Simple Flower Example

Installation

Clone the Repository

git clone https://github.com/waggle-sensor/Simple_Flower_Example.git
cd Simple_Flower_Example

Create a Virtual Environment (Optional)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install Dependencies

pip install torch torchvision flwr datasets numpy

There are two files server.py and client.py.

Configuration

In server.py you can play changing the following options.

strategy = FedAvg(
    fraction_fit=1.0,  # Sample 100% of available clients for training
    fraction_evaluate=0.5,  # Sample 50% of available clients for evaluation
    min_fit_clients=10,  # Minimum number of clients to be sampled for training
    min_evaluate_clients=5,  # Minimum number of clients to be sampled for evaluation
    min_available_clients=10,  # Minimum number of clients that need to connect to the server before training starts
    evaluate_metrics_aggregation_fn=weighted_average,  # Custom metric aggregation function
)

Usage

Running the Server Start the Flower server by running:

python server.py

This will:

• Start the server on 0.0.0.0:8080.
• Use the FedAvg strategy with specified parameters.
• Wait for clients to connect (minimum number specified in the strategy).

Running the Clients

Each client represents a participant in the federated learning process.

python client.py --partition <PARTITION_ID> [--server_address <SERVER_ADDRESS>]

• --partition: (Required) The data partition ID (0-9).
• --server_address: The server address (default is 127.0.0.1:8080).

Example:

python client.py --partition 0

To simulate multiple clients, run the above command in separate terminals with different --partition IDs.