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如图,你给出的源码在推理阶段仍然采用get_seg_model的方法来返回model对象,在模型底层设置的argument参数永远是True,在Fullmodel这个类里面返回的[x_extra_p, x_bag],这样也就解释了你设置输出nums数目为2,测试时的索引为1,我没理解错误的话,应该是要获取x_bag的结果吧?但是,推理阶段按照论文的说法,不应该只保留x_bag这一个结果吗?如果你仍然采用get_seg_model来获取测试时的结果,是不是说明辅助分支也影响到了推理精度?只不过在单纯速度的推理指标方面,你舍弃了辅助分割头吧
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如图,你给出的源码在推理阶段仍然采用get_seg_model的方法来返回model对象,在模型底层设置的argument参数永远是True,在Fullmodel这个类里面返回的[x_extra_p, x_bag],这样也就解释了你设置输出nums数目为2,测试时的索引为1,我没理解错误的话,应该是要获取x_bag的结果吧?但是,推理阶段按照论文的说法,不应该只保留x_bag这一个结果吗?如果你仍然采用get_seg_model来获取测试时的结果,是不是说明辅助分支也影响到了推理精度?只不过在单纯速度的推理指标方面,你舍弃了辅助分割头吧
The text was updated successfully, but these errors were encountered: