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[BUG] Exception: Your CUDA environment is invalid.

See original GitHub issue

Recently I got this error while trying to install cupy on a Kaggle GPU Kernel:

Collecting cupy
  Downloading cupy-7.4.0.tar.gz (3.7 MB)
     |████████████████████████████████| 3.7 MB 3.4 MB/s eta 0:00:01
    ERROR: Command errored out with exit status 1:
     command: /opt/conda/bin/python3.7 -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-jzxcfeco/cupy/setup.py'"'"'; __file__='"'"'/tmp/pip-install-jzxcfeco/cupy/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /tmp/pip-install-jzxcfeco/cupy/pip-egg-info
         cwd: /tmp/pip-install-jzxcfeco/cupy/
    Complete output (48 lines):
    Options: {'package_name': 'cupy', 'long_description': None, 'wheel_libs': [], 'wheel_includes': [], 'no_rpath': False, 'profile': False, 'linetrace': False, 'annotate': False, 'no_cuda': False, 'use_hip': False}
    
    -------- Configuring Module: cuda --------
    cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
    cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
    /opt/conda/compiler_compat/ld: /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/libcuda.so: file not recognized: file truncated
    collect2: error: ld returned 1 exit status
    Cannot build a stub file.
    Original error: command 'g++' failed with exit status 1
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/tmp/pip-install-jzxcfeco/cupy/setup.py", line 129, in <module>
        ext_modules = cupy_setup_build.get_ext_modules()
      File "/tmp/pip-install-jzxcfeco/cupy/cupy_setup_build.py", line 744, in get_ext_modules
        extensions = make_extensions(arg_options, compiler, use_cython)
      File "/tmp/pip-install-jzxcfeco/cupy/cupy_setup_build.py", line 492, in make_extensions
        raise Exception('Your CUDA environment is invalid. '
    Exception: Your CUDA environment is invalid. Please check above error log.
    
    ************************************************************
    * CuPy Configuration Summary                               *
    ************************************************************
    
    Build Environment:
      Include directories: ['/usr/local/cuda/include']
      Library directories: ['/usr/local/cuda/lib64']
      nvcc command       : ['/usr/local/cuda/bin/nvcc']
    
    Environment Variables:
      CFLAGS          : (none)
      LDFLAGS         : (none)
      LIBRARY_PATH    : (none)
      CUDA_PATH       : (none)
      NVTOOLSEXT_PATH : (none)
      NVCC            : (none)
      ROCM_HOME       : (none)
    
    Modules:
      cuda      : No
        -> Cannot link libraries: ['cublas', 'cuda', 'cudart', 'cufft', 'curand', 'cusparse', 'nvrtc']
        -> Check your LDFLAGS environment variable.
    
    ERROR: CUDA could not be found on your system.
    Please refer to the Installation Guide for details:
    https://docs-cupy.chainer.org/en/stable/install.html
    
    ************************************************************
    
    ----------------------------------------
ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.

Issue Analytics

  • State:closed
  • Created 3 years ago
  • Comments:21 (12 by maintainers)

github_iconTop GitHub Comments

1reaction
rosbocommented, Apr 30, 2020

About pre-installing Rapids packages, I tried in December 2019 but hit that issue: https://github.com/Kaggle/docker-python/issues/594#issuecomment-563498314

Let me check whether this dependency conflict issue has been fixed.

1reaction
aerdem4commented, Apr 30, 2020

Btw now there are many people using Rapids on Kaggle relying on our manually uploaded installation dataset: https://www.kaggle.com/cdeotte/rapids/kernels?sortBy=voteCount&group=everyone&pageSize=20&datasetId=492658 It would be really nice if it can be preinstalled on Kaggle’s GPU Docker Image. https://rapids.ai/start.html

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