As part of this repo, you will learn to build a custom GAN architecture and train the model using Amazon SageMaker.
- Access to Amazon SageMaker
Using a ml.c5.4xlarge, the entire exercise take 3-4 hrs to run. Please see the Amazon SageMaker pricing for details.
First we create the Amazon SageMaker notebook instance.
Navigate to Amazon SageMaker using the link: https://console.aws.amazon.com/sagemaker/home?region=us-east-1#/dashboard
Click Notebook instances from the left navigation bar
Select Create notebook instance
Within the notebook instance creation form, select "c5.4xlarge" for Notebook instance type
Set the following for Permissions and encryption:
- IAM role: Use an existing role or create a new role
- Root access: Enable
- Encryption key: No Custom Encryption
Set the following for Git repositories:
- Repository: Clone a public Git repository to this notebook instance only
- Git repository URL: https://github.com/aws-samples/aws-deepcomposer-samples
Click Open Jupyter
Click gan folder, then click GAN.ipynb
You will likely be prompted to select kernel. Choose the drop down and select conda_python3 as the kernel
This notebook contains instructions and code to create a custom GAN model from scratch. Follow the notebook content and run all cells to the end.
To run the code cells, choose the code cell you want to run and click Run
If the kernel has an empty circle, it means it is free and ready to execute the code
If the kernel has a filled circle, it means it is busy. Wait for it to become free before you execute the next line of code.
Congratulations on building a custom GAN model from scratch!
Now try using your model to create compositions based on your custom MIDI input.
Important: Remember to stop your Amazon SageMaker instances after you're done to avoid extra charges
