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Recent Releases of openfederatedlearning

openfederatedlearning - v1.9

We are excited to announce the release of OpenFL 1.9! This release brings the following changes.

New Features

  • Scaling to 100s of collaborators: This release comes with several memory and performance improvements when scaling federations horizontally, including extensive testing and benchmarking in distributed environments.
  • Verifiable Datasets & S3 support: Introducing a new framework of utilities for flexible loading of datasets, including optional integrity check verifications. Building on this framework, OpenFL now supports data loading from object storage (S3), illustrated by the histology_s3 workspace template.
  • Aggregator REST API: OpenFL now supports REST as an alternative to gRPC for the communication between the collaborators and the aggregator. The protocol can now be selected in the network settings section of the FL plan.
  • Federated Analytics: experimental support introduced via example workspace templates, with core framework support scheduled for subsequent OpenFL releases.
  • Workflow API Enhancements: Numerous bug fixes to LocalRuntime, and continued progress towards production-readiness of the FederatedRuntime:
    • Fixed an issue that would prevent enabling TLS in distributed environments.
    • Optimized memory usage and introduced gRPC streaming for the FederatedRuntime, enabling experimental federations with models of up to 2GB in size.
    • Removed the legacy Aggregator-Based Workflow, superseded by the FederatedRuntime.

Enhanced Developer Experience

  • TaskRunner API Bootstrapping Utilities: Introducing FL administrator utilities for TaskRunner API:
    • A new fx collaborator ping command to test collaborator/aggregator connectivity without starting any FL tasks or accessing private data
    • A no-op workspace template that can be configured and distributed just for the purposes of establishing and testing connectivity and PKI, in conjunction with the a no-op workspace
  • Saving a native model: In previous versions of OpenFL, the trained models would be saved as a .pbuf file by default. OpenFL 1.9 provides the option to save the model in native format directly (such as .pth), if enabled via the save_native_model flag in the aggregator section of the FL plan.
  • Flower Interoperability: Most of the OpenFL/Flower interop components have been moved from the experimental flower-app-pytorch workspace to the core OpenFL framework, enabling FL developers to run a wide variety of existing Flower experiments on the OpenFL infrastructure.
  • OpenFL Nightly Builds: A comprehensive Product Quality Pipeline now runs on a nightly basis and, upon success, produces an openfl-nightly build.

New Contributors

Thank you and welcome to our 3 first time contributors in OpenFL 1.9: @rahulga1 @scngupta-dsp @tayfunceylan

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.8...v1.9

- Python
Published by psfoley 8 months ago

openfederatedlearning - v1.8

We are excited to announce the release of OpenFL 1.8! This release brings the following changes.

New Features

  • Secure Aggregation: : OpenFL now supports Secure Aggregation, a privacy-preserving algorithm for Federated Learning based on secure multiparty computation (MPC). This ensures that intermediate model updates remain protected from introspection. Secure Aggregation is available via both the Task Runner API and Workflow API.

  • OpenFL & Flower Interoperability: Run FL experiments defined in Flower API as OpenFL federations using the Task Runner API. This integration allows you to leverage Flower's extensive FL algorithms alongside OpenFL’s robust security features, including trusted execution, secure communication, and protection against data exfiltration.

  • Federated Evaluation: Easily transition from model training to evaluation in the Task Runner API without redistributing the FL plan—ideal for large, geo-distributed federations. Federated Evaluation is now also available in the Workflow API for streamlined testing and validation.

Enhanced Developer Experience

  • ML Frameworks Integration:
    • Upgraded PyTorch-based FL workspaces to version 2.4.1.
    • Introduced additional Keras 3 backends, including JAX and PyTorch for broader framework compatibility.
  • Improved Resilience: OpenFL Task Runner API experiments can now recover seamlessly from both Collaborator and Aggregator restarts, ensuring greater stability in distributed environments.

Breaking Changes:

  • Removing Legacy APIs: Removed legacy APIs—the Python Native API and the Interactive API—along with their corresponding examples and documentation.

New Contributors

Thank you and welcome to our 10 first time contributors in OpenFL 1.8: @cloudnoize @bandatarunkumar @nambi21 @yuliasherman @shgandhi @Efrat1 @bsenthilr @situ-s @yarikoptic @lior1-malka

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.7...v1.8

- Python
Published by theakshaypant 11 months ago

openfederatedlearning - v1.7.1

What's Changed

  • [Workflow Interface] Fix for FederatedRuntime bringup in distributed infrastructure Issue #1265

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.7...v1.7.1

- Python
Published by rajithkrishnegowda 12 months ago

openfederatedlearning - v1.7

We are excited to announce the release of OpenFL 1.7! This release brings the following changes.

