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I have a v2 RAVE model (default config) trained in v2.2.2, which works fine to export and play. I then upgraded to v2.3.1 and attempted to train a prior for this model with rave train_prior --model runs/birdfrog1_fe77618ebd/version_9/ --db_path datasets/birdfrog1/ --out_path priors
but received the following error message:
/home/username/miniconda3/lib/python3.9/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
model found : runs/birdfrog1_fe77618ebd/version_9/checkpoints/best.ckpt
Traceback (most recent call last):
File "/home/username/miniconda3/bin/rave", line 8, in <module>
sys.exit(main())
File "/home/username/miniconda3/lib/python3.9/site-packages/scripts/main_cli.py", line 34, in main
app.run(train_prior.main)
File "/home/username/miniconda3/lib/python3.9/site-packages/absl/app.py", line 308, in run
_run_main(main, args)
File "/home/username/miniconda3/lib/python3.9/site-packages/absl/app.py", line 254, in _run_main
sys.exit(main(argv))
File "/home/username/miniconda3/lib/python3.9/site-packages/scripts/train_prior.py", line 106, in main
prior = rave.prior.VariationalPrior(pretrained_vae=pretrained)
File "/home/username/miniconda3/lib/python3.9/site-packages/gin/config.py", line 1605, in gin_wrapper
utils.augment_exception_message_and_reraise(e, err_str)
File "/home/username/miniconda3/lib/python3.9/site-packages/gin/utils.py", line 41, in augment_exception_message_and_reraise
raise proxy.with_traceback(exception.__traceback__) from None
File "/home/username/miniconda3/lib/python3.9/site-packages/gin/config.py", line 1582, in gin_wrapper
return fn(*new_args, **new_kwargs)
File "/home/username/miniconda3/lib/python3.9/site-packages/rave/prior/model.py", line 36, in __init__
raise RuntimeError('please init Prior with either fidelity or latent_size keywords')
RuntimeError: please init Prior with either fidelity or latent_size keywords
In call to configurable 'VariationalPrior' (<class 'rave.prior.model.VariationalPrior'>)
When I specify either latent_size or fidelity with a custom .gin file, I receive a new error during the data loading stage which I'm happy to share if it's of interest. This is on Python 3.9, Debian 10, RAVE 2.3.1, and Torch 2.1.2.
The text was updated successfully, but these errors were encountered:
Hi,
I have a v2 RAVE model (default config) trained in v2.2.2, which works fine to export and play. I then upgraded to v2.3.1 and attempted to train a prior for this model with
rave train_prior --model runs/birdfrog1_fe77618ebd/version_9/ --db_path datasets/birdfrog1/ --out_path priors
but received the following error message:
When I specify either latent_size or fidelity with a custom .gin file, I receive a new error during the data loading stage which I'm happy to share if it's of interest. This is on Python 3.9, Debian 10, RAVE 2.3.1, and Torch 2.1.2.
The text was updated successfully, but these errors were encountered: