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Merge pull request #297 from GrzegorzKarchNV/tacotron2-readme-update

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updated tacotron2 trtis readme
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PyTorch/SpeechSynthesis/Tacotron2/notebooks/trtis/README.md
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@ -19,7 +19,7 @@ below to learn how to train, export --- or simply download the pretrained models
You can either download the pretrained checkpoints or train the models yourself.
#### Download pretrained checkpoints.
#### (Option 1) Download pretrained checkpoints.
If you want to use a pretrained checkpoints, download them from [NGC](https://ngc.nvidia.com/catalog/models):
@ -27,7 +27,7 @@ If you want to use a pretrained checkpoints, download them from [NGC](https://ng
- [WaveGlow checkpoint](https://ngc.nvidia.com/models/nvidia:waveglow256pyt_fp16)
#### Train Tacotron 2 and WaveGlow models.
#### (Option 2) Train Tacotron 2 and WaveGlow models.
In order to train the models, follow the QuickStart section in the `Tacotron2/README.md`
file by executing points 1-5. You have to train WaveGlow in a different way than described there. Use
@ -52,25 +52,25 @@ python export_tacotron2_ts_config.py --amp-run
```
This will export the folder structure of the TRTIS repository and the config file of Tacotron 2.
By default, it will be found in the `trtis_repo/tacotron` folder.
By default, it will be found in the `trtis_repo/tacotron2` folder.
Now there are two ways to proceed.
#### Download the Tacotron 2 TorchScript model.
#### (Option 1) Download the Tacotron 2 TorchScript model.
Download the Tacotron 2 TorchScript model from:
- [Tacotron2 TorchScript](https://ngc.nvidia.com/models/nvidia:tacotron2pyt_jit_fp16)
Move the downloaded model to `trtis_repo/tacotron2/1/model.pt`
#### Export the Tacotron 2 model using TorchScript.
#### (Option 2) Export the Tacotron 2 model using TorchScript.
To export the Tacotron 2 model using TorchScript, type:
```bash
python export_tacotron2_ts.py --tacotron2 <tacotron2_checkpoint> -o trtis_repo/tacotron2/1/model.pt --amp-run
```
This will save the model as ``trtis_repo/tacotron/1/model.pt``.
This will save the model as ``trtis_repo/tacotron2/1/model.pt``.
### Setup WaveGlow TRT engine.
@ -86,14 +86,14 @@ By default, it will be found in the `trtis_repo/waveglow` folder.
There are two ways to proceed.
#### Download the WaveGlow TRT engine.
#### (Option 1) Download the WaveGlow TRT engine.
Download the WaveGlow TRT engine from:
- [WaveGlow TRT engine](https://ngc.nvidia.com/models/nvidia:waveglow256pyt_trt_fp16)
Move the downloaded model to `trtis_repo/waveglow/1/model.plan`
#### Export the WaveGlow model to TRT.
#### (Option 2) Export the WaveGlow model to TRT.
Before exporting the model, you need to install onnx-tensorrt by typing:
```bash