Upgrade to Quantizeml 0.12.1, Akida/CNN2SNN 2.10.0 and Akida models 1.6.1

Update QuantizeML to version 0.12.1

New features

• ONNX Runtime and ONNX requirements bumped to 1.19 and 1.16 respectively
• Limited requantization support and improved errors and warnings
• Added support for ONNX 'sub' nodes when rescaling
• Improved ONNX nodes naming during sanitizing and quantization
• When they comes with more than 2 inputs, Concatenate layers are now split into several layers

Bug fixes:

• Fixed RuntimeError management when using custom patterns for quantization
• Combined custom patterns with standard patterns so that quantization defaults to standard when custom fails
• 'input_weight_bits' was not always properly applied to the first layers depending on its type
• Fixed ONNX quantization issue with padding variable name in convolution layers

Update Akida and CNN2SNN to version 2.10.0

Aligned with FPGA 1538/1532(ViT)

New features

• [akida] Mapping mode AllNps (default) will limit search to layer that can be split
• [akida] Custom MapConstraints to override mapping mode has been reworked for easier usage
• [akida] Improved mapping search for transposed convolution
• [akida] Aligned skip DMA info in mesh discovery with other NPs info
• [cnn2snn] Updated requirement to QuantizeML 0.12.1

Bug fixes:

• [akida] Fixed a crash when loading non .FBZ files
• [akida] Fixed InputConvolutional output for resolution 384
• [akida] Prevent using the Model constructor with a list of layers when the list contains skip connections

Update Akida models to 1.6.1

• Limited MTCNN dependency version
• Updated QuantizeML dependency to 0.12.1 and CNN2SNN to 2.10.0

Documentation update

• Updated broken ONNX links in "custom pattern" advanced example