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Table of Contents
PerfSPEC Learning Phase INSTALLATION
By follwing thesed steps you can easy run PerfSPEC notebooks
Python
Caution
Due to TensorFlow requiremens Python 3.12 is the latest compatible
For Linux
I end up by downloading Python soruce and compile
For MacOS
Use Homebrew
brew install python@3.12 python3-pip
Warning
After install Python with pip and virtualenv
Install TensorFlow requiremens
pip install tensorflow
Package manager
Use uv
An extremely fast Python package and project manager, written in Rust.
MacOS and Linux
sudo curl -LsSf https://astral.sh/uv/install.sh | sh
To add $HOME/.local/bin to your PATH, either restart your shell or run:
source $HOME/.local/bin/env (sh, bash, zsh)
source $HOME/.local/bin/env.fish (fish)
Notebook tool
Rather than use Jupyter this project use Marimo for a lot of good reasons !
Marimo
python -m venv marimo-env
source marimo-env/bin/activate
uv pip install marimo
Check with marimo tutorial intro --no-token
A web server should be run at http://localhost:2718 with a token if not use --no-token option for a non secure session
Marimo configuration is in $HOME/.config/marimo.toml
PerfSPEC Learning Phase
1 - git clone this repository
git clone https://repo.jesusperez.pro/jesus/perfSPEC-learning.git
cd perfspec-learning
2 - Make structures
For data use data_sample.tar.xc
tar xvJf data_sample.tar.xz
For trained models use models_sample.tar.xz
tar xvJf models_sample.tar.xz
Raw log file raw-audit-logs.log.xz is included in data directory
3 - Run notebook tool like this
Inside perfspec-learning path
cd learning/python
uvx marimo edit --no-token --watch
Connect with a browser to http://localhost:2718
Start with run_perfspec.py
Important
A red box will appear at top left corner prompting to install required packages for the loaded notebook, in console where localhost:2718 appers listening uv will do the magic by installing them using pip
Note each notebook can import some extra packages like train_perfspec.py
In any case some notebook import content from others.
Tip
When all notebooks have being loaded it will be posible also to use them as a Python script by run it in a terminal o console like this:
python model_perfspec.py -- --help
There is also an static html mode to be used, more info: script mode
Some Python packages could be not detected and will require manual installation via command-line, simply for example, use:
uv pip install scikit-learn
uv pip install prettytable