TF 2.0 is out! Get hands-on practice at TF World, Oct 28-31. Use code TF20 for 20% off select passes. Register now

tff.simulation.HDF5ClientData

View source

Class HDF5ClientData

A tff.simulation.ClientData backed by an HDF5 file.

Inherits From: ClientData

This class expects that the HDF5 file has a top-level group examples which contains further subgroups, one per user, named by the user ID.

The tf.data.Dataset returned by HDF5ClientData.create_tf_dataset_for_client(client_id) yields tuples from zipping all datasets that were found at /data/client_id group, in a similar fashion to tf.data.Dataset.from_tensor_slices().

__init__

View source

__init__(hdf5_filepath)

Constructs a tff.simulation.ClientData object.

Args:

  • hdf5_filepath: String path to the hdf5 file.

Properties

client_ids

The list of string identifiers for clients in this dataset.

output_shapes

Returns the shape of each component of an element of the client datasets.

Any tf.data.Dataset constructed by this class is expected to have matching output_shapes properties when accessed via tf.compat.v1.data.get_output_shapes(dataset).

Returns:

A nested structure of tf.TensorShape objects corresponding to each component of an element of the client datasets.

output_types

Returns the type of each component of an element of the client datasets.

Any tf.data.Dataset constructed by this class is expected have matching output_types properties when accessed via tf.compat.v1.data.get_output_types(dataset).

Returns:

A nested structure of tf.DType objects corresponding to each component of an element of the client datasets.

Methods

create_tf_dataset_for_client

View source

create_tf_dataset_for_client(client_id)

Creates a new tf.data.Dataset containing the client training examples.

Args:

  • client_id: The string client_id for the desired client.

Returns:

A tf.data.Dataset object.

create_tf_dataset_from_all_clients

View source

create_tf_dataset_from_all_clients(seed=None)

Creates a new tf.data.Dataset containing all client examples.

NOTE: the returned tf.data.Dataset is not serializable and runnable on other devices, as it uses tf.py_func internally.

Currently, the implementation produces a dataset that contains all examples from a single client in order, and so generally additional shuffling should be performed.

Args:

  • seed: Optional, a seed to determine the order in which clients are processed in the joined dataset.

Returns:

A tf.data.Dataset object.

from_clients_and_fn

View source

from_clients_and_fn(
    cls,
    client_ids,
    create_tf_dataset_for_client_fn
)

Constructs a ClientData based on the given function.

Args:

  • client_ids: A non-empty list of client_ids which are valid inputs to the create_tf_dataset_for_client_fn.
  • create_tf_dataset_for_client_fn: A function that takes a client_id from the above list, and returns a tf.data.Dataset.

Returns:

A ClientData.

preprocess

View source

preprocess(preprocess_fn)

Applies preprocess_fn to each client's data.