New Features

  • FederatedRuntime for Workflow API: enables a seamless transition from a local simulation (via LocalRuntime) to a distributed Federated Learning deployment - all orchestrated from a familiar Jupyter notebook environment. Check out the FederatedRuntime 101 Tutorial to try it yourself. The initial version of the FederatedRuntime included in this release is an experimental feature that should be used only in an internal environment. We further recommend that users operate only on artificial or public data that is not considered intellectual property. The experimental tag and restrictions will be removed in future releases of OpenFL.

  • Federated XGBoost: Adding support for XGBoost training in OpenFL via TaskRunner API, illustrated with the Higgs dataset.

  • Callbacks: An abstraction for running user-defined actions in TaskRunner API or Workflow API. Callbacks can be used to perform custom actions at different stages of the Federated Learning process.

Enhanced Developer Experience

  • Streamlining OpenFL APIs: With this release, the OpenFL Team will concentrate on the TaskRunner API and Workflow API. Consequently, the Python Native API and Interactive API have been deprecated and are scheduled for removal in future iterations.

  • Docker packaging improvements: Revised Task Runner API workspace dockerization process, with TEE-ready containers (using Gramine and Intel® Software Guard Extensions). Follow the updated instructions to enhance the privacy and security of your FL experiments.

  • Federated Evaluation via TaskRunner API: OpenFL 1.7 further simplifies the creation of Federated Evaluation experiments via the TaskRunner API (see the example FedEval workspace).

  • Keras 3 support: Upgrading the base TaskRunner classes and example workspaces to Keras 3 for building state-of-the-art FL experiments with TensorFlow (more backends to be included in the upcoming OpenFL releases).

  • Updated Tutorials: This includes fixes to existing tutorial and example code, and migrating a selection of key OpenFL tutorials from deprecated APIs to Workflow API. Check out the updated Tutorials folder.

  • Updated Official Documentation: The OpenFL documentation website has been comprehensively reviewed and reorganized to improve navigation and provide clearer content.

Breaking Changes

  • Removing support for Python 3.8 and 3.9: We are moving to a new policy of 42 month support for historical Python versions - which currently includes Python 3.10-3.12. This policy is in line with Numpy and other popular open source Python packages.

New Contributors

Thank you and welcome to our 5 first time contributors in OpenFL 1.7: @jkk-intel, @gbikkiintel, @vrancurel, @ynonflumintel, @yontyon

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.6...v1.7

- Python
Published by psfoley about 1 year ago

openfederatedlearning - v1.6

We are excited to announce the release of OpenFL 1.6! This release brings the following changes.

New Features and APIs:

  • Federated LLM fine-tuning:

    • Horovod: Use horovod to efficiently train LLMs across multiple private clusters
    • Neuralchat-7b fine-tuning: Learn how to fine-tune neuralchat-7b using the Intel® Extension for Transformers and the workflow interface.

  • Workflow API enhancements: Introducing an experimental Workspace Export feature that can be used to transform a Workflow API-based FL experiment into the TaskRunner API format for running in a distributed deployment. There is also groundwork laid for a future FederatedRuntime implementation for Workflow API, in addition to the currently supported LocalRuntime.

  • Federated Evaluation: Federated evaluation allows for the assessment of ML models in a federated learning system by validating the model's performance locally on decentralized collaborator nodes, and then aggregating these metrics to gauge overall effectiveness, without compromising data privacy and security. FE is now officially supported by OpenFL, including example tutorials on how to use this new feature (via TaskRunner API).

  • Expanded AI Accelerator Support: Intel® Data Center GPU Max Series support via the Intel® Extension for PyTorch, including examples for training on datasets such as MNIST (via Workflow API) and TinyImageNet (via Interactive API)

  • Improved straggler collaborator handling: Improvements and bug fixes to aggregator’s fault-tolerance when collaborators stop responding or drop out of a federation. Introducing a cut-off timer-based policy and enabling other policies to be plugged-in. This capability is particularly relevant for large or geo-distributed federations.

