p2pfl.learning.frameworks.simulation package

Module for the efficient parallel local simulation of the learning process (based on Ray).

p2pfl.learning.frameworks.simulation.try_init_learner_with_ray(learner, model, data, addr, aggregator)

Create a learner instance.

Parameters:

• learner (Type[Learner]) – The learner class.

• model (P2PFLModel) – The model of the learner.

• data (P2PFLDataset) – The data of the learner.

• addr (str) – The address of the learner.

• aggregator (Aggregator) – The aggregator that we are using.

Return type:

Learner

Submodules

• p2pfl.learning.frameworks.simulation.actor_pool module
  • SuperActorPool
    • SuperActorPool._instance
    • SuperActorPool._lock
    • SuperActorPool.resources
    • SuperActorPool._addr_to_future
    • SuperActorPool.actor_to_remove
    • SuperActorPool.num_actors
    • SuperActorPool.lock
    • SuperActorPool.initialized
    • SuperActorPool.add_actor()
    • SuperActorPool.create_actor()
    • SuperActorPool.get_learner_result()
    • SuperActorPool.process_unordered_future()
    • SuperActorPool.submit()
    • SuperActorPool.submit_learner_job()
• p2pfl.learning.frameworks.simulation.utils module
  • check_client_resources()
  • pool_size_from_resources()
• p2pfl.learning.frameworks.simulation.virtual_learner module
  • VirtualNodeLearner
    • VirtualNodeLearner.evaluate()
    • VirtualNodeLearner.fit()
    • VirtualNodeLearner.get_data()
    • VirtualNodeLearner.get_framework()
    • VirtualNodeLearner.get_model()
    • VirtualNodeLearner.interrupt_fit()
    • VirtualNodeLearner.set_addr()
    • VirtualNodeLearner.set_data()
    • VirtualNodeLearner.set_epochs()
    • VirtualNodeLearner.set_model()