Training problem

[JokeCorleone]

First of all, thank you for sharing the open-source of Multi-Tacotron-Voice-Cloning. I also just started learning about natural language processing programming. And I also started learning Python programming. -I put the software in the directory: D: \ SV2TTS -I put the dataset in the directory: D: \ Datasets, I have D: \ Datasets \ book and D: \ Datasets \ LibriSpeech

When using the code you provided, I had some training issues:

1. I have finished the steps
   • Run python encoder_preprocess.py D: \ Datasets and the result is Arguments: datasets_root: D: \ Datasets out_dir: D: \ Datasets \ SV2TTS \ encoder datasets: ['preprocess_voxforge'] skip_existing: False Done preprocessing book.
2. Run visdom
3. But I could not continue
   • Run python encoder_train.py my_run D: \ Datasets because the notice appeared C: \ Users \ Admin \ anaconda3 \ envs \ [Test_Voice] \ lib \ site-packages \ umap \ spectral.py: 4: NumbaDeprecationWarning: No direct replacement for 'numba.targets' available. Visit https://gitter.im/numba/numba-dev to request help. Thanks! import numba.targets usage: encoder_train.py [-h] [--clean_data_root CLEAN_DATA_ROOT] [-m MODELS_DIR] [-v VIS_EVERY] [-u UMAP_EVERY] [-s SAVE_EVERY] [-b BACKUP_EVERY] [-f] [--visdom_server VISDOM_SERVER] [--no_visdom] run_id encoder_train.py: error: unrecognized arguments: D: \ Datasets

My question: How can I fix this problem?

Thanks again for your sharing!!!

[vlomme]

Hello. use python encoder_train.py my_run --clean_data_root D:\Datasets\SV2TTS\encoder

[JokeCorleone]

Hello @vlomme Thank for your support, When I used python encoder_train.py my_run --clean_data_root D:\Datasets\SV2TTS\encoder,
The result is

File "encoder_train.py", line 46, in train(**vars(args)) File "D:\SV2TTS\encoder\train.py", line 87, in train model.do_gradient_ops() File "D:\SV2TTS\encoder\model.py", line 39, in do_gradient_ops clip_gradnorm(self.parameters(), 3, norm_type=2) File "C:\Users\Admin\anaconda3\envs[Test_Voice]\lib\site-packages\torch\nn\utils\clip_grad.py", line 30, in clip_gradnorm total_norm = torch.norm(torch.stack([torch.norm(p.grad.detach(), norm_type) for p in parameters]), norm_type) RuntimeError: All input tensors must be on the same device. Received cpu and cuda:0

[ramanova]

Hello, getting the same error, torch==1.5.0 I see that we have

    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    # FIXME: currently, the gradient is None if loss_device is cuda
    loss_device = torch.device("cpu")

after that if we are using clip_gradnorm from torch, it performs operation on all of the parameters, two of which are on cpu, and the rest on cuda:0

total_norm = torch.norm(torch.stack([torch.norm(p.grad.detach(), norm_type) for p in parameters]), norm_type)

which throws the error. Could it be that the torch version is incorrect? I'm using 1.5.0

[UPDATE] Reinstalled torch and it started training! pip uninstall torch # you might need to ran it twice, check with pip list | grep torch # that you don't have torch left pip install torch # or pip install torch==1.5.0 to ensure the version

[JokeCorleone]

Hello, When I trained vocoder (run python vocoder_train.py my_run D:\Datasets), I encountered an error:

+------------+--------+--------------+ | Batch size | LR | Sequence Len | +------------+--------+--------------+ | 60 | 0.0001 | 1000 | +------------+--------+--------------+

RuntimeError: CUDA out of memory. Tried to allocate 118.00 MiB (GPU 0; 4.00 GiB total capacity; 2.87 GiB already allocated; 10.61 MiB free; 32.29 MiB cached)

how can i solve this error ?

[vlomme]

not enough video memory. Reduce the Batch size

[JokeCorleone]

Thank @vlomme