Command line interface

A command line interface (CLI) is provided for running multiple federated learning experiments. The only argument is the path to the configuration file (in YAML format) for the experiments. Examples of configuration files can be found in the example-configs directory. For example, in the all-alg-fedprox-femnist.yml file, we have

[example-configs/all-alg-fedprox-femnist.yml]

# Example config file for fl-sim command line interface

strategy:
matrix:
    algorithm:
    - Ditto
    - FedDR
    - FedAvg
    - FedAdam
    - FedProx
    - FedPD
    - FedSplit
    - IFCA
    - pFedMac
    - pFedMe
    - ProxSkip
    - SCAFFOLD
    clients_sample_ratio:
    - 0.1
    - 0.3
    - 0.7
    - 1.0

algorithm:
name: ${{ matrix.algorithm }}
server:
    num_clients: null
    clients_sample_ratio: ${{ matrix.clients_sample_ratio }}
    num_iters: 100
    p: 0.3  # for FedPD, ProxSkip
    lr: 0.03  # for SCAFFOLD
    num_clusters: 10  # for IFCA
    log_dir: all-alg-fedprox-femnist
client:
    lr: 0.03
    num_epochs: 10
    batch_size: null  # null for default batch size
    scheduler:
    name: step  # StepLR
    step_size: 1
    gamma: 0.99
dataset:
name: FedProxFEMNIST
datadir: null  # default dir
transform: none  # none for static transform (only normalization, no augmentation)
model:
name: cnn_femmist_tiny
seed: 0

The strategy (optional) section specifies the grid search strategy; the algorithm section specifies the hyperparameters of the federated learning algorithm: name is the name of the algorithm, server specifies the hyperparameters of the server, and client specifies the hyperparameters of the client; the dataset section specifies the dataset, and the model section specifies the named model (ref. the candidate_models property of the dataset classes) to be used.