/deeplearning4astro_labs_2019

Exercises and deep learning challenge for the 2019 edition of the deeplearning4astro course

Primary LanguageJupyter NotebookBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Tutorial Sessions - Intelligence artificielle pour l'astrophysique à l'époque du big-data - ED127

Authors: Alexandre Boucaud & Marc Huertas-Company

These pages contain all the required information to run the tutorials of the course. Please follow the instructions below to set up ypur environment.

Set up your environment

  1. clone this repository
git clone https://github.com/aboucaud/deeplearning4astro_labs_2019.git
cd deeplearning4astro_labs_2019
  1. install the dependencies
  • with conda This option is highly recommended to ensure that the installation will not interfere with your current python installation
conda install -y -c conda conda-env     # First install conda-env
conda env create                        # Use environment.yml to create the 'dl4astro19' env
conda activate dl4astro19       # Activates the virtual env
  • without conda (best to use a virtual environment)
python -m pip install -r requirements.txt
  1. Only if your system has an Nvidia GPU (not for Mac)

  • check if the nvidia drivers are installed by typing nvidia-smi in a terminal. If the command is not recognized, download and install from here [https://www.nvidia.com/Download/index.aspx?lang=en-us]. You will need root access and the model of your GPU.

  • within your virtual environment type:

conda install tensorflow-gpu cudatoolkit=9.0