aidge-learning 0.9.1.post2

Functions and algorithms to train models in the AIDGE framework

aidge_learning

In this module, you can find functions and classes to train your models:

• Optimizer (SGD)
• LRScheduler (ConstantLR, StepLR)
• loss functions (MSE)

Quick Start

Prerequisite:

• aidge_core

• aidge_backend_cpu
  • Only needed for tests.

pip install aidge-learning

🛠 Build from Source

Prerequisite (in addition to previous one):

• Please review the global installation instructions before proceeding.
• If using a virtual environment, use the same one for all Aidge modules.

1. Python or C++ installation using setup scripts

Environment	C++ Development	Python Development
Windows	.\setup.ps1 -Modules learning -Clean -Tests	.\setup.ps1 -Modules learning -Clean -Tests -Python
Unix	./setup.sh -m learning --clean --tests	./setup.sh -m learning --clean --tests --python

[!TIP] Use Get-Help setup.ps1 (Windows) or ./setup.sh -h (Unix) for full documentation.

2. Python Installation using pip

Run these commands from the aidge_learning/ directory:

# Standard install
pip install . -v

# Install with testing dependencies
pip install .[test] -v && pytest

Editable Install (Experimental)

Use this for real-time development without re-installing.

pip install --no-build-isolation -ve . --config-settings=editable.rebuild=true -Cbuild-dir=build

3. C++ Installation (CMake)

A CMakePresets.json is provided for standard configurations.

# Configure, Build, and Install
cmake --preset clang-debug
cmake --build --preset clang-debug
cmake --install

# Run C++ Tests
ctest --test-dir build/

[!TIP] Create a CMakeUserPresets.json to define your own local build configurations.