PaulEmmanuelSotir

#!/bin/bash

# Begining of custom MOTD
#echo -e "\e[32m\e[1m###################################> ☣❤ \e[33m\e[1mPES SHELL\e[39m\e[0m - INTRUDERS BE CAREFULL\e[32m\e[1m ❤☣ <###################################\e[39m\e[0m"
                                     
echo -e "\e[33m\e[1m################################><><><><><><><><><><><><><><><><><><><><><><><><################################\e[39m\e[0m"
echo -e "\e[32m                                       ___  ________  ______ ________   __ "
echo -e       "                                      / _ \/ __/ __/ / __/ // / __/ /  / / "
echo -e       "                                     / ___/ _/_\ \  _\ \/ _  / _// /__/ /__"
echo -e       "                                    /_/  /___/___/ /___/_//_/___/____/____/\e[39m\e[1m ☣❤(INTRUDERS BE CAREFULL)☣❤"

PaulEmmanuelSotir

import re
import logging

import git
import mlflow
import configparser

def mlflow_log_repo_tags(default_project_name: str, entry_point: str = __file__, path_in_repository: str = __file__):
    """ This code creates special mlflow tags about current repository infos, which is not done by mlflow when starting an MLFlow run from code instead of from `mlflow run` command

PaulEmmanuelSotir

A non-exhaustive Deep Learning techniques mind-map (december 2019)

Released under open-source MIT License.
By Pau-Emanuel SOTIR paul-emanuel@outlook.com

Neural network architectures

• Fully connected networks = Dense neural networks (FC DNN) (Warning, could be confused with FCN: Fully Convolutional Networks or with some residual networks (e.g. "Densely Connected Networks" (DenseNet), which are only dense in terms of residual links between layer blocks))
• CNN: Convolutionnal Neural Networks (Mainly brougth by Yahn LeCun)
• a-trou-convolutions = upconv = upsampling convolutions = dilated convolutions (popularized by DeepLab)

PaulEmmanuelSotir

/*********************************************************************************
					Typed_main_binding  - An helper class for main args
					---------------------------------------------------
Under MIT License,
Copyright (c) 2015 Paul-Emmanuel SOTIR
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files 
(the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, 
publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do 
so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.