[Feat] Add quantized exports for Resnet18 and LeNet

Context

This MR aims to enable the quantized (int8) export of LeNet and Resnet18.

It brings a lot of changes to clean and update the CPP Aidge export with the latest features.

Refactor

• Operators register files are splitted from one global operators.py file to several ones, each matching the actual implementation of one given kernel.
• Some utils functions are added to simplify the export file :
  • cpp_fuse_to_metaops() : Fuse the model nodes into the metaoperators corresponding to the operators supported by the export.
  • set_nodes_names() : Rename the newly created nodes based on their type, position in the graph and number of iterations of this specific layer, to ensure readability once exported.
  • set_nodes_datatypes() : Datatypes have to be set manually after the quantization step.
  • read_log_file() : May be useful to compare intermediate results...

New features

General improvements

• Now possible to ignore some producers during export phase, as some of them are not relevant (for instance, the producers holding scaling coefficients, which are handled separately).
• Change the kernels_to_copy export node system as the old system had some limitations. Indeed, it was not possible to chose a destination path different from the source path. Also the copied kernel would be automatically included in the fwd file, sometime leading to unused includes. The new system is based on a list of dict holding, for each kernel file, the source and destination paths as well as a boolean to indicate if the kernel needs to be included in the forward file.
• Add an aidge_cmp feature which allows to compare the aidge_export_cpp and aidge_backend_cpu intermediate tensor results for the exported model.

New models examples

• Add LeNet generation file (create_lenet.py) which create, train and export a LeNet model.
• Add a lenet.py file describing the different steps to perform an export with the aidge_export_cpp module.
• Add a resnet18.py file describing the different steps to perform an export with the aidge_export_cpp module.
• Add these example scripts to the CI

Quantized Export

• Handle the scaling nodes added by the PTQ and transmit the shift and coef parameters to the generated export.
• Add scaling functions (SingleShift and FixedPoint) to the export.
• Add a aidge_cmp option which exports the log_outputs (intermediate tensors generated by the aidge_backend_cpu) as reference and allow data comparison at inference time.
• Now possible to export quantized LeNet using --dtype int8 while running the lenet.py file.
• Now possible to export quantized Resnet18 using --dtype int8 while running the resnet18.py file.

Related Issues

[ResNet18] Export Cpp INT8 not supported

TODO

• LeNet Export fp32
• LeNet Export int8
• Resnet18 Export fp32
• Resnet18 Export int8