From 3d9e2faba857d945f15d2c78c0bacc9709544d8b Mon Sep 17 00:00:00 2001 From: nmstoker Date: Sat, 11 Jul 2020 17:56:49 +0100 Subject: [PATCH] Clarify GPU Id use with vocoder training --- vocoder/README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/vocoder/README.md b/vocoder/README.md index 1b65f929..e3baf1f9 100644 --- a/vocoder/README.md +++ b/vocoder/README.md @@ -16,23 +16,23 @@ You can see here an example (Soon)[Colab Notebook]() training MelGAN with LJSpee In order to train a new model, you need to collecto all your wav files under a common parent folder and give this path to `data_path` field in '''config.json''' -You need to define other relevant parameters in your ```config.json``` and then start traning with the following command from Mozilla TTS root path. +You need to define other relevant parameters in your ```config.json``` and then start traning with the following command from Mozilla TTS root path, where '0' is the Id of the GPU you wish to use. -```CUDA_VISIBLE_DEVICES='1' python vocoder/train.py --config_path path/to/config.json``` +```CUDA_VISIBLE_DEVICES='0' python vocoder/train.py --config_path path/to/config.json``` Exampled config files can be found under `vocoder/configs/` folder. You can continue a previous training by the following command. -```CUDA_VISIBLE_DEVICES='1' python vocoder/train.py --continue_path path/to/your/model/folder``` +```CUDA_VISIBLE_DEVICES='0' python vocoder/train.py --continue_path path/to/your/model/folder``` You can fine-tune a pre-trained model by the following command. -```CUDA_VISIBLE_DEVICES='1' python vocoder/train.py --restore_path path/to/your/model.pth.tar``` +```CUDA_VISIBLE_DEVICES='0' python vocoder/train.py --restore_path path/to/your/model.pth.tar``` Restoring a model starts a new training in a different output folder. It only restores model weights with the given checkpoint file. However, continuing a training starts from the same conditions the previous training run left off. You can also follow your training runs on Tensorboard as you do with our TTS models. ## Acknowledgement -Thanks to @kan-bayashi for his [repository](https://github.com/kan-bayashi/ParallelWaveGAN) being the start point of our work. \ No newline at end of file +Thanks to @kan-bayashi for his [repository](https://github.com/kan-bayashi/ParallelWaveGAN) being the start point of our work.