Deleted docker_v2/fidle_env_test.py, docker_v2/fidle_python_pip.dockerfile,...

Deleted docker_v2/fidle_env_test.py, docker_v2/fidle_python_pip.dockerfile, docker_v2/jupyter_lab_config.py, docker_v2/notebook.json, docker_v2/requirements-cpu.txt, docker_v2/requirements.txt

docker_v2/fidle_env_test.py

-#!/usr/bin/env python3
-## Some tests to check fidle installation is ok
-##
-
-import tensorflow as tf
-import torch
-import sys, os
-
-# Check data set is found
-datasets_dir = os.getenv('FIDLE_DATASETS_DIR', False)
-if datasets_dir is False:
-   print("FIDLE_DATASETS_DIR not found - Should be /data/fidle_datasets/")
-   sys.exit(1) 
-print("FIDLE_DATASETS_DIR = ", os.path.expanduser(datasets_dir))
-
-# Check Python version
-print("Python version = {}.{}".format(sys.version_info[0], sys.version_info[1]))
-# Check tensorflow version
-print("Tensorflow version = ", tf.__version__)
-# Obsolete command
-#print("Tensorflow GPU/CUDA available = ", tf.test.is_gpu_available())
-print("Tensorflow GPU/CUDA available = ", "true" if len(tf.config.list_physical_devices('GPU')) else "False")
-
-# Chech Pytorch version
-print("Pytorch version = ", torch.__version__)
-print("Pytorch GPU/CUDA available = ", torch.cuda.is_available())
-
-sys.exit(0)

docker_v2/fidle_python_pip.dockerfile

-#
-#
-ARG PYTHON_VERSION=3.7
-ARG docker_image_base=python:${PYTHON_VERSION}-slim
-FROM ${docker_image_base}
-
-LABEL maintainer=soraya.arias@inria.fr
-
-# Ensure a sane environment
-ENV TZ=Europe/Paris LANG=C.UTF-8 LC_ALL=C.UTF-8 DEBIAN_FRONTEND=noninteractive
-
-RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone && \
-    apt update --fix-missing && \
-    apt install -y --no-install-recommends apt-utils &&\
-    apt install -y wget curl git \
-        python3-venv python3-pip && \
-    apt -y dist-upgrade && \
-    curl -fsSL https://deb.nodesource.com/setup_lts.x |  bash - && \
-    apt install -y nodejs && \
-    apt clean && \
-    rm -fr /var/lib/apt/lists/*
-
-# Get Python requirement packages list
-COPY requirements-cpu.txt /root/requirements.txt
-
-# Add & Update Python tools and install requirements packages
-RUN python -m pip install --upgrade pip && \
-    pip install --no-cache-dir -I --upgrade setuptools && \
-    pip install --no-cache-dir -r /root/requirements.txt 
-
-# Get Fidle datasets
-# - datasets
-RUN mkdir /data && \
-    fid  install_datasets --quiet --install_dir /data
-# - notebooks
-RUN mkdir /notebooks/ && \
-    fid install_notebooks --quiet --install_dir /notebooks
-
-# Add Jupyter configuration (no browser, listen all interfaces, ...)
-COPY jupyter_lab_config.py /root/.jupyter/jupyter_lab_config.py
-COPY notebook.json /root/.jupyter/nbconfig/notebook.json
-
-# Jupyter notebook uses 8888 
-EXPOSE 8888
-# Tensor board uses 6006
-EXPOSE 6006
-
-VOLUME /notebooks
-WORKDIR /notebooks
-
-# Set a folder in the volume as Python Path
-ENV PYTHONPATH=/notebooks/fidle-master/:$PYTHONPATH
-
-# Force bash as the default shell (useful in the notebooks)
-ENV SHELL=/bin/bash
-
-# Set Fidle dataset directory variable
-ENV FIDLE_DATASETS_DIR=/data/datasets-fidle
-
-# Run a notebook by default
-CMD ["jupyter", "lab"]

docker_v2/notebook.json

-{
-  "load_extensions": {
-    "execute_time/ExecuteTime": true,
-    "tree-filter/index": true
-  }
-}

docker_v2/requirements-cpu.txt

-# ----------------------------------------------------
-#    ______ _     _ _       __      __             
-#   |  ____(_)   | | |      \ \    / /             
-#   | |__   _  __| | | ___   \ \  / /__ _ ____   __
-#   |  __| | |/ _` | |/ _ \   \ \/ / _ \ '_ \ \ / /
-#   | |    | | (_| | |  __/    \  /  __/ | | \ V / 
-#   |_|    |_|\__,_|_|\___|     \/ \___|_| |_|\_/  
-#                               Fidle pip virtual env
-# ----------------------------------------------------
-#
-# To install your Fidle env, see https://fidle.cnrs.fr/installation
-
-tensorflow_cpu>=2.7,<=2.9
-scikit-image
-scikit-learn
-matplotlib
-plotly
-barviz
-fidle
-jupyterlab
--f https://download.pytorch.org/whl/cpu
-torch
-torchvision 

docker_v2/requirements.txt

-tensorflow_cpu
-Scikit-image
-Scikit-learn
-Matplotlib
-Pandas
-Pandoc
-pyyaml
-torch
-torchvision
-torchaudio
-Jupyterlab