Comments (2)
amirgholami
commented on August 18, 2024
2
I just re-tested the code with Pytorch 1.5, Cuda 10.1, and Python 3.8 and got the same results as reported in README.
We plan to open source the mixed precision along with some new features soon.
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xieydd
commented on August 18, 2024
@amirgholami I re-download imagenet val dataset, i got the right result, tks.
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Related Issues (20)
- How much calibration data is needed? HOT 3
- Where could I find low bit quantization code.
- increased inference latency for quantized model HOT 4
- The accuracy of pytorch official model is 0.3% lower than full precision HOT 1
- bitwidth of each layer (discussion of MP) HOT 2
- Export quantized model into pth file
- How to Train A Quantized SSD Detector?
- 生成数据时，提取的网络激活位置是否有bug? HOT 1
- Backpropagation function for quantized model
- is the initialized data from a uniform distribution instead of a gaussian distribution?
- Could you share the slides of the oral report? Thanks
- The result of using original ImageNet dataset to calibrate 4bit model is worse than ZeroQ, why is that?
- Why do the weights need to be dequantized after one quantization? HOT 1
- Runtime error when running uniform_test.py
- Welcome update to OpenMMLab 2.0
- Model remains float32 type after quantization HOT 1
- How is the Mixed Precision bit setting is automated? HOT 1
- Is the proposed method a Offline quantization or Run-time quantization? HOT 2
- Difference in Baseline FP32 accuracy numbers for MobileNetV2 and ResNet18 as compared to DFQ HOT 4
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