BRECQ
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Pytorch implementation of BRECQ, ICLR 2021
So I tried running your code on my dataset with a pre-trained ResNet50 model. I got these results Full precision model i got accuracy of : MobileNetV2 (58.19) Quantized model...
Hi, So I tried running your code on CIFAR-10 with a pre-trained ResNet50 model. I've attached the code below. My accuracy however does not come nearly as close to the...
We use the APoT method on COCO dataset ,but the mAP is very low,why?Thx! @yhhhli @blackandredplayerinfuture
I used the model (resnet18) provided by the project and the default parameters of the code to run W4A4 quantization. The results are quite different from those in the paper....
I tried running your code for with a pre-trained ResNet50 and MobilieNetV2 model. I got loss function value for output and pred losses: rec_loss = lp_loss(pred, tgt, p=self.p) :param pred:...
Hi, it is a nice code for a quantization. However, I have some questions about sensitivity measurement and genetic algorithm. 1. In the paper, you expressed that layer sensitivity can...
Thank you very much for your work, I refer to your code modification yolov5,When w4a8 quantizing There are nearly 3points of loss,Have you experimented yolov5
Hi, it is a nice code for a quantization. However, I have some questions about sensitivity measurement and genetic algorithm. 1. In the paper, you expressed that layer sensitivity can...
the scale and offset of UniformAffineQuantizer are tensor-type data after I finished quantization. How to convert them to scalar data ,used to generate quantization form. @yhhhli such as: Encoding:{ bitwidth:...
Hey, Im just wondering what BRECQ is stand for? BR as block reconstruction but what about the other letters?