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| { | |
| "owner": "labmlai", | |
| "repo": "annotated_deep_learning_paper_implementations", | |
| "number": 146, | |
| "html_url": "https://github.com/labmlai/annotated_deep_learning_paper_implementations/issues/146", | |
| "is_pull_request": false, | |
| "state": "closed", | |
| "state_reason": "completed", | |
| "title": "Bug in SA for DDPM UNet?", | |
| "author": "FutureXiang", | |
| "created_at": "2022-09-07T17:28:50Z", | |
| "updated_at": "2022-10-13T11:16:47Z", | |
| "closed_at": "2022-10-13T11:16:47Z", | |
| "labels": [ | |
| "bug" | |
| ], | |
| "milestone": null, | |
| "comments_count": 3, | |
| "reactions": { | |
| "total_count": 0, | |
| "+1": 0, | |
| "-1": 0, | |
| "laugh": 0, | |
| "hooray": 0, | |
| "confused": 0, | |
| "heart": 0, | |
| "rocket": 0, | |
| "eyes": 0 | |
| }, | |
| "resolution_days": 35.74, | |
| "fix": { | |
| "closing_commit": null, | |
| "linked_prs": [], | |
| "best_guess_fix_commit": null, | |
| "has_fix": false | |
| }, | |
| "fetched_at": "2026-07-28T12:22:15.889126+00:00", | |
| "comments": [ | |
| { | |
| "author": "vpj", | |
| "created_at": "2022-09-11T12:02:35Z", | |
| "body": "Thanks, you are right! That's a typo and a big bug!" | |
| }, | |
| { | |
| "author": "FutureXiang", | |
| "created_at": "2022-09-11T14:04:07Z", | |
| "body": "Thank you for your response!\r\n\r\nI compare the FID results on classifier-free guidance conditional CIFAR-10 with `attn = attn.softmax(dim=1)` and `attn = attn.softmax(dim=2)`, following the settings in the original DDPM paper.\r\n\r\nHowever, I observe **no difference** between the bugged and the correct model (FID \u00b10.05),\r\nand the correct model performs **even worse** than the bugged one when trained with more iterations (FID -0.02~0.3).\r\n\r\nHave any idea why it happens?" | |
| }, | |
| { | |
| "author": "vpj", | |
| "created_at": "2022-09-12T03:11:06Z", | |
| "body": "This is strange. I guess the wrong softmax also provides a similar non-linearity to the correct softmax and gradient descent finds a way to use it. But I don't understand how the wrong softmax becomes better than the correct one. Wonder how well no attention will perform. I will also try to run some tests.\r\n\r\nBtw, I pushed the fix https://github.com/labmlai/annotated_deep_learning_paper_implementations/commit/7d1550dd67ef903959a6367165e17c15b89da5c8" | |
| } | |
| ] | |
| } |