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PPL_DSP_INT8量化后export问题 #86

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Menace-Dragon opened this issue May 4, 2022 · 8 comments
Closed

PPL_DSP_INT8量化后export问题 #86

Menace-Dragon opened this issue May 4, 2022 · 8 comments

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@Menace-Dragon
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Menace-Dragon commented May 4, 2022 •
edited

GPU模式下，在跑RetinaFace（backbone为ResNet50时），量化过程成功跑完，在导出时报TypeError: Cannot convert Resize_133 to caffe op。debug发现是因为没有满足ppq/parser/caffe/caffe_export_utils.py 的第439行判断而导致的。
@Menace-Dragon Menace-Dragon reopened this May 4, 2022
@Menace-Dragon
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Capture
如图，（当然你也发现了，该resize算子输入尺寸为23x23，输出为45x45，居然不是2倍关系，我也迷惑

@Menace-Dragon
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但是我又看了一下，该模型是Pytorch.onnx export出来的opset11，应该是比较正常的算子，Resize算子写的虽然省略了东西但是应该没毛病（ONNXRuntime可以跑通该模型）

@ZhangZhiPku
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据我所知你拿ppq转换onnx的模型到caffe问题可多了，或者从caffe转换到onnx也一堆问题，主要是它们有些定义好像不是很一样...你确定要这样搞的话可以解除439行的判断试试，虽然它后面可能还要别的问题。

@Menace-Dragon
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有道理，emmmmmmmm那我暂时先不考虑这个模型了

@ZhangZhiPku
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好像就只有caffe进caffe出是可以的，你这个东西是输入了一个onnx然后要导出caffe？

@Menace-Dragon
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确实，我才意识到，PPL_DSP_INT8只能导出CaffeModel。再叨扰问一下，，，PPL_DSP_INT8的DSP，指的是量化完成的模型是在CPU上运行的吗？

@ZhangZhiPku
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好像不是这样的，这个PPL_DSP_INT8指的是按照PPL_DSP的量化规则对模型进行量化，确定每一个算子的具体量化细节。这一规则适用于PPL_DSP和SNPE平台。

@Menace-Dragon
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ohh明白了，感谢

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@ZhangZhiPku @Menace-Dragon