(x, pooling_size, stride=1)
            pool = functional.pad(pool, pad=padding, mode="replicate")
        return pool