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How to use _install_cudnn method in lisa

Best Python code snippet using lisa_python

gpusuite.py

Source:gpusuite.py

...131        ),132    )133    def verify_gpu_cuda_with_pytorch(self, node: Node) -> None:134        _check_driver_installed(node)135        _install_cudnn(node)136        gpu = node.features[Gpu]137        pip = node.tools[Pip]138        if not pip.exists_package("torch"):139            pip.install_packages("torch")140        gpu_script = "import torch;print(f'gpu count: {torch.cuda.device_count()}')"141        python = node.tools[Python]142        expected_count = gpu.get_gpu_count_with_lspci()143        script_result = python.run(144            f'-c "{gpu_script}"',145            force_run=True,146        )147        gpu_count_str = get_matched_str(script_result.stdout, self._pytorch_pattern)148        script_result.assert_exit_code(149            message=f"failed on run gpu script: {gpu_script}, "150            f"output: {script_result.stdout}"151        )152        assert_that(gpu_count_str).described_as(153            f"gpu count is not in result: {script_result.stdout}"154        ).is_not_empty()155        gpu_count = int(gpu_count_str)156        assert_that(gpu_count).described_as(157            "GPU must be greater than zero."158        ).is_greater_than(0)159        assert_that(gpu_count).described_as(160            "cannot detect GPU from PyTorch"161        ).is_equal_to(expected_count)162def _check_driver_installed(node: Node) -> None:163    gpu = node.features[Gpu]164    if not gpu.is_supported():165        raise SkippedException(f"GPU is not supported with distro {node.os.name}")166    if ComputeSDK.AMD in gpu.get_supported_driver():167        raise SkippedException("AMD vm sizes is not supported")168    try:169        _ = node.tools[NvidiaSmi]170    except Exception as identifier:171        raise LisaException(172            f"Cannot find nvidia-smi, make sure the driver installed correctly. "173            f"Inner exception: {identifier}"174        )175def _install_cudnn(node: Node) -> None:176    wget = node.tools[Wget]177    tar = node.tools[Tar]178    path = wget.get_tool_path(use_global=True)179    extracted_path = tar.get_tool_path(use_global=True)180    if node.shell.exists(path / _cudnn_file_name):181        return182    download_path = wget.get(183        url=_cudnn_location, filename=str(_cudnn_file_name), file_path=str(path)184    )185    tar.extract(download_path, dest_dir=str(extracted_path))186    if isinstance(node.os, Debian):187        target_path = "/usr/lib/x86_64-linux-gnu/"188    else:189        target_path = "/usr/lib64/"...

fabfile.py

Source:fabfile.py

...39        sudo('apt-get update -yq')40        sudo('apt-get install -yq cuda')41        run('echo "export PATH=/usr/local/cuda/bin:$PATH" >> ~/.bash_profile')42        fabric.operations.reboot()43def _install_cudnn(ver, cudnn):44    url = 'http://developer.download.nvidia.com/compute/redist/cudnn/%s/%s' % (ver, cudnn)45    run('wget -q %s' % url)46    sudo('tar -xzf %s -C /usr/local' % cudnn)47    run('rm %s' % cudnn)48    sudo('ldconfig')49def install_cudnn5():50    _install_cudnn('v5.1', 'cudnn-8.0-linux-x64-v5.1.tgz')51def install_cudnn4():52    _install_cudnn('v4', 'cudnn-7.0-linux-x64-v4.0-prod.tgz')53def install_cudnn3():54    _install_cudnn('v3', 'cudnn-7.0-linux-x64-v3.0-prod.tgz')55def install_cudnn2():56    _install_cudnn('v2', 'cudnn-6.5-linux-x64-v2.tgz')57def install_chainer_env():58    sudo('apt-get install -yq g++ libhdf5-dev python3-dev python3-pip')59    sudo('pip3 install -U setuptools pip')60    sudo('pip3 install h5py')61    sudo('pip3 install numpy')62def install_chainer():63    apt_update()64    install_nvidia()65    install_cuda80_deb()66    install_cudnn5()67    install_chainer_env()68    sudo('pip3 install chainer')69    # On ubuntu16.04, lightdb runs out of cpu.70    sudo('systemctl disable lightdm')...

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