feat(baselines) Add FedRep Baseline (#3790)

Co-authored-by: jafermarq <[email protected]>
Co-authored-by: Adam Narozniak <[email protected]>

README.md

@@ -102,6 +102,7 @@ Flower Baselines is a collection of community-contributed projects that reproduc
 - [FedNova](https://github.com/adap/flower/tree/main/baselines/fednova)
 - [HeteroFL](https://github.com/adap/flower/tree/main/baselines/heterofl)
 - [FedAvgM](https://github.com/adap/flower/tree/main/baselines/fedavgm)
+- [FedRep](https://github.com/adap/flower/tree/main/baselines/fedrep)
 - [FedStar](https://github.com/adap/flower/tree/main/baselines/fedstar)
 - [FedWav2vec2](https://github.com/adap/flower/tree/main/baselines/fedwav2vec2)
 - [FjORD](https://github.com/adap/flower/tree/main/baselines/fjord)

baselines/fedrep/.gitignore

@@ -0,0 +1,5 @@
+# generated files
+outputs/
+client_states/
+datasets/
+models/

baselines/fedrep/LICENSE

@@ -0,0 +1,202 @@
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

baselines/fedrep/README.md

@@ -0,0 +1,126 @@
+---
+title: Exploiting Shared Representations for Personalized Federated Learning
+url: http://arxiv.org/abs/2102.07078
+labels: [image classification, label heterogeneity, personalized federated learning]
+dataset: [CIFAR-10, CIFAR-100]
+---
+
+# Exploiting Shared Representations for Personalized Federated Learning
+
+**Paper:** [arxiv.org/abs/2102.07078](http://arxiv.org/abs/2102.07078)
+
+**Authors:** Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
+
+**Abstract:** Deep neural networks have shown the ability to extract universal feature representations from data such as images and text that have been useful for a variety of learning tasks. However, the fruits of representation learning have yet to be fully-realized in federated settings. Although data in federated settings is often non-i.i.d. across clients, the success of centralized deep learning suggests that data often shares a global feature representation, while the statistical heterogeneity across clients or tasks is concentrated in the labels. Based on this intuition, we propose a novel federated learning framework and algorithm for learning a shared data representation across clients and unique local heads for each client. Our algorithm harnesses the distributed computational power across clients to perform many local-updates with respect to the low-dimensional local parameters for every update of the representation. We prove that this method obtains linear convergence to the ground-truth representation with near-optimal sample complexity in a linear setting, demonstrating that it can efficiently reduce the problem dimension for each client. This result is of interest beyond federated learning to a broad class of problems in which we aim to learn a shared low-dimensional representation among data distributions, for example in meta-learning and multi-task learning. Further, extensive experimental results show the empirical improvement of our method over alternative personalized federated learning approaches in federated environments with heterogeneous data.
+
+
+## About this baseline
+
+**What’s implemented:** The code in this directory replicates the experiments in _Exploiting Shared Representations for Personalized Federated Learning_ (Liam Collins et al., 2021) for CIFAR10 and CIFAR-100 datasets, which proposed the `FedRep` model. Specifically, it replicates the results of CIFAR-10 (`(100, 2), (100, 5)`) and CIFAR-100 (`(100, 5), (100, 20)`) found in table 1 in their paper.
+
+**Datasets:** CIFAR-10, CIFAR-100 from `Flower Datasets`.
+
+**Hardware Setup:** WSL2 Ubuntu 22.04 LTS, NVIDIA RTX 3070 Laptop, 32GB RAM, AMD Ryzen 9 5900HX. 
+
+**Contributors:** Jiahao Tan<<[email protected]>>
+
+
+## Experimental Setup
+
+**Task:** Image Classification
+
+**Model:** This directory implements 2 models:
+
+- CNNCifar10 
+- CNNCifar100
+
+These two models are modified from the [official repo](https://github.com/rahulv0205/fedrep_experiments)'s. To be clear that, in the official models, there is no BN layers. However, without BN layer helping, training will definitely collapse.
+
+Please see how models are implemented using a so called model_manager and model_split class since FedRep uses head and base layers in a neural network. These classes are defined in the `models.py` file and thereafter called when building new models in the directory `/implemented_models`. Please, extend and add new models as you wish. 
+
+**Dataset:** CIFAR10, CIFAR-100. CIFAR10/100 will be partitioned based on number of classes for data that each client shall receive e.g. 4 allocated classes could be [1, 3, 5, 9].
+
+**Training Hyperparameters:** The hyperparameters can be found in `conf/base.yaml` file which is the configuration file for the main script. 
+
+| Description           | Default Value                       |
+| --------------------- | ----------------------------------- |
+| `num_clients`         | `100`                               |
+| `num_rounds`          | `100`                               |
+| `num_local_epochs`    | `5`                                 |
+| `num_rep_epochs`      | `1`                                 |
+| `enable_finetune`     | `False`                             |
+| `num_finetune_epochs` | `5`                                 |
+| `use_cuda`            | `true`                              |
+| `specified_device`    | `null`                              |
+| `client resources`    | `{'num_cpus': 2, 'num_gpus': 0.5 }` |
+| `learning_rate`       | `0.01`                              |
+| `batch_size`          | `50`                                |
+| `model_name`          | `cnncifar10`                        |
+| `algorithm`           | `fedrep`                            |
+
+
+## Environment Setup
+
+To construct the Python environment follow these steps:
+
+```bash
+# Set Python 3.10
+pyenv local 3.10.12
+# Tell poetry to use python 3.10
+poetry env use 3.10.12
+
+# Install the base Poetry environment
+poetry install
+
+# Activate the environment
+poetry shell
+```
+
+## Running the Experiments
+
+```
+python -m fedrep.main # this will run using the default settings in the `conf/base.yaml` 
+```
+
+While the config files contain a large number of settings, the ones below are the main ones you'd likely want to modify to .
+```bash
+algorithm: fedavg, fedrep # these are currently supported
+dataset.name: cifar10, cifar100
+dataset.num_classes: 2, 5, 20 (only for CIFAR-100)
+model_name: cnncifar10, cnncifar100
+```
+
+
+## Expected Results
+
+### CIFAR-10 (100, 2)
+
+```
+python -m fedrep.main --config-name cifar10_100_2 algorithm=fedrep 
+python -m fedrep.main --config-name cifar10_100_2 algorithm=fedavg 
+```
+<img src="_static/cifar10_100_2.png" width="400"/> 
+
+### CIFAR-10 (100, 5)
+
+```
+python -m fedrep.main --config-name cifar10_100_5 algorithm=fedrep 
+python -m fedrep.main --config-name cifar10_100_5 algorithm=fedavg 
+```
+<img src="_static/cifar10_100_5.png" width="400"/> 
+
+### CIFAR-100 (100, 5)
+
+```
+python -m fedrep.main --config-name cifar100_100_5 algorithm=fedrep 
+python -m fedrep.main --config-name cifar100_100_5 algorithm=fedavg 
+```
+<img src="_static/cifar100_100_5.png" width="400"/> 
+
+### CIFAR-100 (100, 20)
+
+```
+python -m fedrep.main --config-name cifar100_100_20 algorithm=fedrep 
+python -m fedrep.main --config-name cifar100_100_20 algorithm=fedavg 
+```
+<img src="_static/cifar100_100_20.png" width="400"/> 

baselines/fedrep/fedrep/__init__.py

@@ -0,0 +1 @@
+"""Template baseline package."""