Comments (4)
Hi, thanks for the report!
Did you train a model based on the bmshj2018-factorized architecture? or the toy network in the example training file?
Can you run print(torch.load("checkpoint_best_loss.pth.tar").keys())
?
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Hi, thanks for the report!
Did you train a model based on the bmshj2018-factorized architecture? or the toy network in the example training file?
Can you runprint(torch.load("checkpoint_best_loss.pth.tar").keys())
?
Thanks so much for your quick reply!
I trained the model in the example training file:
python3 examples/train.py -d /path/to/my/image/dataset/ --epochs 300 -lr 1e-4 --batch-size 16 --save , just replace my own dataset; So what should i use about the argument "-a ?"
when i run the :"print(torch.load("checkpoint_best_loss.pth.tar").keys())", got "dict_keys(['epoch', 'state_dict', 'loss', 'optimizer', 'aux_optimizer'])"
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ok thanks, so the toy model in the example training file is not defined in the reference compressai models. If you want to use compressai.utils.eval_model
you need to use one of the implemented architectures or add support for a custom architecture.
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ok thanks, so the toy model in the example training file is not defined in the reference compressai models. If you want to use
compressai.utils.eval_model
you need to use one of the implemented architectures or add support for a custom architecture.
Hi, I trained the model in the following command:
python3 examples/train.py -m bmshj2018-factorized -d images
--batch-size 16 -lr 1e-4 --save --cuda
bmshj2018-factorized is the default architecture. However, when I evaluate the model with the command:
python -m compressai.utils.eval_model checkpoint images/test
-a bmshj2018-factorized -p checkpoint.pth.tar
I got the error:
File "/project/6003167/compressai/compressai/models/google.py", line 285, in from_state_dict
N = state_dict["g_a.0.weight"].size(0)
KeyError: 'g_a.0.weight'
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