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| author | Dylan <boss@tehbox.org> | 2026-11-09 16:38:13 +1300 |
|---|---|---|
| committer | Dylan <boss@tehbox.org> | 2026-11-09 16:38:13 +1300 |
| commit | 478e7568f5eda9780d1409bb8dccc86221126281 (patch) | |
| tree | 2f4ec7a90d0c65505b757bdce0ddd2f9778ccaa5 /src/main.rs | |
| parent | 0fd43eb6d9a4bae8d4c29fd614f9cf2a362f7b7c (diff) | |
| download | tigers-and-sheep-478e7568f5eda9780d1409bb8dccc86221126281.tar.gz tigers-and-sheep-478e7568f5eda9780d1409bb8dccc86221126281.zip | |
feat: Multi-threaded training; play matches every 10 generations
Gradients and losses are computed on rayon's pool in fixed-size chunks
summed in order, so the weights are the same on any number of threads.
Self-play uses the same pool, and the output shows the training time.
The matches against the earlier network and ClaudePlayer now run only
every --match-every generations (default 10), against the generation
that last played them, read back from its saved file.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Diffstat (limited to 'src/main.rs')
| -rw-r--r-- | src/main.rs | 6 |
1 files changed, 5 insertions, 1 deletions
diff --git a/src/main.rs b/src/main.rs index 5a3c798..5237100 100644 --- a/src/main.rs +++ b/src/main.rs @@ -145,9 +145,12 @@ struct TrainArgs /// Adam's learning rate #[arg(long, default_value_t = train::Config::default().learning_rate)] learning_rate: f32, - /// Games against ClaudePlayer, and against the previous generation, after each generation + /// Games against ClaudePlayer, and against the generation that last played them #[arg(long, default_value_t = train::Config::default().match_games)] match_games: usize, + /// Play those matches only every this many generations + #[arg(long, default_value_t = train::Config::default().match_every)] + match_every: usize, } impl From<TrainArgs> for train::Config @@ -171,6 +174,7 @@ impl From<TrainArgs> for train::Config batch_size: args.batch_size, learning_rate: args.learning_rate, match_games: args.match_games, + match_every: args.match_every, } } } |