{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/could-use-op","entry":"could_use_op","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":0,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":3,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":3},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2304.03119","paper":"/paper/zero-shot-generative-model-adaptation-via","title":"Zero-shot Generative Model Adaptation via Image-specific Prompt Learning","date":"2023-04-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"picsart-ai-research/ipl-zero-shot-generative-model-adaptation","path":"op/conv2d_gradfix.py","file_url":"https://github.com/picsart-ai-research/ipl-zero-shot-generative-model-adaptation/blob/HEAD/op/conv2d_gradfix.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ce977f8c2571b94b","mcp_get_code":{"code_sha256":"ce977f8c2571b94b"}},{"arxiv_id":"2203.14954","paper":"/paper/giraffe-hd-a-high-resolution-3d-aware","title":"GIRAFFE HD: A High-Resolution 3D-aware Generative Model","date":"2022-03-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"austinxy/giraffehd","path":"op/conv2d_gradfix.py","file_url":"https://github.com/austinxy/giraffehd/blob/HEAD/op/conv2d_gradfix.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ce977f8c2571b94b","mcp_get_code":{"code_sha256":"ce977f8c2571b94b"}},{"arxiv_id":"2112.11641","paper":"/paper/jojogan-one-shot-face-stylization-1","title":"JoJoGAN: One Shot Face Stylization","date":"2021-12-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mchong6/JoJoGAN","path":"op/conv2d_gradfix.py","file_url":"https://github.com/mchong6/JoJoGAN/blob/HEAD/op/conv2d_gradfix.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ca47733c49998955","mcp_get_code":{"code_sha256":"ca47733c49998955"}},{"arxiv_id":"2110.04627","paper":"/paper/vector-quantized-image-modeling-with-improved-1","title":"Vector-quantized Image Modeling with Improved VQGAN","date":"2021-10-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thuangb/enhancing-transformers","path":"enhancing/losses/op/conv2d_gradfix.py","file_url":"https://github.com/thuangb/enhancing-transformers/blob/HEAD/enhancing/losses/op/conv2d_gradfix.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ce977f8c2571b94b","mcp_get_code":{"code_sha256":"ce977f8c2571b94b"}},{"arxiv_id":"2106.12423","paper":"/paper/alias-free-generative-adversarial-networks","title":"Alias-Free Generative Adversarial Networks","date":"2021-06-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"duskvirkus/alias-free-gan-pytorch-lightning","path":"src/op/conv2d_gradfix.py","file_url":"https://github.com/duskvirkus/alias-free-gan-pytorch-lightning/blob/HEAD/src/op/conv2d_gradfix.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5ded1499a636f8df","mcp_get_code":{"code_sha256":"5ded1499a636f8df"}}]}