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Source channel @githubtrending · Post #14985 · Jul 22

#c_lang#cuda#cuda_driver_api#cuda_kernels#cuda_opengl You can use the CUDA Samples from NVIDIA to learn and test CUDA Toolkit 12.9 features by downloading them from GitHub or as a ZIP file. These samples show how to use CUDA for GPU programming, including utilities, concepts, libraries, and performance optimization. You build them with CMake on Linux, Windows, or Tegra devices, and can run tests automatically with a provided Python script. This helps you understand CUDA programming, debug GPU code, and optimize your applications for better performance on NVIDIA GPUs. It’s a practical way to develop and improve GPU-accelerated software efficiently. https://github.com/NVIDIA/cuda-samples

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djangoproject

@djangoproject · Post #595 · 04/17/2018, 03:51 PM

https://github.com/pypa/virtualenv/issues/1059 Earlier today I installed python3.6 on my debian machine. Python3.6 was made available in buster distribution. When I try to create a virtualenv with python3.6. python3.6 -m venv venv gives the following error. The #virtual_environment was not created successfully because ensurepip is not available. On Debian/Ubuntu systems, you need to install the python3-venv package using the following command. apt-get install python3-venv You may need to use sudo with that command. After installing the python3-venv package, recreate your virtual environment. Failing command: ['/home/float/test/t/bin/python3.6', '-Im', 'ensurepip', '--upgrade', '--default-pip'] I do have python3-venv (3.5.3-1) installed. Why do I get this error? If I run the command py3 -Im ensurepip —upgrade —default-pip it says /usr/bin/python3.6: No module named ensurepip I don't have trouble creating virtualenvs using the default python3 version (3.5.3). Also , I noticed that I can create a virtualenv as follows: #virtualenv -p python3.6 #venv

djangoproject

@djangoproject · Post #535 · 12/28/2017, 10:12 AM

https://docs.pipenv.org/ #Pipenv — the officially recommended #Python#packaging tool from Python.org, free (as in freedom). Pipenv is a tool that aims to bring the best of all packaging worlds (#bundler, #composer, #npm, #cargo, #yarn, etc.) to the Python world. #Windows is a first–class citizen, in our world. It automatically creates and manages a #virtualenv for your projects, as well as adds/removes #packages from your #Pipfile as you install/uninstall packages. It also generates the ever–important Pipfile.lock, which is used to produce deterministic builds.