Has anyone successfully trained a model using only a CPU?

[duruipeng]

I don't hava a GPU, and I encountered the following error when training with a CPU mode.
I don't know how to solve it.
I modified 「train.py」 file to enable CPU training mode, but I encountered the following error when it enters the 「train_and_evaluate」method->「with autocast(enabled=hps.train.fp16_run) 」.

---

in value is tensor(-1.1321)
min value is tensor(-1.1666)
min value is tensor(-1.2234)
max value is tensor(1.1344)
min value is tensor(-1.1321)
min value is tensor(-1.1666)
\MeloTTS-main\venv\lib\site-packages\torch\amp\autocast_mode.py:198: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
warnings.warn('User provided device_type of 'cuda', but CUDA is not available. Disabling')
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Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by passing the keyword argument find_unused_parameters=True to torch.nn.parallel.DistributedDataParallel, and by
making sure all forward function outputs participate in calculating loss.
If you already have done the above, then the distributed data parallel module wasn't able to locate the output tensors in the return value of your module's forward function. Please include the loss function and the structure of the return value of forward of your module when reporting this issue (e.g. list, dict, iterable).
Parameter indices which did not receive grad for rank 0: 18 19
In addition, you can set the environment variable TORCH_DISTRIBUTED_DEBUG to either INFO or DETAIL to print out information about which particular parameters did not receive gradient on this rank as part of this error
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