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**- Prerequisites -**
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* All notebooks can run on CPU or GPU
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* The software environment (conda) requires about 10G
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* Original datasets require about 2.5G
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* Consolidated datasets may require up to 150G depending on the tests you perform... \
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Anyway, 15GB will probably be a minimum...
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* All notebooks can run on a **classic CPU**, having a GPU can be nice, but is not essential.
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* Original datasets require about 2.5G, but Consolidated datasets may require up to 150G depending on the tests you perform. **15GB** will probably be a minimum...
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**- Important : -**
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You can install the Fidle environment via **Docker** or in a classic way. If you know how to use a Docker container, this is the best solution !
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**- Contents -**
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[[_TOC_]]
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[<img width="350px" src="uploads/31d5ce29e91c44d33930aed9ef465559/InstallationFIDLE.png"></img>](https://www.youtube.com/watch?v=pw8x3D5IaQY&t=5s)
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A small video presentation of the installation under Windows...
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But everything is **precisely described below** ! ;-)
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## 1 - Get Fidle repository of notebooks
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## Step 0 - Create a main repository
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The very first step will be to create a folder in which we will then install all the elements of Fidle, for example : `fidle-tp`
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The next 3 steps will take place within this folder.
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## Step 1 - Get Fidle repository of notebooks
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The simplest and most conventional way is with **git** (200 MB):
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| ... | ... | @@ -30,7 +35,7 @@ However, a **[classic retrieval](https://fidle.cnrs.fr/notebooks)** (zip) is pos |
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**Important :** The project is frequently updated and we encourage you to get the latest version.\
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The version number is specified in the README of the repository.
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## 2 - Get and install Datasets
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## Step 2 - Get and install Datasets
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**Get it**\
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The datasets used in the examples are **[available here ](https://fidle.cnrs.fr/fidle-datasets.tar)**.\
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tar -xf fidle-datasets.tar
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```
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**Specify the location**\
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You must then indicate the location of this folder with an environment variable.
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* For computers under Linux, add the following line to your `.bashrc`, or \`.bash_profile, ...
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```shell
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export FIDLE_DATASETS_DIR=<the place of your datasets directory>
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```
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* For computers under Windows (and using a terminal that is NOT a powershell!)
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```shell
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set FIDLE_DATASETS_DIR=<the place of your datasets directory>
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```
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A complete description of the different datasets is available in Notebooks.
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## 3 - Setup Python Environment
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### Linux users
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It is possible to install **conda** or **pip** :
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**[Linux installation procedure, using conda](Using Fidle/Linux installation using conda)**
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**[Linux installation procedure, using pip](Using-Fidle/Linux installation with pip)**
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## Step 3 - Setup Python Environment
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### Windows users
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Choose the right procedure :
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**[Windows installation procedure, using pip](/Using Fidle/Windows installation)**
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- [Linux installation](/Using-Fidle/Linux installation with pip)
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- [Windows installation](/Using Fidle/Windows installation)
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- [Manual installation (MacOs ?)](/Using Fidle/Manual installation)
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### Manual or MacOS installation
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If you have difficulties or if you are under MacOS...
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**[Try this this manual installation procedure](/Using Fidle/Manual installation)**
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**NOTE:**
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- If you are lucky enough to have an account at **IDRIS** or at your favorite **meso center**, pre-installed environments are already available !
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- To avoid infos and warning messages from tensorflow, you can set an additional environment variable `TF_CPP_MIN_LOG_LEVEL` whose possible values are 0, 1, 2 or 3.\
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(0: all msg, 1:hide infos, 2:hide infos+warnings, 3:hide info, warnings and errors)
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That's all folks !!
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## Annexe 2 - Test installations
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### Check Tensorflow / Keras
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If you want to check your **tensorflow installation** (and check if it supports gpu), launch a python interpreter and use these instructions :
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If you want to **check your tensorflow installation** (and check if it supports gpu), launch a python interpreter and use these instructions :
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```python
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import tensorflow as tf
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print(tf.config.list_physical_devices('GPU'))
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```
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## Annexe 3 - Uninstall
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Great, now you can **[run Jupyter Lab !](Using-Fidle/Running-Jupyter)**
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To delete data and notebooks:
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- delete the folder containing the datasets (probably `fidle-datasets`)
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- delete the folder containing the notebooks (probably `fidle` ou `fidle-master`)
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For **conda installed version (Linux)** use the following command :
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```
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conda deactivate
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conda env remove --name fidle
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```
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## Annexe 1 : Hide warning messages
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For **pip installed version (Windows)** use the following command :
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```
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deactivate
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```
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And remove the virtual env directory
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- To avoid infos and warning messages from tensorflow, you can set an additional environment variable `TF_CPP_MIN_LOG_LEVEL` whose possible values are 0, 1, 2 or 3.\
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(0: all msg, 1:hide infos, 2:hide infos+warnings, 3:hide info, warnings and errors)
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...and think to remove your FIDLE_DATASET_DIR variable setting !
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## Annexe 2 - Uninstall
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To remove and delete all Fidle stuff :
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- delete the folder containing the datasets (probably `fidle-datasets`)
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- delete the folder containing the notebooks (probably `fidle` ou `fidle-master`)
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- close terminals and remove python virtual env directory (probably `file-env`)
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...and think to remove your FIDLE_DATASET_DIR variable setting !
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L'ancienne procédure est [accessible ici :-)](Using-Fidle/install%20fidle%20v1)
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\ No newline at end of file |
