tff.simulation.compose_dataset_computation_with_computation  |  TensorFlow Federated (original) (raw)

tff.simulation.compose_dataset_computation_with_computation

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Builds a new tff.Computation which constructs datasets on clients.

tff.simulation.compose_dataset_computation_with_computation(
    dataset_computation: tff.Computation,
    computation_body: tff.Computation
) -> tff.Computation

Given a tff.Computation that returns a tf.data.Dataset, and atff.Computation where exactly one of the arguments is a dataset placed on clients of the same type as returned by the tff.Computation, this function will construct a new tff.Computation that accepts a federated set of values of the same type as the parameter of the dataset_computation, mapsdataset_computation over these values, and proceeds with the body ofcomputation_body.

For example, if the type signature of dataset_computation is:

(T -> U*)

and the type signature of computation_body is:

({U*}@CLIENTS -> V)

then the returned computation_body type signature will be:

({T}@CLIENTS -> V)

This functionality is useful in several settings:

• We may want to push some dataset preprocessing to happen on the clients, as opposed to preprocessing happening on the TFF simultation controller. This may be necessary, e.g., in the case that we want to shuffle client examples.
• We may want to construct the entire dataset on the clients, given a client id. This may be useful in order to speed up distributed simulations, in order to remove a linear cost incurred in constructing and serializing the datasets on the controller.