tff.simulation.baselines.ClientSpec

Note: This API is new and only available via pip install tensorflow-federated-nightly.

Contains information for configuring clients within a training task.

tff.simulation.baselines.ClientSpec(
    num_epochs, batch_size,
    max_elements=attr_dict['max_elements'].default,
    shuffle_buffer_size=attr_dict['shuffle_buffer_size'].default
)

Attributes
num_epochs	An integer representing the number of passes each client performs over its entire local dataset.
batch_size	An integer representing the batch size used when iterating over client datasets.
max_elements	An optional positive integer governing the maximum number of examples used by each client. By default, this is set to None in which case clients use their full dataset.
shuffle_buffer_size	An optional positive integer specifying the shuffle buffer size to use. If set to None, a default value suitable for the task's dataset will be used. If set to 1, no shuffling occurs.