Prerequisites for running example scripts or Jupyter notebooks without using a SLURM workload manager

Prior to running any scripts or Jupyter notebooks in the directory <root>/examples without using a SLURM workload manager, where <root> is the root of the emicroml repository, a set of Python libraries need to be installed in the Python environment within which any such scripts or Jupyter notebooks are to be executed.

The Python libraries that need to be installed in said Python environment are:

torch
pyprismatic>=2.0
emicroml[examples]

With appropriately chosen command line arguments, the script <root>/default_env_setup_for_slurm_jobs.sh will attempt to create a virtual environment, then activate it, and then install the above Python libraries. If the script is executed on a Digital Alliance of Canada (DRAC) high-performance computing (HPC) server, then the virtual environment is created via virtualenv. Otherwise, the virtual environment is created via conda. For the latter scenario, an anaconda or miniconda distribution must be installed prior to running the script.

The correct form of the command to run the script is:

source <path_to_current_script> <env_name> <install_extras>

where <path_to_current_script> is the absolute or relative path to the script <root>/default_env_setup_for_slurm_jobs.sh; <env_name> is the path to the virtual environment, if the script is being executed on a DRAC HPC server, else it is the name of the conda virtual environment; and <install_extras> is a boolean, i.e. it should either be true or false. If <install_extras> is set to true, then the script will attempt to install within the environment the dependencies required to run all of the examples in the repository, in addition to installing emicroml. Otherwise, the script will attempt to install only emicroml and its dependencies, i.e. not the additional libraries required to run the examples.

If for whatever reason the script <root>/default_env_setup_for_slurm_jobs.sh fails to create and the activate successfully a virtual environment equipped with the Python libraries listed above, then one will need to do so manually according to the constraints imposed by the machine or server on which you intend to run examples. Before installing emicroml[examples], it is recommended that users install torch in the same environment that they intend to install emicroml[examples] according to the instructions given here for their preferred PyTorch installation option. The Python library pyprismatic>=2.0 must also be installed prior to emicroml[examples]. The easiest way to install this additional dependency is within a conda virtual environment, using the following command:

conda install -y pyprismatic=*=gpu* -c conda-forge

if CUDA version >= 11 is available on your machine, otherwise users should run instead the following command:

conda install -y pyprismatic=*=cpu* -c conda-forge