Core algorithms for operators and graph of the AIDGE framework
Project description
Aidge Core
Aidge is a powerful open-source framework for optimizing and deploying deep neural networks on embedded systems. This is the core library required by every other module.
Quick Start
pip install aidge-core
python -c "import aidge_core ; print(f'Available backends:\n{aidge_core.get_keys_Conv2DOp()}')"
This should print:
Available backends:
{'export_serialize'}
[!NOTE] Pypi packages are experimental !
Build from Source
Prerequisite:
- Please review the global installation instructions before proceeding.
- Use the same virtual environment for all Aidge modules.
1. Python or C++ installation using setup scripts
| Environment | C++ Development | Python Development |
|---|---|---|
| Windows | .\setup.ps1 -Modules core -Tests -CppOnly |
.\setup.ps1 -Modules core -Tests |
| Unix | ./setup.sh -m core --tests --cpp-only |
./setup.sh -m core --tests |
[!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_core/ directory:
# Standard install
pip install . -v
# Install with testing dependencies
pip install .[test] -v && pytest
Editable Install (Experimental)
For real-time development without re-installing:
pip install --no-build-isolation -ve . --config-settings=editable.rebuild=true -Cbuild-dir=build
3. C++ Installation using 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.jsonto define your own local build configurations.
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