提交 ae79a8bd 编辑于 作者: Zheng Xu's avatar Zheng Xu 提交者: tensorflow-copybara
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Reorganize TFF tutorials to move tutorials from "advanced tutorial" to "custom computation".

PiperOrigin-RevId: 391269837
上级 aa1bd1f0
......@@ -28,6 +28,12 @@ upper_tabs:
path: /federated/tutorials/building_your_own_federated_learning_algorithm
- title: "Custom Federated Algorithm with TFF Optimizers"
path: /federated/tutorials/custom_federated_algorithm_with_tff_optimizers
- title: "Custom Federated Algorithms Part 1 - Introduction to the Federated Core"
path: /federated/tutorials/custom_federated_algorithms_1
- title: "Custom Federated Algorithms Part 2 - Implementing Federated Averaging"
path: /federated/tutorials/custom_federated_algorithms_2
- title: "Implementing Custom Aggregators"
path: /federated/tutorials/custom_aggregators
- heading: Simulation Runtime
- title: "High-performance Simulations with TFF"
......@@ -38,8 +44,6 @@ upper_tabs:
path: /federated/tutorials/working_with_client_data
- heading: Advanced tutorials
- title: "Implementing Custom Aggregators"
path: /federated/tutorials/custom_aggregators
- title: "Random Noise Generation"
path: /federated/tutorials/random_noise_generation
- title: "Sending Different Data To Particular Clients With tff.federated_select"
......@@ -50,10 +54,6 @@ upper_tabs:
path: /federated/tutorials/tff_for_federated_learning_research_compression
- title: "Federated Learning with Differential Privacy in TFF"
path: /federated/tutorials/federated_learning_with_differential_privacy
- title: "Custom Federated Algorithms Part 1 - Introduction to the Federated Core"
path: /federated/tutorials/custom_federated_algorithms_1
- title: "Custom Federated Algorithms Part 2 - Implementing Federated Averaging"
path: /federated/tutorials/custom_federated_algorithms_2
- title: "Experimental support for JAX in TFF"
path: /federated/experimental/tutorials/jax_support
......
......@@ -19,7 +19,7 @@ documentation can be found in the [TFF guides](../get_started.md).
specialized aggregation routines offering robustness, differential privacy,
compression, and more.
**Getting started writing custom federated computations**
**Writing custom federated computations**
* [Building Your Own Federated Learning Algorithm](building_your_own_federated_learning_algorithm.ipynb)
shows how to use the TFF Core APIs to implement federated learning
......@@ -27,6 +27,14 @@ documentation can be found in the [TFF guides](../get_started.md).
* [Custom Federated Algorithm with TFF Optimizers](custom_federated_algorithm_with_tff_optimizers.ipynb)
shows how to use `tff.learning.optimizers` to build a custom iterative
process for Federated Averaging.
* [Custom Federated Algorithms, Part 1: Introduction to the Federated Core](custom_federated_algorithms_1.ipynb)
and
[Part 2: Implementing Federated Averaging](custom_federated_algorithms_2.ipynb)
introduce the key concepts and interfaces offered by the Federated Core API
(FC API).
* [Implementing Custom Aggregations](custom_aggregators.ipynb) explains the
design principles behind the `tff.aggregators` module and best practices for
implementing custom aggregation of values from clients to server.
**Simulation best practices**
......@@ -43,10 +51,6 @@ documentation can be found in the [TFF guides](../get_started.md).
**Intermediate and advanced tutorials**
* [Implementing Custom Aggregations](custom_aggregators.ipynb) explains the
design principles behind the `tff.aggregators` module and best practices for
implementing custom aggregation of values from clients to server.
* [Random noise generation](random_noise_generation.ipynb) points out some
subtlities with using randomness in decentralized computations, and proposes
best practices and recommend patterns.
......@@ -70,12 +74,6 @@ documentation can be found in the [TFF guides](../get_started.md).
demonstrates how to use TFF to train models with user-level differential
privacy.
* [Custom Federated Algorithms, Part 1: Introduction to the Federated Core](custom_federated_algorithms_1.ipynb)
and
[Part 2: Implementing Federated Averaging](custom_federated_algorithms_2.ipynb)
introduce the key concepts and interfaces offered by the Federated Core API
(FC API).
* [Experimental support for JAX in TFF](../experimental/tutorials/jax_support.ipynb)
shows how [JAX](https://github.com/google/jax) computations can be used in
TFF, demonstrating how TFF is designed to be able to interoperate with other
......
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