Python can live in many different places on your computer, and each source may have different packages already installed.īy using an anaconda environment that we create, and by explicitly using only that environment, we can avoid conflicts…Īnd know exactly what environment is being used to run our python code. These packages are:Ī note about anaconda XKCD #1987: Python Environment To avoid these conflicts, we will create a new environment with only the packages we need for this workshop. This workshop utilizes some Python packages (such as Plotly) that cannot be installed in Anaconda’s base environment, because they will cause conflicts. See an example for the environments.Create a new environment from an environment.yml fileĪdd this environment to Jupyter’s kernel list To persist a conda virtual environment, you can define an environments.ymlįor a description of the syntax. Persistence of Conda Virtual Environment ¶ (my-torch-env) conda install -c pytorch torchvisionĬollecting package metadata (current_repodata.json): done Preparing transaction: done Verifying transaction: done (my-torch-env) which python # ensure to use the correct Python (my-torch-env) python -c "import torchvision print(torchvision._version_)" 0.12.0 (my-torch-env) conda deactivate conda create -prefix my-torch-env python = 3.8Ĭollecting package metadata (current_repodata.json): done Solving environment: done Proceed (/n)? y conda activate my-torch-env Use the pip freeze command for srun -nodes = 1 -gres =gpu:1 -time = 01:00:00 -pty ws_allocate my_conda_virtualenv 100 # use a workspace for the environment cd module load Anaconda3 Then you can restore this virtualenv by installing the To persist a virtualenv, you can store the names and versions of installed Persistence of Python Virtual Environment ¶ Installing collected packages: torchvision=0.10.0 Successfully installed torchvision-0.10.0 (my-torch-env) python -c "import torchvision print(torchvision._version_)" 0.10.0+cu102 (my-torch-env) deactivate (my-torch-env) pip install torchvision = 0.10.0 virtualenv -system-site-packages my-torch-envĬreated virtual environment CPython3.8.6.final.0-64 in 42960ms creator CPython3Posix(dest=/my-torch-env, clear=False, global=True) seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=~/.local/share/virtualenv) added seed packages: pip=21.1.3, setuptools=57.2.0, wheel=0.36.2 activators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator source my-torch-env/bin/activate sw/installed/Python/3.8.6-GCCcore-10.2.0/bin/python pip list TheĬonda manager is included in all versions of Anaconda and srun -nodes = 1 -gres =gpu:1 -time = 01:00:00 -pty ws_allocate my_python_virtualenv 100 # use a workspace for the environment cd module load modenv/hiera GCC/10.2.0 CUDA/11.1.1 OpenMPI/4.0.5 PyTorch/1.9.0 Management system and environment management system from Anaconda. Virtual environments on ZIH system and part of the Python modules.Ĭonda is an alternative method for managing installations and It is the preferred interface for managing installations and Virtualenv is a standard Python tool to create isolated PythonĮnvironments. There are two methods of how to work with virtual environments on ZIH systems: Pip freeze, you can see a list of all installed packages and their versions. Required packages with the command: pip install. Modules list or if you didn't find what you need you can install In your virtual environment, you can use packages from the Virtual environments allow users to install additional Python packages andĬreate an isolated run-time environment. GPU-accelerated Containers for Deep Learning (NGC Containers) Persistence of Python Virtual Environment Transfer Data between ZIH Systems and Object Storage (S3) Transfer Data to/from old ZIH Systems via Export Nodes Transfer Data to/from ZIH Systems via Dataport Nodes Transfer Data Inside ZIH Systems with Datamover Connecting via Terminal (Linux, Mac, Windows)
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