FINN uses <a href="https://github.com/Xilinx/brevitas/tree/master/brevitas_examples/bnn_pynq">
several pre-trained QNNs</a>
FINN uses `several pre-trained QNNs <https://github.com/Xilinx/brevitas/tree/master/brevitas_examples/bnn_pynq>`_
that serve as examples and testcases.
* TFC, SFC, LFC... are fully-connected networks trained on the MNIST dataset
* CNV is a convolutional network trained on the CIFAR-10 dataset
* w\_a\_ refers to the quantization used for the weights (w) and activations (a) in bits
These networks are built end-to-end as part of the <a href="https://github.com/Xilinx/finn/blob/master/tests/end2end/test_end2end_bnn_pynq.py">FINN integration tests</a>,
These networks are built end-to-end as part of the `FINN integration tests <https://github.com/Xilinx/finn/blob/master/tests/end2end/test_end2end_bnn_pynq.py>`_ ,
and the key performance indicators (FPGA resource, frames per second...) are
automatically posted to the dashboard below.
To implement a new network, you can use the <a href="https://github.com/Xilinx/finn/blob/dev/tests/end2end/test_end2end_bnn_pynq.py">
integration test code</a> as a starting point, as well as the relevant
@@ -75,15 +75,21 @@ from the FINN root directory* as follows:
::
python setup.py test --addopts "-k test_end2end_tfc_w1a2"
python setup.py test --addopts "-k test_brevitas_debug"
Finally, if you want to run tests in parallel (e.g. to take advantage of a multi-core CPU)
If you want to run tests in parallel (e.g. to take advantage of a multi-core CPU)
you can use:
* pytest-parallel for any rtlsim tests, e.g. `python setup.py test --addopts "-k rtlsim --workers auto"`
* pytest-xdist for anything else, make sure to add `--dist=loadfile` if you have tests in the same file that have dependencies on each other e.g. `python setup.py test --addopts "-k mytest -n auto --dist=loadfile"`
Please see the pytest documentation for more about picking tests by marks or by name.
Finally, the full test suite with appropriate parallelization can be run inside the container by:
* The repository, this Read the Docs website corresponds to. It is about the FINN compiler, which is the centerpiece of the FINN project. Details can be looked up directly in the `FINN GitHub repository <https://github.com/Xilinx/finn>`_. To learn more about the FINN compiler, use this website and for a hands-on experience the repository contains some Jupyter notebooks which can be found under this `link <https://github.com/Xilinx/finn/tree/dev/notebooks>`_.
* The FINN compiler, which this Read the Docs website corresponds to and is the centerpiece of the FINN project. Details can be looked up directly in the `FINN GitHub repository <https://github.com/Xilinx/finn>`_. To learn more about the FINN compiler, use this website and for a hands-on experience the repository contains some Jupyter notebooks which can be found under this `link <https://github.com/Xilinx/finn/tree/dev/notebooks>`_.
