Federated learning system for learning MRI Images classifer

This project was created for learning MRI images classifier using the Federated Learning method (McMahan B., et al., 2016).

The project structure consists of two following folders:

distributed_federated_system - contains the implemented federated system, which can be deployed and run on multiple nodes.
experimtents - includes federated learning experiments using differently distributed data between clients

How to run the federated system?

In order to run the federated system on multiple different nodes, please, take the following steps:

Move every single envoy_# and director (aggregator) + workspace folders to separate nodes and install required packages using pip install -r requirements.txt
For every envoy_# download its corresponding data from here and extract all files to the according envoy's data folder.
On aggregator node:
- Set listen_host and listen_port parameters in director.yaml
- Open director folder in cmd or bash and run the following command to start the director:
  
  fx director start --disable-tls -c director_config.yaml
On envoys nodes:
- Open envoy_# folder in cmd or bash and run the following command to start the envoy:
  
  fx envoy start -n ${ENVOY_NAME} --disable-tls --envoy-config-path envoy_config.yaml -dh ${AGGREGATOR_FQDN} -dp ${AGGREGATOR_PORT}
Open experiment-manager.ipynb in Jupyter Notebook and run all of its cells.