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>>> nmstoker |
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>>> ttaong6 |
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>>> othiele |
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>>> ttaong6
[January 13, 2020, 3:09pm]
Hello TTS team, thanks a lot for open sourcing this project!
I'm a newbie to TTS DeepLearning stuff... so, I'm trying to get a hang
of this by going through the process of training and inferring using
LJSpeech sample dataset. I ran the training script using this notebook -
https://gist.github.com/erogol/97516ad65b44dbddb8cd694953187c5b. It
went well... I'm using Tacotron2 model. I stopped the training at 10K
checkpoint. I want to go through the infer process of generating the
wave file for an input sentence. I know that 10K iterations are not
enough, but I just want to iron out end to end process before committing
to performing full training (even if what I get is just static or
gibberish). So, I'm now trying to perform infer using this notebook -
https://colab.research.google.com/github/tugstugi/dl-colab-notebooks/blob/master/notebooks/Mozilla_TTS_WaveRNN.ipynb
# I'm ending up with the following errors:
(this is the cell I'm executing; the last one) slash
align, spec, stop_tokens, wav = tts(model, SENTENCE, CONFIG, use_cuda,
ap, speaker_id=0, use_gl=False, figures=False)
(error below) slash
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in
linear(input, weight, bias) slash
1370 ret = torch.addmm(bias, input, weight.t()) slash
1371 else: slash
1373 if bias is not None: slash
1374 output += bias
RuntimeError: size mismatch, m1: slash [1 x 560 slash ], m2: slash [80 x 256 slash ] at
/pytorch/aten/src/THC/generic/THCTensorMathBlas.cu:290
===== slash
I'm pretty much using standard config files and sample dataset
(LJSpeech). Wondering what config changes should I make (to tts or
wavenet), or how to overcome this error, for the 10K checkpoint model I
have (Tacotron2)? Any help is appreciated. Thanks!
[This is an archived TTS discussion thread from discourse.mozilla.org/t/infer-error-with-tacotron2-wavenet]
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