Comments (4)
luuuyi
commented on May 18, 2024
基本定位出问题是mask_rcnn从mmdet导出到onnx的时候，fcn_mask_head里面有一个逻辑是让特征图和阈值0.5去比较然后输出mask，在pytorch代码里面全程都是用torch.float和python原生float去做逻辑大小判断，但是通过onnx导出的时候我看了下log，他会把tensor转换为double类型的数据，然后那个0.5的阈值也不再是float32的了，直接就变成了double类型。
这个问题挺奇怪的，int类型的数据做这个逻辑判断的时候，onnx导出也会把tensor转为long类型，然后另一个待比较的值也是会变成long类型，哪怕在mmdet代码里面他们都是int32形式的。
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luuuyi
commented on May 18, 2024
看了下export onnx的log，硬编码把double类型改掉了
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pranerd
commented on May 18, 2024
请问下这个最终怎么解决了的了？
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zhenglongjiepheonix
commented on May 18, 2024
请问下这个最终怎么解决了的了？
建议用onnx强行改掉数据的datatype, tensor和原生类型混合导出的时候确实存在inconsistent datatype的问题，可以看一下这个issue
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Related Issues (20)
- Floating point exception (core dumped) occured when using cuda engine HOT 1
- Floating point exception (core dumped) HOT 1
- Onnx run error HOT 2
- 请问支持int8在高通芯片上cDSP进行推理吗？
- Slice op question HOT 1
- pplnn run mobilenet v2 model failed. (use cuda) HOT 7
- linux compile error protobuf static assertion failed HOT 3
- malloc_consolidate(): invalid chunk size HOT 2
- pplnn save-input 得到的NDARRAY的 shape不正确 HOT 1
- 如何使用cmake的将ppl.nn和依赖ppl.nn的代码一同编译？ HOT 3
- Segmentation fault at ppl::nn::x86::X86Kernel::DumpOutputTensors HOT 5
- 获取模型推理结果（GetOutputs)耗时长 HOT 2
- Install Error HOT 1
- The compilation passed, but an error was reported in test phase HOT 2
- Floating point exception (core dumped) ？ HOT 4
- 使用x86 engine运行resnet50 fp16 onnx模型 core dump
- (Ask) why InferInheritedType handle int8 to fp16 out? HOT 3
- Got wrong output shape when run a Gemm op(transB=0) use cuda HOT 4
- Crash with ONNX Split operator
- 关于全局engine，其他线程引用导致的性能下降问题 HOT 4
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