Is your feature request related to a problem? Please describe.
As a user of this platform I would like to define Airflow DAGs for the execution of training workflows.
Describe the solution you'd like
Definition of an Airflow DAG to execute training both on the local host that this repository is located and also on a remote host.
We would like to enable to training and caching of trained models on local and remote hosts. This feature would likely allow us to define variables that allow us to define whether or not this will be a local training job and if not what host we would like to execute it on along with if that host has a GPU available for use.
Model caching can also follow the same methods outlined in the feature request outlined in #24
Describe alternatives you've considered
Manual training using bash to execute containerized training
Is your feature request related to a problem? Please describe. As a user of this platform I would like to define Airflow DAGs for the execution of training workflows.
Describe the solution you'd like Definition of an Airflow DAG to execute training both on the local host that this repository is located and also on a remote host.
We would like to enable to training and caching of trained models on local and remote hosts. This feature would likely allow us to define variables that allow us to define whether or not this will be a local training job and if not what host we would like to execute it on along with if that host has a GPU available for use.
Model caching can also follow the same methods outlined in the feature request outlined in #24
Describe alternatives you've considered Manual training using bash to execute containerized training
Additional context