  • fx CLI Improvements: We have separated the CLI commands are separated for creating a collaborator from the certificate request generation, for offering improved control of the participant setup workflow.

Highlighting Community Research

  • Mitigating backdoor attacks in FL - Workflow API example contributed by @perieger (TU Darmstadt) demonstrates how Crowdguard can be used to leverage clients' feedback on individual models, analyze the behavior of neurons in hidden layers, and eliminate poisoned models through an iterative pruning scheme.

Enhanced Documentation:

  • Quickstart Tutorial: An updated TaskRunner API quickstart tutorial makes it easier for newcomers to get up and running with built-in workspaces or custom code.
  • FL Plan Description Documentation: There is now a detailed FL plan description in the to our documentation to help users better understand and configure the federated learning process.

New Contributors

Thank you and welcome to our 30 first time contributors In OpenFL 1.6!

@ptizzza, @grib0ed0v, @joedevon, @akantak, @wangleflex, @fangxiaoran, @danhe1, @bjklemme-intel, @fstrr, @KeertiX, @porteratzo, @amitport, @ashahba, @andreazanetti, @GabrieleRoncolato, @orionsBeltWest, @sbakas, @perieger, @manuelhsantana, @Hmikihiro, @VukW, @aryanxk02, @pboushy, @ParthMandaliya, @yanmxa, @tonywjs, @theakshaypant, @ishaileshpant, @rajithkrishnegowda, @teoparvanov

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.5...v1.6

- Python
Published by psfoley over 1 year ago

openfederatedlearning - v1.5.1

We are excited to announce the release of OpenFL 1.5.1 - our first since moving to LF AI & Data! This release brings the following changes.

Highlights

What's Changed

  • Update Github Python version badge by @grib0ed0v in https://github.com/securefederatedai/openfl/pull/719
  • Fixed workflow interface notebook requirements by @psfoley in https://github.com/securefederatedai/openfl/pull/729
  • Fix CONTINUE_GLOBAL optimizer treatment by @itrushkin in https://github.com/securefederatedai/openfl/pull/711
  • Create MAINTAINERS.md by @ptizzza in https://github.com/securefederatedai/openfl/pull/761
  • Create GOVERNANCE.md by @ptizzza in https://github.com/securefederatedai/openfl/pull/763
  • Create TSC by @ptizzza in https://github.com/securefederatedai/openfl/pull/762
  • Fix flake8 error in local runtime by @psfoley in https://github.com/securefederatedai/openfl/pull/764
  • Q2 2023 Roadmap by @psfoley in https://github.com/securefederatedai/openfl/pull/765
  • Update ROADMAP.md by @joedevon in https://github.com/securefederatedai/openfl/pull/785
  • Updated integrations to GaNDLF by @sarthakpati in https://github.com/securefederatedai/openfl/pull/781
  • Fix Flake8 C419 for Ubuntu CI by @akantak in https://github.com/securefederatedai/openfl/pull/800
  • Fix warnings and issues in docs by @akantak in https://github.com/securefederatedai/openfl/pull/825
  • Add Logo by @psfoley in https://github.com/securefederatedai/openfl/pull/827
  • Change OpenFL documentation font to improve accessibility by @wangleflex in https://github.com/securefederatedai/openfl/pull/809
  • Update unit tests to improve code coverage by @fangxiaoran in https://github.com/securefederatedai/openfl/pull/821
  • Add PyTorch linear regression example by @danhe1 in https://github.com/securefederatedai/openfl/pull/808
  • This prints out the hash of the CSR to disk for both the aggregator and by @bjklemme-intel in https://github.com/securefederatedai/openfl/pull/813
  • Improve workspace requirements import by @danhe1 in https://github.com/securefederatedai/openfl/pull/810
  • Added Example using FedProx by @bjklemme-intel in https://github.com/securefederatedai/openfl/pull/818
  • Add new tutorial example to OpenFL interactive API by @bjklemme-intel in https://github.com/securefederatedai/openfl/pull/812
  • Running a federation with GaNDLF Documentation by @psfoley in https://github.com/securefederatedai/openfl/pull/794
  • Fix documentation build by @psfoley in https://github.com/securefederatedai/openfl/pull/841
  • Fix GaNDLF documentation links by @psfoley in https://github.com/securefederatedai/openfl/pull/842
  • Fix incorrectly formatted link in docs by @fstrr in https://github.com/securefederatedai/openfl/pull/839
  • Accessibility updates by @fstrr in https://github.com/securefederatedai/openfl/pull/861
  • Fixing FedAvg in workflow interface tutorials to be compatible with latest numpy stable release (1.24.3) by @kta-intel in https://github.com/securefederatedai/openfl/pull/833
  • Accessibility color contrast fixes by @fstrr in https://github.com/securefederatedai/openfl/pull/864
  • Testflow for verifying stdout redirection to Metaflow datastore by @KeertiX in https://github.com/securefederatedai/openfl/pull/758
  • Tweak link color so it’s not so aggressive by @fstrr in https://github.com/securefederatedai/openfl/pull/865
  • pinned tensorboardX by @porteratzo in https://github.com/securefederatedai/openfl/pull/870
  • Update Tensorflow, gRPC, Protobuf dependencies by @psfoley in https://github.com/securefederatedai/openfl/pull/868
  • Add FL plan description to documentation by @mansishr in https://github.com/securefederatedai/openfl/pull/872
  • Resolve Coverity Issues by @psfoley in https://github.com/securefederatedai/openfl/pull/874
  • Migrate Docker to Ubuntu 22.04 LTS release (supported through 2027) by @psfoley in https://github.com/securefederatedai/openfl/pull/875
  • Update EdenPipeline in the documentation by @amitport in https://github.com/securefederatedai/openfl/pull/877
  • CI Scans by @psfoley in https://github.com/securefederatedai/openfl/pull/873
  • Roadmap update by @psfoley in https://github.com/securefederatedai/openfl/pull/878
  • Removed unused packages from Docker image by @ashahba in https://github.com/securefederatedai/openfl/pull/890
  • Help redirect users looking for Open Flash Library (OpenFL) Project by @psfoley in https://github.com/securefederatedai/openfl/pull/891
  • Fixes that address dependency vulnerabilities

