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faq.md

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Frequently Asked Questions

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:

    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, the issue may be caused by NVidia and will fix in CUDA release 11.7. For now one could use the fixNvPe.py 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:

    import torch
print(torch.__file__)

Pip

  • pip installed package but could not import them.

    Make sure your are using conda pip.

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