def _client_one(): return intrinsics.federated_eval( tensorflow_computation.tf_computation( lambda: tf.constant(1, tf.int32)), placements.CLIENTS)
def get_bounds(state): del state # Unused. return intrinsics.federated_eval(bounds_fn, placements.SERVER)
def init_fn(): return intrinsics.federated_eval(initialize, placements.SERVER)
def _create_zero_model_on_server(): return intrinsics.federated_eval(_create_zero_model, placements.SERVER)
def init_fn(): return intrinsics.federated_eval( computations.tf_computation( lambda: tf.zeros(shape=[], dtype=tf.float32)), placements.SERVER)
def initialize_fn(): return intrinsics.federated_eval( tensorflow_computation.tf_computation()( lambda: tf.constant([], dtype=tf.string)), placements.SERVER)
def comp(): return_five = computations.tf_computation(lambda: 5) return intrinsics.federated_eval(return_five, placements.CLIENTS)
def initialize_fn(): return intrinsics.federated_eval( tf_computation(lambda: tf.constant(0.0, tf.float32)), placements.SERVER)
def comp(): return_five = computations.tf_computation(lambda: 5) five_at_server = intrinsics.federated_eval(return_five, placements.SERVER) six_at_server = intrinsics.federated_map(add_one, five_at_server) return six_at_server
def initial_state_comp(): return intrinsics.federated_eval(initial_state_fn, placements.SERVER)
def init(): return intrinsics.federated_eval(make_zero, placements.SERVER)
def init(): return intrinsics.federated_eval(create_dataset, placements.CLIENTS)
def comp(): client_keys = intrinsics.federated_eval(get_keys, placements.CLIENTS) max_key = intrinsics.federated_value(5, placements.SERVER) server_val = intrinsics.federated_value('db', placements.SERVER) return intrinsics.federated_select(client_keys, max_key, server_val, select_fn)