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New feature, bug fixes, code modifications to create a CPP export of Resnet18 (quantified model)

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Summary

This MR is or adapt, fix error and add new features to this module for support the ResNet18 quandfied model

Detailed major modifications

Work on operators:

  • Pooling
    • [Feat] integration of rounding for an integer data type (pooling.hpp)
  • Rescaling
    • [Feat] Add rescaling function (rescaling.hpp)
    • [Feat] Add registrar file (CppRescaling.py)
    • [Feat] Add config and forward jinja for rescaling operator (rescaling_config.jinja & rescaling_forward.jinja)
  • Elemwise
    • [Refactor] Change "elemwise_op" attribute resolution (elemwise_config.py)
    • [Refactor] Use rescaling.jinja file to collect rescaling attribute

Work on export object:

  • [Fix] Modify cpp_recipes: renaming operator to fix error (export_utils.py)
  • [Feat] Add normalize function necessary to format data before PTQ (export_utils.py)
  • [Feat] Add external input_tensor option. Can be use with main cpp generation fucntion (export.py)
  • [Fix] Replacing a hard CAST with a CAST based on the output data type (_aidge_cmp.jinja)
  • [Feat] create a new template for aidge_cmp function (for integer datatype)

Work to fix error for openmp option:

  • [Fix] Add "#ifdef _OPENMP" to enable or disable the OpenMP option of the compilation
    • convolution.hpp
    • fullyconnected.hpp
    • leakyrelu.hpp
    • pooling.hpp
Edited by Mickael GUIBERT

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