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Fed-BioMed changelog

2022-05-09 version 3.5

  • add FedProx optimization scheme support for PyTorch in training plan
  • data manager to provide robust solution on managing node datasets before training on the node side
  • model evaluation/testing on the node side over locally updated and aggregated model parameters
  • add NIFTI folder dataset type
  • add option to load MedNIST dataset in node
  • update docstrings for API documentation support
  • node container support for GPU with PyTorch, tested on Fedora 35
  • debug and robustify VPN/containers environment, test on Ubuntu 20 and Windows 10 + WSL2
  • VPN/containers environment scripts for simpler management of containers and peers
  • refactor training_plans/_fedbiosklearn.py to get rid off eval()
  • change training_plans file organisation
  • create a top class for training_plans
  • removed the magic %writefile use in notebooks to save the user's defined model
  • more unittests and flake8 parsing
  • add validation class for checking user input

2022-02-25 version 3.4

  • rewriting of Opacus notebook
  • new tutorial notebook on Experiment() usage
  • add .coveragerc to tune test coverage
  • fix mqtt logger loop then mqqt not reachable
  • replace @property getters/setters by proper getters() setters(), still in progress
  • a lot of new unit tests and increase test coverage
  • refactor of Message() class, simplication of Messages description (purely declarative now)
  • add more ErrorNumbers + associated messages
  • check user input (mainly in Experiment() for now)
  • rename Exceptions as Errors, add FedbiomedError as top class of our errors
  • use try/except block at low level layers
  • Environ() class refactoring, environment tests rewriting
  • Experiment() class refactoring, new API, more setters/getters, interactive use, rename rounds -> round_limit,...
  • add single GPU training support for PyTorch
  • add a gui to manage data on nodes
  • update of sklearn sgdregressor notebook
  • update of monai notebook
  • Tensorboard fixes for multi class classification with scikit learn

2022-01-07 version 3.3

  • add MONAI support and example notebooks
  • add model manager to register and check authorized training models on the node based on model hash
  • refactor experiment real time monitoring capacity with Tensorboard
  • add Request.list() to list shared dataset on online nodes
  • configure_conda may take parameters to only update some environments
  • fix conda environments for mac OSX
  • add -n (dryrun) option for configure_conda, for debug/validation purpose
  • fix and refactor breakpoint feature which was not fully operational
  • change the names of breakpoint directories
  • node error reporting to researcher
  • basic error handling on researcher component
  • mutualize the Singleton metaclass
  • refactor environ as singleton class
  • fix the way the tests deal with fedbiomed.common.environ
  • refactor strategy (moved some methods in upper classes)
  • add command run_integration_test to easily run an integration test from a single .py or .ipynb
  • add an automatized method to add a dataset in nodes's db from a JSON dataset description file
  • add error numbering as an enum, impact on error messages serialization
  • more example notebooks, update existing notebooks
  • more unittests
  • normalize naming : use term 'node' not 'client'

2021-10-21 version 3.2

  • add support for scikit-learn with SGD regressor and example notebook
  • add VPN + docker environment for deploying over an untrusted network
  • add message logging capability including sending node messages to researcher
  • add loss report from node during training and view in tensorboard in researcher
  • add save/load state capability after each round during a training
  • add capability for listing datasets on each node
  • add example notebooks for Celeba and used cars dataset
  • WIP add unit tests
  • add support for multiple Experiment(), including re-executing a notebook
  • fix issue erratic failure when training with 3+ nodes
  • test and document Windows 10 installation in WSL

2021-08-13 version 3.1

  • merge 3 gitlab repos fedbiomed-{network,node,researcher} in a unique fedbiomed repo
  • add new model variational autoencoder (VAE)
  • add support for generic dataloader and handling of .csv dataset
  • measure execution time on nodes
  • WIP adding unit tests
  • misc code cleaning

2021-07-05 version 3.0

  • initial release of re-implementation based on pytorch model file transfer and MQTT messaging