Step-by-Step Guide for Running Python Code in an svr Folder

1. Log in to the JADE System

Open a terminal on your local machine and connect to the JADE HPC system using SSH:

ssh your_username@jade_hpc_address

2. Load the Anaconda Module

Once logged in, load the Anaconda module to use conda for managing Python environments:

module load python/anaconda3
source $condaDotFile

3. Create a Conda Environment

Create a new conda environment with the required Python version. For example, if you need Python 3.8:

conda create -n <conda_env_name> python=3.8

Activate the newly created environment:

source activate <conda_env_name>

<aside> <img src="/icons/info-alternate_yellow.svg" alt="/icons/info-alternate_yellow.svg" width="40px" /> ml_dev_env - PhD ML project environment

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4. Install Python Packages

Install the necessary Python packages. For example, if you need numpy, pandas, scikit-learn, and tensorflow:

conda install numpy pandas scikit-learn
conda install -c conda-forge tensorflow

If a package is not available via conda, use pip:

pip install <some_package>

5. Prepare Your Submission Script

Create a submission script (submit_devel.sh) for your job. This script will load the Anaconda module, activate the environment, navigate to the svr folder, and run your Python code.