Hello everyone,
I hope you are having a great day,
I’m having difficulties loading a quantized model.
When I investigated I noted that the chekpoint file has 236 parameter keys, while the model, after being fused as only 112 parameter names.
(base) marian@u04-2:/mnt/s3user/Pytorch_Retinaface_quantized# python test_widerface.py --trained_model ./weights/mobilenet0.25_Final_quantized.pth --network mobile0.25layers:
Loading pretrained model from ./weights/mobilenet0.25_Final_quantized.pth
remove prefix 'module.'
Missing keys:235
Unused checkpoint keys:171
Used keys:65
Traceback (most recent call last):
File "/root/.vscode/extensions/ms-python.python-2020.1.58038/pythonFiles/ptvsd_launcher.py", line 43, in <module>
main(ptvsdArgs)
File "/root/.vscode/extensions/ms-python.python-2020.1.58038/pythonFiles/lib/python/old_ptvsd/ptvsd/__main__.py", line 432, in main
run()
File "/root/.vscode/extensions/ms-python.python-2020.1.58038/pythonFiles/lib/python/old_ptvsd/ptvsd/__main__.py", line 316, in run_file
runpy.run_path(target, run_name='__main__')
File "/root/anaconda3/lib/python3.7/runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "/root/anaconda3/lib/python3.7/runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "/root/anaconda3/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/mnt/f3user/Pytorch_Retinaface_quantized/test_widerface.py", line 114, in <module>
net = load_model(net, args.trained_model, args.cpu)
File "/mnt/f3user/Pytorch_Retinaface_quantized/test_widerface.py", line 95, in load_model
model.load_state_dict(pretrained_dict, strict=False)
File "/root/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 830, in load_state_dict
self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for RetinaFace:
While copying the parameter named "ssh1.conv3X3.0.weight", whose dimensions in the model are torch.Size([32, 64, 3, 3]) and whose dimensions in the checkpoint are torch.Size([32, 64, 3, 3]).
While copying the parameter named "ssh1.conv5X5_2.0.weight", whose dimensions in the model are torch.Size([16, 16, 3, 3]) and whose dimensions in the checkpoint are torch.Size([16, 16, 3, 3]).
While copying the parameter named "ssh1.conv7x7_3.0.weight", whose dimensions in the model are torch.Size([16, 16, 3, 3]) and whose dimensions in the checkpoint are torch.Size([16, 16, 3, 3]).
While copying the parameter named "ssh2.conv3X3.0.weight", whose dimensions in the model are torch.Size([32, 64, 3, 3]) and whose dimensions in the checkpoint are torch.Size([32, 64, 3, 3]).
While copying the parameter named "ssh2.conv5X5_2.0.weight", whose dimensions in the model are torch.Size([16, 16, 3, 3]) and whose dimensions in the checkpoint are torch.Size([16, 16, 3, 3]).
.....
The full list can be found here.
basically the weights cant be found. plus the scale and zero_point which are missing from the fused model.
The following snippet is the actual training loop which was used to train and save the model :
if __name__ == '__main__':
# train()
...
net = RetinaFace(cfg=cfg)
print("Printing net...")
print(net)
net.fuse_model()
...
net.qconfig = torch.quantization.get_default_qat_qconfig('fbgemm')
torch.quantization.prepare_qat(net, inplace=True)
print(f'quantization preparation done.')
...
quantized_model = net
for i in range(max_epoch):
net = net.to(device)
train_one_epoch(net, data_loader, optimizer, criterion, cfg, gamma, i, step_index, device)
if i in stepvalues:
step_index += 1
if i > 3 :
net.apply(torch.quantization.disable_observer)
if i > 2 :
net.apply(torch.nn.intrinsic.qat.freeze_bn_stats)
net=net.cpu()
quantized_model = torch.quantization.convert(net.eval(), inplace=False)
quantized_model.eval()
# evaluate on test set ?!
torch.save(net.state_dict(), save_folder + cfg['name'] + '_Final.pth')
torch.save(quantized_model.state_dict(), save_folder + cfg['name'] + '_Final_quantized.pth')
#torch.jit.save(torch.jit.script(quantized_model), save_folder + cfg['name'] + '_Final_quantized_jit.pth')
by the way test_widerface.py
can be accessed here
You can view keys here
Why has this happened? How should this be taken care of?