A couple of very noob questions

[YuvoBowmar4244]

Hi friends! The demos of this are blowing my mind! I'm trying to play around with this but I'm just a musician, so I haven't gotten very far. A couple of questions.

1. I'm stuck right here. Here are my parameters and subsequent output. What can be gleaned from this? A 97 GB data.mdb appears to have been almost instantaneously created, but I'm assuming it's just an empty container?

python train_rave.py --name ravex1 --wav F:\rave\WavTestA --preprocessed H:\rave\temp\ravex1\rave --sr 48000 --data-size 16 --n-signal 65536 --capacity 64 --warmup 1000000 --no-latency false --max-kl 0.1

No GPU found.
GPU available: False, used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
2022-04-08 06:25:50.553284: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-04-08 06:25:50.553590: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.

  | Name          | Type                | Params
------------------------------------------------------
0 | pqmf          | CachedPQMF          | 16.7 K
1 | loudness      | Loudness            | 0
2 | encoder       | Encoder             | 4.8 M
3 | decoder       | Generator           | 12.8 M
4 | discriminator | StackDiscriminators | 16.9 M
------------------------------------------------------
34.6 M    Trainable params
0         Non-trainable params
34.6 M    Total params
138.202   Total estimated model params size (MB)
Validation sanity check:   0%|                                                                                                                                                                                                                                                              | 0/1 [00:00<?, ?it/s]T
raceback (most recent call last):
  File "C:\Users\Bob\Documents\GitHub\RAVE\train_rave.py", line 154, in <module>
    trainer.fit(model, train, val)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 552, in fit
    self._run(model)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 922, in _run
    self._dispatch()
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 990, in _dispatch
    self.accelerator.start_training(self)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\accelerators\accelerator.py", line 92, in start_training
    self.training_type_plugin.start_training(trainer)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\plugins\training_type\training_type_plugin.py", line 161, in start_training
    self._results = trainer.run_stage()
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1000, in run_stage
    return self._run_train()
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1035, in _run_train
    self._run_sanity_check(self.lightning_module)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1122, in _run_sanity_check
    self._evaluation_loop.run()
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\loops\base.py", line 111, in run
    self.advance(*args, **kwargs)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\pytorch_lightning\loops\dataloader\evaluation_loop.py", line 107, in advance
    dataloader_iter = enumerate(dataloader)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\torch\utils\data\dataloader.py", line 368, in __iter__
    return self._get_iterator()
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\torch\utils\data\dataloader.py", line 314, in _get_iterator
    return _MultiProcessingDataLoaderIter(self)
  File "C:\Users\Bob\Documents\GitHub\RAVE2\venv\lib\site-packages\torch\utils\data\dataloader.py", line 927, in __init__
    w.start()
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\process.py", line 121, in start
    self._popen = self._Popen(self)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\context.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\context.py", line 327, in _Popen
    return Popen(process_obj)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\popen_spawn_win32.py", line 93, in __init__
    reduction.dump(process_obj, to_child)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
TypeError: cannot pickle 'Environment' object
PS C:\Users\Bob\Documents\GitHub\RAVE> Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python39\lib\multiprocessing\spawn.py", line 126, in _main
    self = reduction.pickle.load(from_parent)
EOFError: Ran out of input

2. The resample and duration utilities seem like they might be important. How exactly do I run them?

3. Could this all be wrapped up into a Colab for a simple-minded guitar guy like myself?

Anyway, keep up the good work all! Don't let me slow you down. Just excited to see where this is all going and how I might be able to use it creatively some day. :)