New Contributors

  • @grib0ed0v made their first contribution in https://github.com/securefederatedai/openfl/pull/719
  • @ptizzza made their first contribution in https://github.com/securefederatedai/openfl/pull/761
  • @joedevon made their first contribution in https://github.com/securefederatedai/openfl/pull/785
  • @akantak made their first contribution in https://github.com/securefederatedai/openfl/pull/800
  • @wangleflex made their first contribution in https://github.com/securefederatedai/openfl/pull/809
  • @fangxiaoran made their first contribution in https://github.com/securefederatedai/openfl/pull/821
  • @danhe1 made their first contribution in https://github.com/securefederatedai/openfl/pull/808
  • @bjklemme-intel made their first contribution in https://github.com/securefederatedai/openfl/pull/813
  • @fstrr made their first contribution in https://github.com/securefederatedai/openfl/pull/839
  • @KeertiX made their first contribution in https://github.com/securefederatedai/openfl/pull/758
  • @porteratzo made their first contribution in https://github.com/securefederatedai/openfl/pull/870
  • @amitport made their first contribution in https://github.com/securefederatedai/openfl/pull/877
  • @ashahba made their first contribution in https://github.com/securefederatedai/openfl/pull/890

Full Changelog: https://github.com/securefederatedai/openfl/compare/v1.5...v1.5.1

