FedJAX
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Getting started

  • Federated datasets
  • Working with models in FedJAX
  • Federated learning algorithms

Developer documentation

  • Contributing
  • Building from source
  • Running the tests
  • Updating the docs

API reference

  • fedjax core
  • fedjax.aggregators
  • fedjax.algorithms
  • fedjax.datasets
  • fedjax.models
  • fedjax.training
FedJAX
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  • FedJAX documentation
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FedJAX documentationΒΆ

FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX. FedJAX prioritizes ease-of-use and is intended to be useful for anyone with knowledge of NumPy.

Getting started

  • Federated datasets
  • Working with models in FedJAX
  • Federated learning algorithms

Developer documentation

  • Contributing
  • Building from source
  • Running the tests
  • Updating the docs

API reference

  • fedjax core
    • Subpackages
      • fedjax.metrics
      • fedjax.optimizers
      • fedjax.tree_util
    • Federated algorithm
    • Federated data
    • Client dataset
    • For each client
    • Model
  • fedjax.aggregators
    • Mean
    • Quantization
  • fedjax.algorithms
    • AgnosticFedAvg
    • FedAvg
    • HypCluster
    • Mime
    • MimeLite
  • fedjax.datasets
    • CIFAR-100
    • EMNIST
    • Shakespeare
    • Stack Overflow
  • fedjax.models
    • EMNIST
    • Shakespeare
    • Stack Overflow
    • Toy Regression
  • fedjax.training
    • Federated experiment
    • Tasks
    • Structured flags
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