distance_gan_model.py 文件源码

def get_expectation(self, num_items, vars):

        num_pairs = 0
        distance_sum = 0.0

        # If self distance computed expectation for top and bottom half
        if self.use_self_distance:
            for i in xrange(num_items):
                # Split image to top and bottom half
                var_half_1, var_half_2 = torch.chunk(vars[i], 2, dim=2)
                distance_sum += self.as_np(self.distance(var_half_1, var_half_2))
            return distance_sum / num_items

        # Otherwise compute expectation for all pairs of images
        for i in xrange(num_items - 1):
            for j in xrange(i + 1, num_items):
                num_pairs += 1
                distance_sum += self.as_np(self.distance(vars[i], vars[j]))

        return distance_sum / num_pairs