tff.simulation.datasets.shakespeare.load_data

Loads the federated Shakespeare dataset.

tff.simulation.datasets.shakespeare.load_data(
    cache_dir: Optional[str] = None
) -> tuple[client_data.ClientData, client_data.ClientData]

Used in the notebooks

Used in the tutorials
Federated Learning for Text Generation Private Heavy Hitters

Downloads and caches the dataset locally. If previously downloaded, tries to load the dataset from cache.

This dataset is derived from the Leaf repository (https://github.com/TalwalkarLab/leaf) pre-processing on the works of Shakespeare, which is published in "LEAF: A Benchmark for Federated Settings" https://arxiv.org/abs/1812.01097

The data set consists of 715 users (characters of Shakespeare plays), where each example corresponds to a contiguous set of lines spoken by the character in a given play.

Data set sizes:

• train: 16,068 examples
• test: 2,356 examples

Rather than holding out specific users, each user's examples are split across train and test so that all users have at least one example in train and one example in test. Characters that had less than 2 examples are excluded from the data set.

The tf.data.Datasets returned by tff.simulation.datasets.ClientData.create_tf_dataset_for_client will yield collections.OrderedDict objects at each iteration, with the following keys and values:

• 'snippets': a tf.Tensor with dtype=tf.string, the snippet of contiguous text.

Args
cache_dir	(Optional) directory to cache the downloaded file. If None, caches in Keras' default cache directory.

Returns
Tuple of (train, test) where the tuple elements are tff.simulation.datasets.ClientData objects.