- Python
Published by psfoley over 2 years ago

openfederatedlearning - v1.5

Highlights

We are excited to announce the release of OpenFL 1.5! This release brings the following changes: * New Workflows Interface (Experimental) - a new way of composing federated learning experiments inspired by Metaflow. Enables the creation of custom aggregator and collaborators tasks. This initial release is intended for simulation on a single node (using the LocalRuntime); distributed execution (FederatedRuntime) to be enabled in a future release. * New use cases enabled by the workflow interface: * End-of-round validation with aggregator dataset * Privacy Meter - Privacy meter, based on state-of-the-art membership inference attacks, provides a tool to quantitatively audit data privacy in statistical and machine learning algorithms. The objective of a membership inference attack is to determine whether a given data record was in the training dataset of the target model. Measures of success (accuracy, area under the ROC curve, true positive rate at a given false positive rate ...) for particular membership inference attacks against a target model are used to estimate privacy loss for that model (how much information a target model leaks about its training data). Since stronger attacks may be possible, these measures serve as lower bounds of the actual privacy loss. The Privacy Meter workflow example generates privacy loss reports for all party's local model updates as well as the global models throughout all rounds of the FL training. * Vertical Federated Learning Examples * Federated Model Watermarking using the WAFFLE method * Differential Privacy – Global differentially private federated learning using Opacus library to achieve a differentially private result w.r.t the inclusion or exclusion of any collaborator in the training process. At each round, a subset of collaborators are selected using a Poisson distribution over all collaborators, the selected collaborators perform local training with periodic clipping of their model delta (with respect to the current global model) to bound their contribution to the average of local model updates. Gaussian noise is then added to the average of these local models at the aggregator. This example is implemented in two different but statistically equivalent ways – the lower level API utilizes RDPAccountant and DPDataloader Opacus objects to perform privacy accounting and collaborator selection respectively, whereas the higher level API uses PrivacyEngine Opacus object for collaborator selection and internally utilizes RDPAccountant for privacy accounting. * Habana Accelerator Support * Official support for Python 3.9 and 3.10 * EDEN Compression Pipeline: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning (paper link) * FLAX Framework Support * Improvements to the resiliency and security of the director / envoy infrastructure: * Optional notification to plan participants to agree to experiment sent to their infrastructure * Improved resistance to loss of network connectivity and failure at various stages of execution * Windows Support (Experimental): Continuous Integration now tests OpenFL on Windows, but certain features may not work as expected. Full Windows support will be added in a future release.

Breaking Changes

  • Removal of Python 3.6 support due to numpy requirements
  • Removal of FastEstimator examples due to dependency package incompatibility with OpenFL

