/ORU-Titan-example

Example script to run a job in the ORU Titan server

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

ORU-Titan-example

Example notebook to run a trainning job in the ORU Titan server, using the GPUs and exporting the model to an S3 bucket.

  1. Login in the url https://ood.orca.oru.edu/pun/sys/dashboard with your account sil_username@titan.orca.oru.edu and password (for example aquintero@titan.orca.oru.edu)
  2. Go to interactive apps > Jupyter Notebbok Notebook
  3. Launch a session with Partition gpu and some Number of hours
  4. git clone this repo
  5. Create a virtual env and register a kernel
  6. python -m venv venv
  7. source venv/bin/activate
  8. pip install -r requirements
  9. python -m ipykernel install --user --name=myenvkernel --display-name="venv"
  10. Open the TTS_train notebook with the venv kernel. The end of the notebbok saves a checkpoint of the model.
  11. The Export to S3 notebbok shows how to export this checkpoint to an S3 bucket in the IDX-AI AWS account. You will need a .env file as:

AWS_ACCESS_KEY_ID=***

AWS_SECRET_ACCESS_KEY=***

The TTS_train examlpe is a modified copy of https://tts.readthedocs.io/en/latest/tutorial_for_nervous_beginners.html

Notice that the data and model locations .ljspeech and tts_train_dir are excluded in the .gitignore file.