98 lines
5.0 KiB
Markdown
98 lines
5.0 KiB
Markdown
# FAQ
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### TensorRT
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- "WARNING: Half2 support requested on hardware without native FP16 support, performance will be negatively affected."
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Fp16 mode requires a device with full-rate fp16 support.
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- "error: parameter check failed at: engine.cpp::setBindingDimensions::1046, condition: profileMinDims.d\[i\] \<= dimensions.d\[i\]"
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When building an `ICudaEngine` from an `INetworkDefinition` that has dynamically resizable inputs, users need to specify at least one optimization profile. Which can be set in deploy config:
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```python
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 320, 320],
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opt_shape=[1, 3, 800, 1344],
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max_shape=[1, 3, 1344, 1344])))
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])
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```
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The input tensor shape should be limited between `min_shape` and `max_shape`.
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- "error: \[TensorRT\] INTERNAL ERROR: Assertion failed: cublasStatus == CUBLAS_STATUS_SUCCESS"
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TRT 7.2.1 switches to use cuBLASLt (previously it was cuBLAS). cuBLASLt is the defaulted choice for SM version >= 7.0. You may need CUDA-10.2 Patch 1 (Released Aug 26, 2020) to resolve some cuBLASLt issues. Another option is to use the new TacticSource API and disable cuBLASLt tactics if you dont want to upgrade.
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### Libtorch
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- Error: `libtorch/share/cmake/Caffe2/Caffe2Config.cmake:96 (message):Your installed Caffe2 version uses cuDNN but I cannot find the cuDNN libraries. Please set the proper cuDNN prefixes and / or install cuDNN.`
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May `export CUDNN_ROOT=/root/path/to/cudnn` to resolve the build error.
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### Windows
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- Error: similar like this `OSError: [WinError 1455] The paging file is too small for this operation to complete. Error loading "C:\Users\cx\miniconda3\lib\site-packages\torch\lib\cudnn_cnn_infer64_8.dll" or one of its dependencies`
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Solution: according to this [post](https://stackoverflow.com/questions/64837376/how-to-efficiently-run-multiple-pytorch-processes-models-at-once-traceback), the issue may be caused by NVidia and will fix in *CUDA release 11.7*. For now one could use the [fixNvPe.py](https://gist.github.com/cobryan05/7d1fe28dd370e110a372c4d268dcb2e5) script to modify the nvidia dlls in the pytorch lib dir.
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`python fixNvPe.py --input=C:\Users\user\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\lib\*.dll`
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You can find your pytorch installation path with:
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```python
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import torch
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print(torch.__file__)
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```
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- 编译时enable_language(CUDA) 报错
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```
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-- Selecting Windows SDK version 10.0.19041.0 to target Windows 10.0.19044.
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-- Found CUDA: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.1 (found version "11.1")
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CMake Error at C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:491 (message):
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No CUDA toolset found.
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Call Stack (most recent call first):
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C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:6 (CMAKE_DETERMINE_COMPILER_ID_BUILD)
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C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:59 (__determine_compiler_id_test)
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C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCUDACompiler.cmake:339 (CMAKE_DETERMINE_COMPILER_ID)
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C:/workspace/mmdeploy-0.6.0-windows-amd64-cuda11.1-tensorrt8.2.3.0/sdk/lib/cmake/MMDeploy/MMDeployConfig.cmake:27 (enable_language)
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CMakeLists.txt:5 (find_package)
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```
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**原因：** CUDA Toolkit 11.1安装在Visual Studio之前，造成VS的插件没有安装。或者VS的版本过新，使得CUDA Toolkit的安装的时候跳过了VS插件的安装
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**解决方法：** 可以通过手工拷贝插件的方式来解决这个问题。比如将`C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\extras\visual_studio_integration\MSBuildExtensions`中的四个文件拷贝到`C:\Software\Microsoft Visual Studio\2022\Community\Msbuild\Microsoft\VC\v170\BuildCustomizations` 目录下。具体路径根据实际情况进行更改。
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### ONNX Runtime
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- Windows系统下，转模型可视化时以及SDK推理时遇到
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```
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onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Failed to load library, error code: 193
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```
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**原因：** 在较新的windows系统中，系统路径下下有两个`onnxruntime.dll`，且会优先加载，造成冲突。
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```
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C:\Windows\SysWOW64\onnxruntime.dll
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C:\Windows\System32\onnxruntime.dll
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```
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**解决方法：** 以下两个方案任选其一
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1. 将下载的onnxruntime中的lib目录下的dll拷贝到mmdeploy_onnxruntime_ops.dll的同级目录（推荐使用Everything 进行查找）
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2. 将系统路径下的这两个dll改名，使其加载不到，可能涉及到修改文件权限的操作
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### Pip
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- pip installed package but could not `import` them.
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Make sure your are using conda pip.
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```bash
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$ which pip
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# /path/to/.local/bin/pip
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/path/to/miniconda3/lib/python3.9/site-packages/pip
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```
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