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About MLFow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle. It tackles four primary functions:

Tracking experiments to record and compare parameters and results (MLflow Tracking). Packaging ML code in a reusable, reproducible form in order to share with other data scientists or transfer to production (MLflow Projects). Managing and deploying models from a variety of ML libraries to a variety of model serving and inference platforms (MLflow Models). Providing a central model store to collaboratively manage the full lifecycle of an MLflow Model, including model versioning, stage transitions, and annotations (MLflow Model Registry). MLflow is library-agnostic. You can use it with any machine learning library, and in any programming language, since all functions are accessible through a REST API and CLI. For convenience, the project also includes a Python API, R API, and Java API.
(more details... https://mlflow.org/docs/latest/index.html)

Make Python3 default

Python2 and Python3 are already installed on Debian 10, but the default version is Python2. How to check it...

Code Block

language	bash

python --version

That will return Python 2.x.x

Check for Python3

Code Block

language	bash
theme	Confluence

python3 --version

That will return Python 3.x.x

We have to make Python3 as the default version for the distro.
Firstly we have to find the directories for each version...

Code Block

language	bash
theme	Confluence

ls /usr/bin/python* -la

In this example it returns a bunch of directories...

lrwxrwxrwx 1 root root 7 Mar 4 2019 /usr/bin/python -> python2 lrwxrwxrwx 1 root root 9 Mar 4 2019 /usr/bin/python2 -> python2.7 -rwxr-xr-x 1 root root 3604200 Oct 10 2019 /usr/bin/python2.7 lrwxrwxrwx 1 root root 9 Mar 26 2019 /usr/bin/python3 -> python3.7 -rwxr-xr-x 2 root root 4744392 Apr 3 2019 /usr/bin/python3.7 -rwxr-xr-x 2 root root 4744392 Apr 3 2019 /usr/bin/python3.7m -rwxr-xr-x 1 root root 1018 Mar 3 2018 /usr/bin/python3-jsondiff -rwxr-xr-x 1 root root 3661 Mar 3 2018 /usr/bin/python3-jsonpatch -rwxr-xr-x 1 root root 1342 Apr 30 2016 /usr/bin/python3-jsonpointer -rwxr-xr-x 1 root root 398 Sep 7 2018 /usr/bin/python3-jsonschema lrwxrwxrwx 1 root root 10 Mar 26 2019 /usr/bin/python3m -> python3.7m

Of all these paths we need the ones which have only the name and the version of Pythons (2 and 3 version), without any other description.
In the example above the directories are...

/usr/bin/python2.7 # For Python2

/usr/bin/python3.7 # For Python3

Now we must update/create the "Python alternatives list" using the above paths.

Code Block

language	bash

sudo update-alternatives --install /usr/bin/python python /usr/bin/python2.7 1

Code Block

language	bash

sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 2

Finally we can switch between Python versions. Running the following command, a menu will appear in order to choose the Python version that we want as default.

Code Block
sudo update-alternatives --config python

There are 2 choices for the alternative python (providing /usr/bin/python).

Selection Path Priority Status ------------------------------------------------------------ * 0 /usr/bin/python3.7 2 auto mode 1 /usr/bin/python2.7 1 manual mode 2 /usr/bin/python3.7 2 manual mode

Press <enter> to keep the current choice[*], or type selection number: 2

Choosing the selection 2 then Python3 will become the default version.
We could check if Python3 has applied as default, running...

Code Block

language	bash

python --version

In my case it returns Python 3.7.3

Download and install Miniforge3

Miniforge is the community (conda-forge) driven minimalistic conda installer. Subsequent package installations come thus from conda-forge channel, and it started because miniconda didn't support aarch64,

But first check if there is the Download directory on your distro. If there is none, then create one...

Code Block

language	bash

mkdir ~/Download
cd ~/Download
sudo wget https://github.com/conda-forge/miniforge/releases/download/4.8.3-4/Miniforge3-Linux-aarch64.sh 
bash Miniforge3-Linux-aarch64.sh

* Miniforge3 will be installed at this location: ~/miniforge3/bin/ and add it to your PATH variable.
In order to check the location of executable "conda" file, type the following...

Code Block

language	bash

sudo find / -type f -name "conda"

In my case it returned "~/miniforge3/bin/" and the variable PATH must be changed to...

Code Block

language	bash

export PATH=$PATH:~/miniforge3/bin

Install MLFlow using Conda

Code Block

language	bash

conda install -c https://conda.anaconda.org/paulscherrerinstitute mflow
conda update conda
conda --version

In my case the version is 4.9.2

`Create and activate a conda virtual environment and install MLFlow`

A conda environment is a directory that contains a specific collection of conda packages that you have installed. For example, you may have one environment with NumPy 1.7 and its dependencies. The name of the environment is env_mlflow. Use your Python's version to create an environment...

