Topologies
[training topology]
@beam/fedavg-dataFederated averaging on bucket data
Rounds of training on a room bucket prefix; each worker trains on its own share of the files (kept across rounds), then a tree all-reduce merge and a stop on the training loss.
Static membershipBuiltinActivedistributed run
[topology identity]
Details
What version 1.0.1 declares.
- Package
@beam/fedavg-data- Membership
- Static
- Engines
- distributed run
- Tags
- all-reduce, bucket-data, federated-averaging, rounds
- Step kinds
- local, all-reduce
- Latest tag
- latest -> 1.0.1
- Publisher
- registry
- Visibility
- Public
- Checksum
sha256:282d7ec4c81090d25b457abc540102afca99b21d86903ae14ffd8bbd2a0f9893
[roles]
Roles
Who takes part, and how many members each role holds.
Every eligible room member trains on its share of the files.
[slots]
Slots
The actions a run binds: what each slot consumes and produces.
update* -> model, report?
Averages the workers' models; associative, commutative and closed (runs as a tree).
model?, files -> update, report
Trains on the worker's share of the files, from the received model when there is one.
[round]
Step kinds
The steps of one round, in order.
- localrole workers · slot train
- all-reducerole workers · object update · slot merge