cuda推理输出为全0，cpu推理输出正常

[bigsealing]

平台(如果交叉编译请再附上交叉编译目标平台):

linux

Github版本: 2.3.1 ，因为2.4.2无法编译cuda版本，所以采用2.3.1能编译出cuda版本。

编译方式:

Compiling Method

cmake .. -DMNN_USE_SYSTEM_LIB=true -DMNN_SEP_BUILD=false -DMNN_BUILD_CONVERTER=true && make -j8

请在这里粘贴cmake参数或使用的cmake脚本路径以及完整输出
Paste cmake arguments or path of the build script used here as well as the full log of the cmake proess here or pastebin
```--
-- 3.19.0.0
-- Performing Test protobuf_HAVE_BUILTIN_ATOMICS
-- Performing Test protobuf_HAVE_BUILTIN_ATOMICS - Success
-- Use Threadpool, forbid openmp
-- >>>>>>>>>>>>>
-- MNN BUILD INFO:
--      System: Linux
--      Processor: x86_64
--      Version: 2.3.1
--      Metal: OFF
--      OpenCL: OFF
--      OpenGL: OFF
--      Vulkan: OFF
--      ARM82: OFF
--      oneDNN: OFF
--      TensorRT: OFF
--      CoreML: OFF
--      NNAPI: OFF
--      CUDA: ON
--      OpenMP: OFF
--      BF16: OFF
--      ThreadPool: ON
--      Hidden: TRUE
--      Build Path: /disk4/wangxu/MNN/build
--      CUDA PROFILE: OFF
-- WIN_USE_ASM:
-- x86_64: Open SSE
-- MNN_AVX512:OFF
-- Autodetected CUDA architecture(s):  6.1 6.1 6.1 6.1 6.1 6.1 6.1 6.1
-- Enabling CUDA support (version: 11.1, archs: sm_61)
-- message  -D_FORCE_INLINES -Wno-deprecated-gpu-targets -w  -O3 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_72,code=sm_72 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 !!!!!!!!!!! /usr/local/cuda-11.1/include
-- Onnx:
-- Configuring done
-- Generating done
-- Build files have been written to: /disk4/wangxu/MNN/build
Scanning dependencies of target MNNAVX
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[  2%] Built target MNNCV
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[  2%] Built target MNNUtils
[  2%] Building CXX object CMakeFiles/MNNTransform.dir/source/geometry/GeometryBroadcastTo.cpp.o

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/disk4/wangxu/MNN/tools/converter/source/onnx/onnxOpConverter.cpp: In static member function ‘static MNN::BlobT* onnxOpConverter::convertTensorToBlob(const onnx::TensorProto*, const string&)’:
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# 编译日志:
# Build Log:

model.zip

粘贴在这里
Paste log here or pastebin

对应的ModuleBaisc.out分别执行cuda推理和cpu推理的执行结果如下：

1）cuda推理结果，输出为全0
./ModuleBasic.out  model.mnn onnx 0 2 1 1 2
Test model.mnn from input info: onnx
onnx_input
output: onnx_output
Use extra forward type: 2
precision=2 in main, 178
cacheFileName=s .tempcache in main, 179
The device support dot:0, support fp16:0, support i8mm: 0
Load Cache file error.
main, 213, cost time: 75.061005 ms
Run for 0 time
before compare onnx_output: (1, 160000, )
TESTERROR onnx_output value error : absMaxV:0.033646 - DiffMax 0.033646
0 run Error for output onnx_output
Write onnx_output output to output/0_0.txt
memoryInMB=f 208.052795 in main, 332
Avg= 11.334001 ms, min= 11.334001 ms, max= 11.334001 ms
(audio_torch) root@cs102:/disk4/MNN/build# vim output/0_0.txt

2）cpu推理，推理结果正常
(audio_torch) root@cs102:/disk4/MNN/build# ./ModuleBasic.out model.mnn onnx 0 0 1 1 2
Test model.mnn from input info: onnx
onnx_input
output: onnx_output
Use extra forward type: 0
precision=2 in main, 178
cacheFileName=s .tempcache in main, 179
The device support dot:0, support fp16:0, support i8mm: 0
Load Cache file error.
main, 213, cost time: 99.201004 ms
Run for 0 time
before compare onnx_output: (1, 160000, )
Write onnx_output output to output/0_0.txt
memoryInMB=f 385.236145 in main, 332
Avg= 3502.545166 ms, min= 3502.545166 ms, max= 3502.545166 ms

[MaybeShewill-CV]

@bigsealing cuda后端的话 可以试试设置precision_mode为normal 看看能不能解决你的问题：）

[github-actions]

Marking as stale. No activity in 60 days.