提交 1dcb490d 编辑于 作者: Krzysztof Ostrowski's avatar Krzysztof Ostrowski 提交者: tensorflow-copybara
浏览文件

Top-level introductory paragraph for multi-framework documentation in OSS.

PiperOrigin-RevId: 347653240
上级 91f0a85d
package(default_visibility = ["//visibility:private"])
licenses(["notice"])
This directory contains experimental code that is being incubated. Do not depend
on this code from other parts of TFF, as it can change at any time. All code
included here should retain private visibility while in the incubation stage.
# Multi-Framework Support in TensorFlow Federated
TensorFlow Federated (TFF) has been designed to support a broad range of
federated computations, expressed through a combination of TFF's federated
operators that model distributed communication, and local processing logic.
Currently local processing logic can be expressed using TensorFlow APIs (via
`@tff.tf_computation`) at the frontend, and is executed via the TensorFlow
runtime at the backend. However, we aim to support multiple other
(non-TensorFlow) frontend and backend frameworks for local computations,
including non-ML frameworks (e.g., for logic expressed in SQL or general-purpose
programming languages).
In this section, we'll include information on:
* Mechanisms that TFF provides to support alternative frameworks, and how you
can add support for your preferred type of frontend or backend to TFF.
* Experimental implementations of support for non-TensorFlow frameworks, with
examples.
* Tentative future roadmap for graduating these capabilities beyond the
experimental status.
Supports Markdown
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册