There are quantized MobileNet v1 models available at https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md
I see floating point scaling values associated with the weights and biases in the model, but it isn't evident how these should be used in the operations scaling.
The GEMMLOWP quantization info describes scaling values associated with input, weight and the operation's accumulator downscale.
Should the bias scaling value be used alone for down-scaling the accumulator, or is the weight scaling value required?
In short, I'm trying to determine how the two provided scaling values should be used. Thanks.