Class FromTensorSlicesClientData
ClientData based on tf.data.Dataset.from_tensor_slices.
Inherits From: ClientData
Defined in
simulation/from_tensor_slices_client_data.py.
__init__
__init__(tensor_slices_dict)
Constructs the object from a dictionary of client data.
NOTE: All clients are required to have non-empty data.
Args:
tensor_slices_dict: A dictionary keyed by client_id, where values are structures suitable for passing totf.data.Dataset.from_tensor_slices.
Raises:
ValueError: If a client with no data is found.
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
tf.data.Dataset.output_shapes properties.
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
tf.data.Dataset.output_types properties.
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
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
create_tf_dataset_from_all_clients()
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.
Returns:
A tf.data.Dataset object.