How its Work
- Input melody captured on the AWS DeepComposer console
- The console makes a backend call to AWS DeepComposer APIs that triggers an execution Lambda.
- Book-keeping is recorded in Dynamo DB.
- The execution Lambda performs an inference query to SageMaker which hosts the model and the training inference container.
- The query is run on the Generative AI model.
- The model generates a composition.
- The generated composition is returned.
- The user can hear the composition in the console.
- The user can share the composition with SoundCloud.
- User launches a training job from the AWS DeepComposer console by selecting hyperparameters and data set filtering tags
- The backend consists of an API Layer (API gateway and lambda) write request to DynamoDB
- Triggers a lambda function that starts the training workflow
- It then uses AWS Step Functions to launch the training job on Amazon SageMaker
- Status is continually monitored and updated to DynamoDB
- The console continues to poll the backend for the status of the training job and update the results live so users can see how the model is learning