Code Block

language	bash

conda create --name env_mlflow python=3.7.3
conda activate env_mlflow

Reboot the machine and login again. If you are using a remote machine, reboot the remote instance and use ssh to login again.

After the reboot we can install MLFlow using pip3.

Code Block

language	bash

pip3 install mlflow

`Install Sklearn using pip3 and other dependencies`

We need GCC and G++ compilers as dependencies to build Sklearn.

Code Block

language	bash

sudo apt-get install gcc
sudo apt-get install g++

This app helps us to save the point of the process, when the connection drops. As a result, when we reconnect, we can continue from the point where our process was disrupted and not from the very beginning.

(optional) Install tmux. It takes a lot of time to build Sklearn, and there is a high possibility the internet access will be lost. So, tmux helps us to continue the proccess from where it left off.

Code Block
sudo apt-get install tmux

To open tmux just type... tmux

Install Sklearn using pip3 and the dependencies.

Code Block

language	bash

pip3 install sklearn
pip3 install Cython
pip3 install --upgrade setuptools

`Install Matplotlib`

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.

Code Block

language	bash

conda install -c conda-forge matplotlib

In order to check the installation...

Code Block

language	bash

pip3 install matplotlib

The return must be "Requirement already satisfied"

`Install PostgreSQL`

PostgreSQL, also known as Postgres, is a free and open-source relational database management system emphasising extensibility and SQL compliance.

Code Block

language	bash

sudo apt-get install postgresql
sudo apt-get install postgresql-contrib 
sudo apt-get install postgresql-server-dev-all

`Install Psycopg`

Psycopg is the most popular PostgreSQL database adapter for the Python programming language. Its main features are the complete implementation of the Python DB API 2.0 specification and the thread safety (several threads can share the same connection).

Code Block

language	bash

pip3 install psycopg2

`Download and run MLFlow examples`

Check if Git is already installed...

Code Block

language	bash

git --version

If Git is not installed...

Code Block

language	bash

sudo apt update
sudo apt install git

Clone MLFlow example code

Code Block

language	bash

cd ~
git clone https://github.com/mlflow/mlflow
cd ~/mlflow/examples/sklearn_elasticnet_diabetes/linux

Run the example "train_diabetes"

Code Block

language	bash

python train_diabetes.py 0.1 0.9
python train_diabetes.py 0.5 0.5
python train_diabetes.py 0.9 0.1

For each example above the return must be something like this... RMSE: 71.98302888908191 MAE: 60.5647520017933 R2: 0.2165516143465459

MLflow runs can be recorded either locally in files or remotely to a tracking server. By default, the MLflow Python API logs runs to files in an mlruns directory wherever you ran your program. You can then run "mlflow ui" to see the logged runs.

Code Block

language	bash

mlflow ui

The return must be something like that... 2020-12-03 14:17:36 +0000] [1267] [INFO] Starting gunicorn 20.0.4 [2020-12-03 14:17:36 +0000] [1267] [INFO] Listening at: http://127.0.0.1:5000 (1267) [2020-12-03 14:17:36 +0000] [1267] [INFO] Using worker: sync [2020-12-03 14:17:36 +0000] [1270] [INFO] Booting worker with pid: 1270

At the 2nd line there is the localhost's IP and the port (127.0.0.1:5000). Now we can use them to get the results. Using a remote machine (OpenStack), the instances does not have a Desktop Environment (GNOME, XFCE, e.t.c.) in order to see the results. But we can check if it has created the "index.html" file at http://127.0.0.1:5000...

Code Block

language	bash

cd ~/Download
wget 127.0.0.1:5000
cat index.html

But, using SSH Tunneling we can see the OpenStack's instance localhost on the local Web browser. Syntax: ssh -L port:localhost:port userName@FloatingIP Example: ssh -L 5000:localhost:5000 debian@214.152.131.68 (We can replace the localhost with the 127.0.0.1)

Version	Old Version 13	New Version 14
Changes made by	Takis Mavrodakos (Deactivated)	Takis Mavrodakos (Deactivated)
Saved on	Dec 09, 2020	Dec 09, 2020

Versions Compared

Key

About MLFow

Make Python3 default

Download and install Miniforge3

Install MLFlow using Conda

`Create and activate a conda virtual environment and install MLFlow`

`Install Sklearn using pip3 and other dependencies`

`Install Matplotlib`

`Install PostgreSQL`

`Install Psycopg`

`Download and run MLFlow examples`