Comments (11)
@stricklandye 请教个不相关问题哈:你是直接tf转mnn格式吗?没有经过通用onnx格式吗?谢谢
是的,我直接将tf转为forzen model,然后转MNN。如果你有tf->onxx->mnn的需求,可以参考一下 tf2onnx 这个库。
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I looked at the inference code and did not consider the input NC4HW4 layout. When converting the mnn model, add --keepInputFormat. After testing and adding this option, the inference results were normal using the original code.
Hey i am also facing a similar issue. Can you please explain what --keepInputFormat flag does and how is it related to input NC4HW4 layout.
Thanks
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这个错误是在使用 tensorflow 推理,生成测试数据的过程出的。原因是 testMNNFromTf.py 会随机构造输入,有些输入可能是无效的。找一组运行通过的就可以了。
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发下你的使用代码,另外可以用 ./SequenceModuleTest.out 去测试多次输入的情况。现在无法判断是否是你使用代码的问题。
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发送到我邮箱即可,[email protected]
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感谢大佬帮助,我稍后整理一下发到邮箱里。
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@jxt1234 大佬,名为 《MNN推理结果异常反馈》的邮件已经发送了,再次感谢热心帮助。
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@stricklandye 请教个不相关问题哈:你是直接tf转mnn格式吗?没有经过通用onnx格式吗?谢谢
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看了下推理的代码没有考虑 输入的 NC4HW4 布局,转 mnn 模型时加上 --keepInputFormat 吧,测试了下加上这个选项后用原来代码推理结果就正常了。
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与 tf 的对比方面,基于 testMNNFromTf.py ,修改下代码里面 tf 输入的部分,构造测试用例对比吧。
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@jxt1234 感谢社区的帮助,TF的推理差异是我有一个细微的地方代码写错。经过验证以后,准确率无误,--keepInputFormat也解决了跳变的问题。
再次感谢,我将 issue关了。
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