About this installation
- This installation procedure is based on the officia PyTorch procedure,
which are described here : https://pytorch.org/ - If you have a GPU card, things can be more complicated than this simplified procedure.
We advise you to consult the documentation mentioned above. - All commands presented below and prefixed by
$are to be launched on a terminal/unix console. (fidle-env) $is the fidle-env python prompt- Size a full installation (environment, data, notebooks) is around 4GB
Content
Installation
1 - First of all, you need Python !
A recent version of python is required.
This procedure has been tested and validated under Debian 12 (Bookworm) / Python 3.11
For example, if you are root (administrator in your Linux system) under Debian :
sudo apt-get install python3 python3-dev python3-pip python3-venv
2 - A folder to contain them all
The idea is to put everything in the same folder, for example fidle-tp
$ mkdir ~/fidle-tp
$ cd ~/fidle-tp
3 - A python environment, just for us !
The idea is to create a virtual python environment, in order not to “pollute” your system.
This virtual environment will be contained in a sub folder (fidle-env).
FIRST, we create a virtual environment “fidle-env” and activate it:
$ python3 -m venv fidle-env
$ source ./fidle-env/bin/activate
We can now install all the necessary modules in our python environment.
SECOND, we have to install PyTorch, according PyTorch documentation : https://pytorch.org/get-started/locally/
Example: on Linux for cpu :
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
THIRD, we will now install the rest of the modules:-)
(fidle-env) $ pip install torch-geometric torchtext torchdata lightning \
tensorboard keras transformers datasets einops numpy Scikit-image Scikit-learn \
Matplotlib plotly seaborn barviz pyarrow Pandas Pandoc \
pyyaml Jupyterlab fidle
It will take a little while, but should go very well :-)
4 - Install notebooks et datasets
Now all that remains is to install the notebooks and datasets :-)
Nous allons faire cela avec la commande fid de Fidle.
Still from our folder fidle-tp
(fidle-env) $ fid install --quiet
You should have something like :
(version numbers may vary)
==========================================================
fid - Your favorite Fidle admin command :-) (v2.3.0)
==========================================================
Install Fidle notebooks in . :
Install ressource : fidle-master
In directory : .
Extract : [########################################] 100.0% of 113 files
Installed in : ./fidle-master-3.0.5
Done.
Install Fidle datasets in . :
Install ressource : datasets-fidle
In directory : .
Download : [########################################] 100.0% of 528.8 Mo
Extract : [########################################] 100.0% of 51963 files
Installed in : ./datasets-fidle
Done.
5 - Installation check
The tree structure is normally as follows:
fidle-tp
├── fidle-master-3.0.5 Contains notebooks
├── fidle-datasets Contains datasets
└── fidle-env Virtual environment
From a terminal, go to your fidle-tp folder,
activate the fidle-env environment and do a fid check.
$ cd (...)/fidle-tp
$ source ./fidle-env/bin/activate
(fidle-env) $ fid check
You should have something like :
(version numbers may vary)
==========================================================
fid - Your favorite Fidle admin command :-) (v2.3.0)
==========================================================
Notebooks and datasets can only be found if they are in/near the explored folder.
Explored directory is : /home/dupont/fidle-tp
Datasets dir found :
/home/dupont/fidle-tp/datasets-fidle (Datasets Fidle / 2.0)
The environment variable FIDLE_DATASETS_DIR is : undefined
Notebooks dir found :
/home/dupont/fidle-tp/fidle-master-3.0.5 (Notebooks Fidle / 3.0.5)
Check environment :
Python : Ok (3.9.2)
Fidle module : Ok (2.3.0)
keras : Ok (3.0.4)
numpy : Ok (1.24.1)
sklearn : Ok (1.4.0)
yaml : Ok (6.0.1)
skimage : Ok (0.22.0)
matplotlib : Ok (3.8.2)
plotly : Ok (5.18.0)
pandas : Ok (2.2.0)
jupyterlab : Ok (4.0.11)
torch : Ok (2.1.2+cpu)
torchvision : Ok (0.16.2+cpu)
lightning : Ok (2.1.3)
6 - Start Jupyter lab
Very easy :-)
From a terminal, go to your fidle-tp folder,
activate the fidle-env environment and do a jupyter lab.
$ cd (...)/fidle-tp
$ source ./fidle-env/bin/activate
(fidle-env) $ jupyter lab
7 - Reinstall and updates
- You can reinstall notebooks or datasets with the
fid install_notebooksandfid install_datasetscommands - You can also locate the datasets fidle folder anywhere you want.
In this case, you must specify the location of this folder with the environment variableFIDLE_DATASETS_DIR
