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 a
tff.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
, maps
dataset_computation
over these values, and proceeds with the body of
computation_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.
Args |
dataset_computation
|
An instance of tff.Computation which accepts some
parameter and returns an element of tff.SequenceType .
|
computation_body
|
An instance of tff.Computation that accepts exactly one
federated dataset, IE, element of type {B*}@CLIENTS , where B is
equivalent to the return type of dataset_computation .
|
Raises |
TypeError
|
If the arguments are of the wrong types, their TFF type
signatures are incompatible with the specification of this function, or if
computation_body declares more than one sequence parameter matching the
expected dataset type.
|
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Last updated 2024-09-20 UTC.
[null,null,["Last updated 2024-09-20 UTC."],[],[],null,["# tff.simulation.compose_dataset_computation_with_computation\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/federated/blob/v0.87.0 Version 2.0, January 2004 Licensed under the Apache License, Version 2.0 (the) |\n\nBuilds a new [`tff.Computation`](../../tff/Computation) which constructs datasets on clients. \n\n tff.simulation.compose_dataset_computation_with_computation(\n dataset_computation: ../../tff/Computation,\n computation_body: ../../tff/Computation\n ) -\u003e ../../tff/Computation\n\nGiven a [`tff.Computation`](../../tff/Computation) that returns a [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset), and a\n[`tff.Computation`](../../tff/Computation) where exactly one of the arguments is a dataset placed on\nclients of the same type as returned by the [`tff.Computation`](../../tff/Computation), this function\nwill construct a new [`tff.Computation`](../../tff/Computation) that accepts a federated set of values\nof the same type as the parameter of the `dataset_computation`, maps\n`dataset_computation` over these values, and proceeds with the body of\n`computation_body`.\n\nFor example, if the type signature of `dataset_computation` is: \n\n (T -\u003e U*)\n\nand the type signature of `computation_body` is: \n\n ({U*}@CLIENTS -\u003e V)\n\nthen the returned `computation_body` type signature will be: \n\n ({T}@CLIENTS -\u003e V)\n\nThis functionality is useful in several settings:\n\n- 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.\n- 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.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `dataset_computation` | An instance of [`tff.Computation`](../../tff/Computation) which accepts some parameter and returns an element of [`tff.SequenceType`](../../tff/types/SequenceType). |\n| `computation_body` | An instance of [`tff.Computation`](../../tff/Computation) that accepts exactly one federated dataset, IE, element of type `{B*}@CLIENTS`, where `B` is equivalent to the return type of `dataset_computation`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A new [`tff.Computation`](../../tff/Computation) satisfying the specification above. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `TypeError` | If the arguments are of the wrong types, their TFF type signatures are incompatible with the specification of this function, or if `computation_body` declares more than one sequence parameter matching the expected dataset type. |\n\n\u003cbr /\u003e"]]