What's Changed

  • Remove CLA from OpenFL Repo by @psfoley in https://github.com/intel/openfl/pull/504
  • Introduce parameters to tune gRPC max message size by @igor-davidyuk in https://github.com/intel/openfl/pull/494
  • [Snyk] Security upgrade protobuf from 3.20.1 to 3.20.2 by @snyk-bot in https://github.com/intel/openfl/pull/508
  • Bump protobuf from 3.19.4 to 3.19.5 by @dependabot in https://github.com/intel/openfl/pull/507
  • Tutorials fixes by @igor-davidyuk in https://github.com/intel/openfl/pull/516
  • Pin TF version in CI tests by @mansishr in https://github.com/intel/openfl/pull/517
  • OpenFL Roadmap by @psfoley in https://github.com/intel/openfl/pull/514
  • Add ISV product ID and ISV SVN fields to manifest by @DL8 in https://github.com/intel/openfl/pull/502
  • citation updated to IOP source by @sarthakpati in https://github.com/intel/openfl/pull/526
  • Tutorial Improvements by @mkurisoo in https://github.com/intel/openfl/pull/493
  • Flax CIFAR10 CNN Interactive API Example by @acharyasunil in https://github.com/intel/openfl/pull/482
  • Break apart CI tests by @psfoley in https://github.com/intel/openfl/pull/528
  • Support Python 3.9 and 3.10 by @psfoley in https://github.com/intel/openfl/pull/532
  • Contributing EDEN compression pipeline by @yanivbi in https://github.com/intel/openfl/pull/527
  • Gramine manifest update by @igor-davidyuk in https://github.com/intel/openfl/pull/537
  • Configurable enclave size by @DL8 in https://github.com/intel/openfl/pull/569
  • For gramine set write logs to false by @mansishr in https://github.com/intel/openfl/pull/547
  • Add flake8 extensions to linter CI workflow by @itrushkin in https://github.com/intel/openfl/pull/560
  • Removed Protobuf 3.19.4 dependency by @acharyasunil in https://github.com/intel/openfl/pull/558
  • [Snyk] Fix for 2 vulnerabilities by @Einse57 in https://github.com/intel/openfl/pull/598
  • Fix log metric callback settings by @mansishr in https://github.com/intel/openfl/pull/538
  • Convert protobuf model to native format by @psfoley in https://github.com/intel/openfl/pull/550
  • Fix linter issues by @itrushkin in https://github.com/intel/openfl/pull/619
  • Update OpenFL 1.5 features on roadmap by @psfoley in https://github.com/intel/openfl/pull/626
  • Add random delay in authentication failures by @igor-davidyuk in https://github.com/intel/openfl/pull/620
  • [Windows] UnicodeDecodeError by @itrushkin in https://github.com/intel/openfl/pull/610
  • Introduce the install requirements option in director and envoy configs by @igor-davidyuk in https://github.com/intel/openfl/pull/536
  • Update Jenkins pipeline to support publishing to PyPI by @soda480 in https://github.com/intel/openfl/pull/634
  • Update pytest_coverage.yml by @Einse57 in https://github.com/intel/openfl/pull/635
  • Handling envoy disconnections on getting experiment. by @aleksandr-mokrov in https://github.com/intel/openfl/pull/623
  • Versions of zlib before 1.2.12 have several CVEs lodged against them.… by @Einse57 in https://github.com/intel/openfl/pull/631
  • Tensorboard documentation by @mansishr in https://github.com/intel/openfl/pull/520
  • Envoys to review plan before experiment starts by @mansishr in https://github.com/intel/openfl/pull/489
  • PKI testing by @itrushkin in https://github.com/intel/openfl/pull/621
  • Fix logging in Numpy Linear model + Colab example by @igor-davidyuk in https://github.com/intel/openfl/pull/535
  • Fix FeTS Challenge CI by @psfoley in https://github.com/intel/openfl/pull/641
  • HPU Adaptations for PyTorch TinyImagenet Interactive API by @Supriya-Krishnamurthi in https://github.com/intel/openfl/pull/636
  • build(deps): bump pillow from 9.0.1 to 9.3.0 in /openfl-tutorials/interactiveapi/HPU/PyTorchTinyImageNet/envoy by @dependabot in https://github.com/intel/openfl/pull/643
  • Envoy can reconnect to current experiment after restarting for the du… by @aleksandr-mokrov in https://github.com/intel/openfl/pull/640
  • Adapt torch_cnn_mnist example to testing pipeline by @igor-davidyuk in https://github.com/intel/openfl/pull/644
  • Jenkins Pipeline updates by @soda480 in https://github.com/intel/openfl/pull/645
  • Resending Shard Info if the director has lost the information by @aleksandr-mokrov in https://github.com/intel/openfl/pull/624
  • Fix TensorFlow version comparison by @itrushkin in https://github.com/intel/openfl/pull/649
  • Write keys with restricted permissions (#637) by @DL8 in https://github.com/intel/openfl/pull/648
  • [Feature] Timing Fed Components by @acharyasunil in https://github.com/intel/openfl/pull/530
  • [Examples] Update Tensorflow to 2.8.4 by @psfoley in https://github.com/intel/openfl/pull/650
  • Update to Pillow 9.3.0 by @psfoley in https://github.com/intel/openfl/pull/651
  • Suppress pandas FutureWarning by @itrushkin in https://github.com/intel/openfl/pull/664
  • CI for Windows by @itrushkin in https://github.com/intel/openfl/pull/587
  • Enable PEP8 naming extension for flake8 by @itrushkin in https://github.com/intel/openfl/pull/668
  • [CI] Process GitHub API rate limit error by @itrushkin in https://github.com/intel/openfl/pull/669
  • Fix straggler handling to identify stragglers for a round by @mansishr in https://github.com/intel/openfl/pull/628
  • Add tag name argument to graminize by @DL8 in https://github.com/intel/openfl/pull/662
  • Cleanup temporary files (SDLE task) by @mansishr in https://github.com/intel/openfl/pull/665
  • CI badges by @itrushkin in https://github.com/intel/openfl/pull/673
  • Experimental Workflow interface by @psfoley in https://github.com/intel/openfl/pull/632
  • Workflow interface: Fix documentation and colab instructions by @psfoley in https://github.com/intel/openfl/pull/680
  • Fix python path in workspace context manager by @igor-davidyuk in https://github.com/intel/openfl/pull/682
  • Fix missing NumPy int attribute by @itrushkin in https://github.com/intel/openfl/pull/683
  • Updating pytorch versions, renaming deprecated onepochend hook by @aleksandr-mokrov in https://github.com/intel/openfl/pull/687
  • Update eden_pipeline.py by @yanivbi in https://github.com/intel/openfl/pull/681
  • ci: bandit to fail only on high severity vulns by @soda480 in https://github.com/intel/openfl/pull/696
  • Remove FastEstimator until compatible dependencies are available by @psfoley in https://github.com/intel/openfl/pull/697
  • Pytorch version is updated to 1.13.1 by @aleksandr-mokrov in https://github.com/intel/openfl/pull/698
  • Update kc_pipeline.py by @ishant162 in https://github.com/intel/openfl/pull/694
  • Hashing function update by @psfoley in https://github.com/intel/openfl/pull/700
  • Added HPU adaptations to Kvasir_UNet example by @Supriya-Krishnamurthi in https://github.com/intel/openfl/pull/675
  • Cleanup FastEstimator references by @psfoley in https://github.com/intel/openfl/pull/702
  • Update Copyright to 2023 by @psfoley in https://github.com/intel/openfl/pull/704
  • Docker: Pull all GPL package sources by @psfoley in https://github.com/intel/openfl/pull/705
  • Update copyright year for tests, documentation by @psfoley in https://github.com/intel/openfl/pull/706
  • Update version to 1.5 by @psfoley in https://github.com/intel/openfl/pull/703
  • Add tests for EDEN Compression Pipeline by @psfoley in https://github.com/intel/openfl/pull/707
  • Align graminize process with setup documentation by @DL8 in https://github.com/intel/openfl/pull/695
  • Added HPU adaptations for PytorchMedMNIST2D by @Supriya-Krishnamurthi in https://github.com/intel/openfl/pull/652
  • Removes SNYK scan for FastEstimator by @psfoley in https://github.com/intel/openfl/pull/712
  • Updated python version details in readme file by @Supriya-Krishnamurthi in https://github.com/intel/openfl/pull/709
  • Remove Python 3.6 support due to numpy requirements @psfoley https://github.com/intel/openfl/pull/713
  • [Snyk] Fixes for dependency vulnerabilities

