fluke CLI¶
The package provides a command line interface (CLI) to run federated learning experiments.
The two main commands are fluke and fluke-get.
fluke¶
The fluke command is used to run federated learning experiments. It requires two configuration files:
EXP_CONFIG_FILE: the experiment configuration file (independent from the algorithm);ALG_CONFIG_FILE: the algorithm configuration file.
Hint
For more information on the configuration files, see Configuration.
The fluke command allows to run three different types of experiments:
Centralized learning: (
centralized) the server trains a global model on the entire dataset.Federated learning: (
federation) run a centralized federated learning experiment according to the configurations.Clients only: (
clients-only) train each client individually on its own data.
The structure of the command is the following:
fluke --config <EXP_CONFIG_FILE> <experiment_type> <ALG_CONFIG_FILE> [OPTIONS]
where:
<EXP_CONFIG_FILE>is the path to the experiment configuration file;<ALG_CONFIG_FILE>is the path to the algorithm configuration file.
Centralized learning¶
To run a centralized learning experiment, use the following command:
fluke --config <EXP_CONFIG_FILE> centralized <ALG_CONFIG_FILE> [--epochs=<EPOCHS>]
where <EPOCHS> is the number of epochs to train the model (default is 0). If not specified (=0), the number of epochs are calculated according to the algorithm configuration. Specifically, EPOCHS = n_rounds * eligible_perc.
Since the learning is centralized, some of the parameters in the configuration file are ignored (i.e., the parameters related to the data distribution). The set up of for the learning (e.g., batch size, optimizer, etc.) is taken from the client hyper-parameters in the algorithm configuration file.
Federated learning¶
To run a the federated learning algorithm, use the following command:
fluke --config <EXP_CONFIG_FILE> federation <ALG_CONFIG_FILE> [OPTIONS]
where [OPTIONS] are the following:
--save=<PATH>:<PATH>must be the path to a directory where the state of the experiment will be saved. If not specified, the state is not saved.--resume=<PATH>:<PATH>must be the path to a directory where the state of a previous experiment is saved. If specified, the experiment will resume from the saved state. If not specified, the experiment starts from scratch.--seed=<SEED>:<SEED>is the seed for the random number generator, it overrides the seed in the configuration file. If not specified, the seed in the configuration file is used.
Clients only¶
Performing the training on the clients only is useful to evaluate the performance of the algorithm on the clients’ data without the federation. To run a the learning only on the clients, use the following command:
fluke --config <EXP_CONFIG_FILE> clients-only <ALG_CONFIG_FILE> [--epochs=<EPOCHS>]
where <EPOCHS> is the number of epochs to train the model (default is 0). If not specified (=0), the number of epochs are calculated according to the algorithm configuration. Specifically, EPOCHS = n_rounds * eligible_perc * local_epochs, but in any case no less than 100.
The hyper-parameters related to the server are ignored in this case.
Important
When running in clients-only mode, the logging on services like wandb happens at the end of training of all clients.
fluke-get¶
The fluke-get command is useful to get a configuration file template for the specified algorithm or for the experiment.
It directly downloads the template from the repository and saves it in the config directory (if it does not exist, it creates it).
fluke-get <config file name>
where <config file name> is the name of the configuration file to download (without the .yaml extension).
You can also ask for the list of available algorithms or experiments.
fluke-get list