feat: Add missing operators for AIDGE model benchmarking

Context

I am working on benchmarking AIDGE models by fully creating them in AIDGE, setting their weights randomly, and exporting them to C++. The goal is to verify if the outputs in C++ match the forward pass results in AIDGE. You can find it here

To achieve this, I have added several missing operators necessary for running models such as:

• SqueezeNet
• ResNet18 / ResNet50
• MLP for MNIST
• MobileNet

These operators are now available in the export pipeline to ensure proper benchmarking.

Modified Files

• Operators & Kernels

  • aidge_export_cpp/kernels/batchnorm.hpp: Added missing batch normalization operator.
  • aidge_export_cpp/kernels/concat.hpp: Added concatenation operator.
  • aidge_export_cpp/kernels/pad.hpp: Added padding operator.
  • aidge_export_cpp/kernels/pooling.hpp: Added AvgPooling2D.
  • aidge_export_cpp/kernels/softmax.hpp: Added softmax operator.

• Python Script

  • aidge_export_cpp/operators.py: Updated operator handling to include new additions.

• Configuration Templates

  • aidge_export_cpp/templates/configuration/*: Added configurations for batchnorm, concat, pad, and softmax.

• Kernel Forward Templates

  • aidge_export_cpp/templates/kernel_forward/*: Added missing forward implementations for batchnorm, concat, pad, and softmax.

• Unit Tests

  • aidge_export_cpp/unit_tests/test_export.py: Updated tests to validate newly added operators.

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Detailed Major Modifications

• Implemented missing operators to support model export and validation in C++.
• Ensured each new operator follows the existing API.
• Updated test cases to validate correctness of the exported model execution.
• Added the possibility of setting the weights inside the model randomly or with a default value to stay deterministic for the unit tests

TODO

• Add some of the missing args of Pad2D. Do add assertion for now that attribute for padding is constant fill (i.e.do not support other attributes such as mirror etc...).