[training topology]
@beam/scored-subnetScored subnet
Miners pull data shards and send gradients on a broadcast lane; validators observe every gradient, score it and send signed scores to the model holder, which merges the round weighted by the median of their scores. A round nobody scored is weighted by units. Validators need the runs.observe and runs.score room permissions and join by invite only.
[topology identity]
Details
What version 1.0.2 declares.
- Package
@beam/scored-subnet- Membership
- Elastic
- Engines
- distributed run
- Tags
- bittensor, data-grants, elastic, live-session, score-weighted, subnet
- Step kinds
- local, broadcast, gather
- Latest tag
- latest -> 1.0.2
- Publisher
- registry
- Visibility
- Public
- Checksum
sha256:7e5a312b0c5a113fc3283226c1b0ca754587b143f0f7a254744717e9dd47a3ec
[roles]
Roles
Who takes part, and how many members each role holds.
Leads the run, hands out data shards and holds the model.
Registers and leaves freely; pulls data shards.
Observes and scores every gradient (runs.observe and runs.score room permissions).
[slots]
Slots
The actions a run binds: what each slot consumes and produces.
Merges the gradients weighted by the median of their scores.
Scores every observed gradient and signs the scores.
Trains on pulled data shards and sends a gradient.
[round]
Step kinds
The steps of one round, in order.
- localrole miner · slot train
- broadcastfrom miner · to validator · object gradients
- localrole validator · slot score
- gatherfrom miner · to lead · object gradients · slot merge
- broadcastfrom lead · to miner · object model