![]() ![]() Check for conda initialization and active environment.Display information about the current conda installation.Search for public (unofficial) packages.List packages installed in the active environment.Install packages with version requirements.Install the package named "package1" in the active environment.Search for packages with "pack" in their name.Listing, adding and removing environment variables in an environment.Create the environment "my_env" in the specified location.Recreate a previously exported environment.Export the environment "my_env" to the definition file "my_env.yml" for a different platform.Export the environment "my_env" to the definition file "my_env.yml" for an identical platform.Create a cloned environment named "cloned_env" from "original_env".Activate the environment called "my_env".Create an environment called "my_env" with packages "package1" and "package2" installed.tensorflow and CUDA toolkit 11 to run on GPU nodes.tensorflow and CUDA toolkit 10 for a managed client.pytorch and CUDA toolkit 11 to run on GPU nodes.pytorch and CUDA toolkit 10 for a managed client.Creating pytorch/tensorflow environments.Creating an environment with a specific python version.Setting up a personal python development infrastructure.Merged, the recipe will be re-built and uploaded automatically to theĬonda-forge channel, whereupon the built conda packages will be available forĮverybody to install and use from the conda-forge channel. Opportunity to confirm that the changes result in a successful build. Your changes will be run on the appropriate platforms to give the reviewer an Package version, please fork this repository and submit a PR. If you would like to improve the cudatoolkit recipe or build a new Produce the finished article (built conda distributions) Updating cudatoolkit-feedstock yml filesĪnd simplify the management of many feedstocks.Ĭonda-forge - the place where the feedstock and smithy live and work to Its primary use is in the construction of the CI. Terminologyįeedstock - the conda recipe (raw material), supporting scripts and CI configuration.Ĭonda-smithy - the tool which helps orchestrate the feedstock. the CI configuration files) with conda smithy rerender.įor more information please check the conda-forge documentation. Using the conda-forge.yml within this repository, it is possible to re-render all of ![]() To manage the continuous integration and simplify feedstock maintenance It is possible to build and upload installable packages to theĬhannel for Linux, Windows and OSX respectively. Thanks to the awesome service provided by The package) and the necessary configurations for automatic building using freelyĪvailable continuous integration services. Such a repository is known as a feedstock.Ī feedstock is made up of a conda recipe (the instructions on what and how to build The conda-forge organization contains one repositoryįor each of the installable packages. In order to provide high-quality builds, the process has been automated into theĬonda-forge GitHub organization. Mamba repoquery depends cudatoolkit -channel conda-forgeĬonda-forge is a community-led conda channel of installable packages. Mamba repoquery whoneeds cudatoolkit -channel conda-forge # List packages depending on `cudatoolkit`: ![]() Mamba repoquery search cudatoolkit -channel conda-forge # Search all versions available on your platform: Installing cudatoolkit from the conda-forge channel can be achieved by adding conda-forge to your channels with: By downloading and using the packages, you accept the terms and conditions of the CUDA EULA - Current build status Azure The packages are governed by the CUDA Toolkit End User License Agreement (EULA). For the full CUDA Toolkit with a compiler and development tools visit This CUDA Toolkit includes GPU-accelerated libraries, and the CUDA runtime for the Conda ecosystem. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. With CUDA, developers can dramatically speed up computing applications by harnessing the power of GPUs. Summary: CUDA Toolkit - Including CUDA runtimeĬUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). Package license: LicenseRef-NVIDIA-End-User-License-Agreement
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