mmdeploy/docs/zh_cn/faq.md

# FAQ

### TensorRT

- "WARNING: Half2 support requested on hardware without native FP16 support, performance will be negatively affected."

  Fp16 mode requires a device with full-rate fp16 support.

- "error: parameter check failed at: engine.cpp::setBindingDimensions::1046, condition: profileMinDims.d\[i\] \<= dimensions.d\[i\]"

  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:

  ```python
  backend_config = dict(
    common_config=dict(max_workspace_size=1 << 30),
    model_inputs=[
        dict(
            input_shapes=dict(
                input=dict(
                    min_shape=[1, 3, 320, 320],
                    opt_shape=[1, 3, 800, 1344],
                    max_shape=[1, 3, 1344, 1344])))
    ])
  ```

  The input tensor shape should be limited between `min_shape` and `max_shape`.

- "error: \[TensorRT\] INTERNAL ERROR: Assertion failed: cublasStatus == CUBLAS_STATUS_SUCCESS"

  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.

### Libtorch

- 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.`

  May `export CUDNN_ROOT=/root/path/to/cudnn` to resolve the build error.

### Windows

- 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`

  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.

  `python fixNvPe.py --input=C:\Users\user\AppData\Local\Programs\Python\Python38\lib\site-packages\torch\lib\*.dll`

  You can find your pytorch installation path with:

  ```python
  import torch
  print(torch.__file__)
  ```

- 编译时enable_language(CUDA) 报错

  ```
  -- Selecting Windows SDK version 10.0.19041.0 to target Windows 10.0.19044.
  -- Found CUDA: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.1 (found version "11.1")
  CMake Error at C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:491 (message):
    No CUDA toolset found.
  Call Stack (most recent call first):
    C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:6 (CMAKE_DETERMINE_COMPILER_ID_BUILD)
    C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCompilerId.cmake:59 (__determine_compiler_id_test)
    C:/Software/cmake/cmake-3.23.1-windows-x86_64/share/cmake-3.23/Modules/CMakeDetermineCUDACompiler.cmake:339 (CMAKE_DETERMINE_COMPILER_ID)
    C:/workspace/mmdeploy-0.6.0-windows-amd64-cuda11.1-tensorrt8.2.3.0/sdk/lib/cmake/MMDeploy/MMDeployConfig.cmake:27 (enable_language)
    CMakeLists.txt:5 (find_package)
  ```

  **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

  **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。

### ONNX Runtime

- Windows系统下，转模型可视化时以及SDK推理时遇到
  ```
  onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Failed to load library, error code: 193
  ```
  **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。
  ```
  C:\Windows\SysWOW64\onnxruntime.dll
  C:\Windows\System32\onnxruntime.dll
  ```
  **解决方法：** 以下两个方案任选其一
  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）
  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

### Pip

- pip installed package but could not `import` them.

  Make sure your are using conda pip.

  ```bash
  $ which pip
  # /path/to/.local/bin/pip
  /path/to/miniconda3/lib/python3.9/site-packages/pip
  ```