Comments (2)
Hi,
since the computation cost is not high, we don't implement the multi-GPU training.
If you need a multi-GPU version, I would like to recommend you modify the code following the Parallel WaveGAN repo (https://github.com/kan-bayashi/ParallelWaveGAN).
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Hi, since the computation cost is not high, we don't implement the multi-GPU training. If you need a multi-GPU version, I would like to recommend you modify the code following the Parallel WaveGAN repo (https://github.com/kan-bayashi/ParallelWaveGAN).
Thank you very much for your answer
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Related Issues (20)
- What data was used by the pretrained model of LibriTTS? HOT 1
- Some questions about CausalConvTranspose1d in conv_layer.py HOT 3
- The test results are different from those in the paper HOT 7
- Permissive license + patents
- VCTK dataset HOT 11
- vq_loss increase, not converge HOT 7
- projector(e)? HOT 7
- LOSS? HOT 8
- download link. needs. more. juice. HOT 1
- quantizer dropout HOT 3
- LibriTTS dataset HOT 2
- Baseline? HOT 4
- Fix the encoder HOT 4
- Samplerates' affect on hyperparameters HOT 4
- unable to access exp link HOT 1
- Increasing batch length HOT 2
- The trained models seem overfitted to their training sets? HOT 3
- Perplexity blows up at start of training HOT 9
- Is it missing some activation functions between some layers? HOT 8
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