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Zhen-Dong / HAWQ

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
MIT License
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Can't load provided checkpoints #34

Open L-ED opened 2 years ago

L-ED commented 2 years ago

I downloaded baseline and quantized .pth files for resnet18 and 50, but when i'm trying to load them i'm facing with error

python quant_train.py -a resnet50 --epochs 1 --lr 0.0001 --batch-size 128 --data data/imagenet/ --pretrained --save-path ./checkpoints/ --act-range-momentum=0.99 --wd 1e-4 --data-percentage 0.0001 --fix-BN --checkpoint-iter -1 --quant-scheme uniform8 --resume ./HAWQ/loaded_models/resnet50_baseline/resnet50.pth

Traceback (most recent call last): File "quant_train.py", line 766, in main() File "quant_train.py", line 205, in main main_worker(args.gpu, ngpus_per_node, args) File "quant_train.py", line 242, in main_worker checkpoint = torch.load(args.resume)['state_dict'] KeyError: 'state_dict'

python quant_train.py -a resnet18 --epochs 1 --lr 0.0001 --batch-size 128 --data data/imagenet/ --pretrained --save-path ./checkpoints/ --act-range-momentum=0.99 --wd 1e-4 --data-percentage 0.0001 --fix-BN --checkpoint-iter -1 --quant-scheme uniform8 --resume "/workspace/LyginE/projects/paradigma/quantization/HAWQ/loaded_models/resnet18_uniform8/quantized_checkpoint.pth.tar" --resume-quant

Traceback (most recent call last): File "quant_train.py", line 766, in main() File "quant_train.py", line 205, in main main_worker(args.gpu, ngpus_per_node, args) File "quant_train.py", line 307, in main_worker checkpoint = torch.load(args.resume)['state_dict'] KeyError: 'state_dict'