This guide provides step-by-step instructions on executing FedOps Silo, a Federated Learning Lifecycle Management Operations framework.

- Baseline
   - client_main.py
   - client_manager_main.py
   - server_main.py
   - models.py
   - data_preparation.py
   - requirementst.txt (server requirement)
   - conf
      -  config.yaml

1. Start by fork the FedOps-Silo.

2. Customize the FedOps example code.

   • In accordance with the baseline form, write the code with reference to the example and store it in the your own git remote storage.

   • Data & Model:

     • Prepare your data in data_preparation.py and define your model in models.py.
     • Enter your data and model in conf/config.yaml

   • Client:

     • Configure settings in conf/config.yaml for task ID, data, and WandB information.
     • Implement data_preparation.py for data handling.
     • Build models.py for local model specifications.
     • Register data and model, and run the client using client_main.py.

   • Server:

     • Configure settings in conf/config.yaml for FL/Aggregation hyperparameters and data information.
     • Implement models.py to initialize the global model.
     • Register data (for evaluating the global model) and initialize the global model in server_main.py.
       
       

3. Create FL task on FedOps web interface.

   • Use the FedOps web interface to create your FL task.
   • Specify the Git repository address for your FL server code.
   • Refer FedOps Silo Guide
     
     

4. Run the clients.

   • Run client_main.py and client_manager_main.py
   • Or choose either Docker or shell(localhost) to run the clients.
     
     

5. Initiate the FL task.

   • Select the desired clients on the FedOps web interface and initiate the FL task by clicking the "FL start" button.
     
     

6. Monitor and manage the FL task

   • Monitor the performance of local and global models, and manage/download the global model as the FL task administrator through the FedOps web interface.
     
     

7. Monitor data and local model performance

   • Monitor the health of data and local model performance as the device administrator through the designated WandB.
     
     

For any questions or issues, please contact the FedOps support team at [email protected]