def METHOD_NAME(self):
    s = 256
    img_metas = [{
        'img_shape': (s, s),
        'pad_shape': (s, s),
        'scale_factor': (1, 1)
    }]
    guided_anchor_head = GuidedAnchorHead(**guided_anchor_head_config)
    feats = (
        torch.rand(1, 4, s // stride[1], s // stride[0])
        for stride in guided_anchor_head.square_anchor_generator.strides)
    outs = guided_anchor_head(feats)
    guided_anchor_head.predict_by_feat(
        *outs, batch_img_metas=img_metas, rescale=True)