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

Context

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

aidge_export_cpp/kernels/convolution.hpp

@@ -47,8 +47,9 @@ void convolution_forward(
             : clamp(CHANNELS_HEIGHT + PADDING_Y - (oy * STRIDE_Y),
                     0, DILATED_KERNEL_HEIGHT);
         const int iy = (oy * STRIDE_Y) - PADDING_Y;
-
-#pragma omp parallel for collapse(2)
+#ifdef _OPENMP
+    #pragma omp parallel for collapse(2)
+#endif
         for (int ox = 0; ox < OUTPUTS_WIDTH; ++ox) {
             for (int output = 0; output < NB_OUTPUTS; ++output) {
                 // moved to inner loop for collapsing -->