train a clarinet model with LJspeech and a trained wavenet model.
train a clarinet model with LJspeech and a trained wavenet model.
optional arguments:
optional arguments:
-h, --help show this help message and exit
-h, --help show this help message and exit
--config CONFIG path of the config file.
--config CONFIG path of the config file.
--device DEVICE device to use.
--device DEVICE device to use.
--output OUTPUT path to save student.
--output OUTPUT path to save student.
--data DATA path of LJspeech dataset.
--data DATA path of LJspeech dataset.
--resume RESUME checkpoint to load from.
--resume RESUME checkpoint to load from.
--conditioner CONDITIONER
--wavenet WAVENET wavenet checkpoint to use.
conditioner checkpoint to use.
--teacher TEACHER teacher checkpoint to use.
```
```
1.`--config` is the configuration file to use. The provided configurations can be used directly. And you can change some values in the configuration file and train the model with a different config.
1.`--config` is the configuration file to use. The provided configurations can be used directly. And you can change some values in the configuration file and train the model with a different config.
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@@ -57,8 +54,8 @@ optional arguments:
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@@ -57,8 +54,8 @@ optional arguments:
```
```
5.`--device` is the device (gpu id) to use for training. `-1` means CPU.
5.`--device` is the device (gpu id) to use for training. `-1` means CPU.
6.`--conditioner` is the path of the checkpoint to load for the `conditioner` part of clarinet. if you do not specify `--resume`, then this must be provided.
6.`--wavenet` is the path of the wavenet checkpoint to load. if you do not specify `--resume`, then this must be provided.
7.`--teacher` is the path of the checkpoint to load for the `teacher` part of clarinet. if you do not specify `--resume`, then this must be provided.
Before you start training a clarinet model, you should have trained a wavenet model with single gaussian as output distribution. Make sure the config for teacher matches that for the trained model.
Before you start training a clarinet model, you should have trained a wavenet model with single gaussian as output distribution. Make sure the config for teacher matches that for the trained model.
