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Linux installation with pip

Last edited by Jean-Luc Parouty





- Notes -

  • 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

- Contents -

Back to the install procedure

1 - First of all, you need Python !

A version of python 3.6 to 3.9 is required.

Note :

  • Do not download the latest version 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 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

Note:

  • You can reinstall notebooks or datasets with the fid install_notebooks and fid install_datasets commands
  • 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 variable FIDLE_DATASETS_DIR

Back to the install procedure

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