{"action":"created","issue":{"url":"https://api.github.com/repos/gcp/leela-zero/issues/1030","repository_url":"https://api.github.com/repos/gcp/leela-zero","labels_url":"https://api.github.com/repos/gcp/leela-zero/issues/1030/labels{/name}","comments_url":"https://api.github.com/repos/gcp/leela-zero/issues/1030/comments","events_url":"https://api.github.com/repos/gcp/leela-zero/issues/1030/events","html_url":"https://github.com/gcp/leela-zero/issues/1030","id":304758264,"number":1030,"title":"Bigger, stronger, not faster (4dc12a8e etc)","user":{"login":"gcp","id":1104290,"avatar_url":"https://avatars2.githubusercontent.com/u/1104290?v=4","gravatar_id":"","url":"https://api.github.com/users/gcp","html_url":"https://github.com/gcp","followers_url":"https://api.github.com/users/gcp/followers","following_url":"https://api.github.com/users/gcp/following{/other_user}","gists_url":"https://api.github.com/users/gcp/gists{/gist_id}","starred_url":"https://api.github.com/users/gcp/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gcp/subscriptions","organizations_url":"https://api.github.com/users/gcp/orgs","repos_url":"https://api.github.com/users/gcp/repos","events_url":"https://api.github.com/users/gcp/events{/privacy}","received_events_url":"https://api.github.com/users/gcp/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":120,"created_at":"2018-03-13T13:10:53Z","updated_at":"2018-03-19T11:38:17Z","closed_at":null,"author_association":"OWNER","body":"There are a number of tests with bigger networks running, notably 128x20 and 192x10 configurations. Probably due to issue #1025, the 128x20 networks failed rather badly, but 192x10 has been doing OK (it was not affected by the bug due to fortunate circumstances).\r\n\r\nIf the new networks are noticeably stronger than the best 128x10, it makes sense to switch. It looks like we may already be very close to this point. \r\n\r\nWhat the boundary *exactly* is is not so clear: if 128x10 has stalled (it has not, so far), then it's clear. If the new net is several hundreds of Elo stronger, then it's clear. In the middle there's some trade-off between having 1/2 the games played at a higher level, versus being able to iterate new networks faster at a smaller size. I am not worrying too much about this zone, as inevitably we will hit either of the \"clear\" cases sooner rather than later.\r\n\r\nI would also prefer to be able to retrain the 128x20 so it can be tested against 192x10, but I don't consider it a blocker for moving up (if 128x20 ends up surpassing 192x10 significantly, we'll just let it promote...).\r\n\r\n(I originally planned for 128x10 to be the \"final size\" for this \"first run\", but the progress made with bootstrap/net2net, improved client speed and the current strength are certainly making me want to keep going at it for a bit longer...)"},"comment":{"url":"https://api.github.com/repos/gcp/leela-zero/issues/comments/374183563","html_url":"https://github.com/gcp/leela-zero/issues/1030#issuecomment-374183563","issue_url":"https://api.github.com/repos/gcp/leela-zero/issues/1030","id":374183563,"user":{"login":"jkiliani","id":33714573,"avatar_url":"https://avatars2.githubusercontent.com/u/33714573?v=4","gravatar_id":"","url":"https://api.github.com/users/jkiliani","html_url":"https://github.com/jkiliani","followers_url":"https://api.github.com/users/jkiliani/followers","following_url":"https://api.github.com/users/jkiliani/following{/other_user}","gists_url":"https://api.github.com/users/jkiliani/gists{/gist_id}","starred_url":"https://api.github.com/users/jkiliani/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jkiliani/subscriptions","organizations_url":"https://api.github.com/users/jkiliani/orgs","repos_url":"https://api.github.com/users/jkiliani/repos","events_url":"https://api.github.com/users/jkiliani/events{/privacy}","received_events_url":"https://api.github.com/users/jkiliani/received_events","type":"User","site_admin":false},"created_at":"2018-03-19T11:38:17Z","updated_at":"2018-03-19T11:38:17Z","author_association":"NONE","body":"I think doubling visits is really a \"brute-force\" approach that may possibly work, but is unlikely to give us any new insights into what really works in reinforcement learning and what doesn't. AlphaZero contains three key changes compared to Alphago Zero: They actually lowered playouts (and it still worked), they discarded gating, and they used temperature=1 for the whole game. Increasing visits runs exactly counter to the first of those changes. I think both the Always-promote method and temperature=1 should be given serious consideration before increasing visits. Their effectiveness may be linked to each other or not, it's hard to say.\r\n\r\nOne thing that an experiment including temperature=1 would definitely necessitate is a new resign analysis, due to many more endgame blunders."}}
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