Hey everyone. I’m building a new backend for Glow called NMP (from NeuroMorphic Processor). It is an embedded device to make inferences from convolutional neural networks. This device only works with quantized models (Int8 and Int16). It turns out that the external library that performs the convolution operations expects the Bias to be quantized on the same scale as the Convolution result (the same applies to FullyConnected operations). Any ideas on how can I specialize this type of quantization?