120 lines
3.3 KiB
Markdown
120 lines
3.3 KiB
Markdown
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# PerfSPEC Learning Phase INSTALLATION
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## Python
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Due to [TensorFlow requiremens](https://www.tensorflow.org/install/pip) **Python 3.12** is the latest compatible
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For Linux
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I end up by downloading **Python soruce** and compile
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For MacOS
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Use [Homebrew](https://brew.sh/)
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```
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brew install python@3.12 python3-pip
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```
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> After install Python with **pip* and **virtualenv** <br>
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> Install [TensorFlow requiremens](https://www.tensorflow.org/install/pip)
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```
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pip install tensorflow
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```
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### Package manager
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Use [uv](https://docs.astral.sh/uv/)
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> An extremely fast Python package and project manager, written in Rust.
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MacOS and Linux
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```
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sudo curl -LsSf https://astral.sh/uv/install.sh | sh
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```
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To add $HOME/.local/bin to your PATH, either restart your shell or run:
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source $HOME/.local/bin/env (sh, bash, zsh)
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source $HOME/.local/bin/env.fish (fish)
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## Notebook tool
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Rather than use [Jupyter](https://jupyter.org/) this project use [Marimo](https://marimo.io/) for a lot of good reasons !
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#### Marimo
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```
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python -m venv marimo-env
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source marimo-env/bin/activate
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uv pip install marimo
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```
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Check with `marimo tutorial intro --no-token`
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A web server should be run at `http://localhost:2718` with a token if not use **--no-token** option for a non secure session
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[Marimo](https://marimo.io/) configuration is in `$HOME/.config/marimo.toml`
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### PerfSPEC Learning Phase
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1 - `git clone this repository`
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```
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git clone https://repo.jesusperez.pro/jesus/perfspec-learning.git
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cd perfspec-learning
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```
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2 - Make structures
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For **data** use [data_sample.tar.xc](https://repo.jesusperez.pro/jesus/perfspec-learning/src/branch/main/data_sample.tar.xz)
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```
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tar xvJf data_sample.tar.xz
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````
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For trained models use [models_sample.tar.xz](https://repo.jesusperez.pro/jesus/perfspec-learning/src/branch/main/models_sample.tar.xz)
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```
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tar xvJf models_sample.tar.xz
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````
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Raw log file [raw-audit-logs.log.xz](https://repo.jesusperez.pro/jesus/perfspec-learning/src/branch/main/raw-audit-logs.log.xz) is included in **data** directory
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3 - Run notebook tool like this
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Inside `perfspec-learning` path
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```
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cd learning/python
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uvx marimo edit --no-token --watch
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```
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Connect with a browser to **http://localhost:2718**
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Start with [run_perfspec.py](https://repo.jesusperez.pro/jesus/perfspec-learning/src/branch/main/learning/python/run_perfspec.py)
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> 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](https://docs.astral.sh/uv/) will do the magic by installing them using **pip**
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Note each notebook can import some extra packages like [train_perfspec.py](https://repo.jesusperez.pro/jesus/perfspec-learning/src/branch/main/learning/python/train_perfspec.py)
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In any case some notebook import content from others.
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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:
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```
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python model_perfspec.py -- --help
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```
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There is also an static html mode to be used, more info: [script mode][https://docs.marimo.io/guides/scripts/]
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Some Python packages could be not detected and will require manual installation via command-line, simply for example, use:
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```
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uv pip install scikit-learn
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uv pip install prettytable
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```
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