前言
在PTQ量化时，会遇到int16的conv或matmul精度不足，这是因为bpu限制，只支持input和weight一个int16。
本文将讲述在使用地平线PTQ链路基于J6 系列平台进行模型部署时，对conv进行精度调优的相关手段，主要包括以下内容：
如何确定是单int16导致的精度不足？
如何解决这一问题
如何确定是单int16导致的精度不足
使用精度debug工具
得到weight的敏感度分析，如在已经设置int16的情况下，相似度仍然很低，并且在真int16时精度正常，可以确定是单int16导致的精度不足。
node cosine-similarity mse
Conv_60 0.77795 68.02103
Conv_48 0.78428 64.36318
Conv_82 0.80394 61.09268
Conv_94 0.80499 65.05224
Conv_42 0.83787 49.4949
Conv_88 0.84614 49.81132
Conv_54 0.86602 41.69972
Conv_71 0.87148 39.96296
Conv_65 0.87495 40.45997
Conv_25 0.89214 34.30351
Conv_20 0.89829 32.35053
Conv_77 0.89916 31.9907
Conv_14 0.90058 32.40179
Conv_9 0.90107 34.08191
Conv_37 0.91162 28.21194
Conv_31 0.91637 28.79291
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Conv_48 0.78428 64.36318
Conv_82 0.80394 61.09268
Conv_94 0.80499 65.05224
Conv_42 0.83787 49.4949
Conv_88 0.84614 49.81132
Conv_54 0.86602 41.69972
Conv_71 0.87148 39.96296
Conv_65 0.87495 40.45997
Conv_25 0.89214 34.30351
Conv_20 0.89829 32.35053
Conv_77 0.89916 31.9907
Conv_14 0.90058 32.40179
Conv_9 0.90107 34.08191
Conv_37 0.91162 28.21194
Conv_31 0.91637 28.79291
如何解决这一问题
此时可以在config.json文件中配置编译配置如下：配置之后工具会自动进行高低位拆分达到input+weight双int16的效果<div style="text-align:center" data-type="image" data-ace-gallery-json="{"items":[{"uuid":"d72816ff-bbf0-4a76-a9a3-7952834a1a7a","height":625.175879396985,"width":580,"currHeight":625.175879396985,"currWidth":580,"natrualHeight":858,"natrualWidth":796,"pluginName":"imageUpload","scale":0.7286432160804021,"src":"https%3A%2F%2Finternal-api-drive-stream.feishu.cn%2Fspace%2Fapi%2Fbox%2Fstream%2Fdownload%2Fpreview%2FPV9CbTdnUoOqTQxgxiecWkXMnkh%2F%3Fpreview_type%3D16","file_token":"PV9CbTdnUoOqTQxgxiecWkXMnkh","image_type":"image/png","size":53453,"comments":[]}]}" class="image-uploaded gallery old-record-id-JYiSdaOkooQp3bxbVxEciusTngc">
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