New Contributors

  • @DL8 made their first contribution in https://github.com/intel/openfl/pull/502
  • @yanivbi and @shayvar made their first contribution in https://github.com/intel/openfl/pull/527
  • @Supriya-Krishnamurthi made their first contribution in https://github.com/intel/openfl/pull/636
  • @ishant162 made their first contribution in https://github.com/intel/openfl/pull/694

Full Changelog: https://github.com/intel/openfl/compare/v1.4...v1.5

- Python
Published by psfoley about 3 years ago

openfederatedlearning - OpenFL 1.4

The OpenFL v1.4 release contains the following:

- Python
Published by psfoley over 3 years ago

openfederatedlearning - OpenFL 1.3

The OpenFL v1.3 release contains the following updates: * Task Assigner functionality * OpenFL + Gramine to support workloads within SGX * FedCurv aggregation algorithm * HuggingFace/transformers audio classification example using SUPERB dataset * PyTorch Lightning GAN example * NumPy Linear Regression example in Google Colab * Adaptive Federated Optimization algorithms implementation: FedYogi, FedAdagrad, FedAdam * MXNet landmarks regression example as a custom plugin to OpenFL * Migration to JupyterLab * Bug fixes and other improvements

- Python
Published by alexey-gruzdev almost 4 years ago

openfederatedlearning - OpenFL 1.2.1

The OpenFL v1.2.1 release contains the following updates:

- Python
Published by alexey-gruzdev about 4 years ago

openfederatedlearning - OpenFL 1.2

The OpenFL v1.2 release contains the following updates:

- Python
Published by alexey-gruzdev over 4 years ago

openfederatedlearning - OpenFL 1.1

The OpenFL v1.1 release contains the following updates:

  • New Interactive Python API (experimental)
  • Example FedProx algorithm implementation for PyTorch and Tensorflow
  • AggregationFunctionInterface for custom aggregation functions
  • Adds a Keras-based NLP Example
  • Fixed lossy compression pipelines and added an example for usage
  • Bug fixes and documentation improvements

- Python
Published by psfoley almost 5 years ago

openfederatedlearning - OpenFL 1.0.1

v1.0.1 is a patch release. It includes the following updates:

  • New docker CI tests
  • New Pytorch UNet Kvasir tutorial
  • Cleanup / fixes to other OpenFL tutorials
  • Fixed description for Pypi
  • Status/documentation/community badges for README.md

- Python
Published by psfoley almost 5 years ago

openfederatedlearning - OpenFL 1.0

This release includes: - The official open source release of OpenFL - Tensorflow 2.0 and PyTorch support - Examples for classification, segmentation, and adversarial training - No-install Docker and Singularity* deployments - Python native API intended for single node federated learning experiments - fx CLI for multi-node production deployments - Additional test coverage for OpenFL components

* Singularity supported via DockerHub integration: singularity shell docker://openfl:latest

- Python
Published by psfoley about 5 years ago