{"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":"/census/patchify","entry":"patchify","source":"Syntology differential census (groundwork/55, run v2_2026-09-22), per sample; not an archive number","census_date":"2026-09-22","battery_sha256":["b986f7e04d794a0d88ad4c5f32cf63ec3590b5deff0192150737bc5f1c0b4677"],"runner_sha256":["5a452d0e7c0da5b80771d1be2afe3572e253568cf5c5d59a0d08ebd663d00808"],"bucket_key":"positional (rank, kind, dtype) of each array argument; the argument name is not part of the key because the harness draws the shared array from (rank, kind) and casts it to the dtype, whatever the name","bucket_fields":["rank","kind","dtype"],"claim":"Implementations sharing this entry name were each run on one shared input fixed by the positional (rank, kind, dtype) of their array arguments (the bucket). A cluster is the set whose recorded output digest (sha256 of the output rounded to 6 decimals) is identical. Identical values to six decimals on the shared input are agreement on those inputs, not a statement about the whole domain and not a substitution claim.","n_implementations_compared":6,"n_papers":8,"n_buckets":3,"n_distinct_outputs":6,"n_class_bearing":0,"not_compared":{"not_run_on_shared_input":{"n":1,"by_error":{"AssertionError":1}},"no_array_argument_ran_on_own_fixture_arguments_only":{"n":0,"n_papers":0,"recorded_shared_digest_equals_own_fixture_digest":0},"output_not_digested_non_numeric":{"n":0,"by_type":{}}},"withdrawn_excluded":0,"code_page":"/code/patchify","buckets":[{"bucket":[[4,"float","float32"]],"n_implementations_compared":3,"n_papers":5,"n_not_digested":0,"not_digested_by_type":{},"clusters":[{"output_sha":"477cda1d28ad8eef","size":1,"n_papers":4,"shape":[2,4,12],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[0.7231047749519348,-0.45303258299827576,-0.4213716387748718,0.6530793309211731,0.12553228437900543,1.020633339881897,1.1372957229614258,-0.7250184416770935,-0.6618722677230835,-0.19992724061012268,1.1514394283294678,1.982889175415039,1.4460861682891846,0.5928415060043335,-0.4836711883544922,1.0985400676727295,-1.463806390762329,-0.4854681193828583,-0.2714869976043701,-0.3975509703159332,0.2125764787197113,0.8319791555404663,1.4335219860076904,-1.2040232419967651,0.3433533310890198,0.22366678714752197,-0.21204684674739838,-0.13238386809825897,1.184694528579712,-1.479430913925171,-0.709074079990387,0.3742450773715973,0.022702597081661224,-0.4362029433250427,0.00391392083838582,-0.16384494304656982,-1.1905570030212402,-2.0680742263793945,-0.7425822019577026,-0.012713957577943802,-0.16907231509685516,1.2173826694488525,-2.665717124938965,0.895301342010498,0.3325777053833008,0.812962532043457,-0.4980470836162567,-1.246457576751709,1.0319796800613403,0.8440517783164978,-2.2168080806732178,0.47569993138313293,-1.0907533168792725,-0.08749820291996002,1.654322624206543,0.4846275746822357,0.7167379260063171,-0.6244865655899048,0.022118685767054558,1.2303640842437744,2.1016592979431152,0.7723703980445862,0.16540314257144928,-0.01877530850470066,2.0942370891571045,-0.8387367129325867,-2.408447742462158,3.1044223308563232,-1.5213911533355713,-0.21435445547103882,0.0736190527677536,1.0778614282608032,-1.3870023488998413,0.6060231924057007,0.22837327420711517,-2.00654673576355,0.28421318531036377,0.4391850531101227,-2.796109437942505,1.0927388668060303,0.49750959873199463,-0.7385192513465881,0.267061322927475,0.14785639941692352,-1.3687102794647217,0.5158193111419678,1.9725817441940308,-0.026417039334774017,-0.6696537733078003,-1.1686570644378662,-0.6348524689674377,0.6621701121330261,-1.3677366971969604,0.21286723017692566,0.2371496558189392,-0.28564757108688354],"values_recorded":96,"members":[{"code_sha256_prefix":"9cf076a2ae913f94","path":"libs/uvit.py","papers":["2302.10586","2310.13545","2209.12152","2402.05608"],"paper_pages":[{"arxiv_id":"2302.10586","page":"/paper/diffusion-models-and-semi-supervised-learners-1"},{"arxiv_id":"2310.13545","page":"/paper/scalelong-towards-more-stable-training-of-1"},{"arxiv_id":"2209.12152","page":"/paper/all-are-worth-words-a-vit-backbone-for-score"},{"arxiv_id":"2402.05608","page":"/paper/scalable-diffusion-models-with-state-space"}],"arg_sig_recorded":[["imgs",4,"float","float32"]],"scalar_args":{"patch_size":"2"},"class_bearing":false}]},{"output_sha":"c086aa44cd7a2705","size":1,"n_papers":3,"shape":[2,1,48],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[0.7231047749519348,-0.45303258299827576,-0.4213716387748718,0.6530793309211731,0.12553228437900543,1.020633339881897,1.4460861682891846,0.5928415060043335,-0.4836711883544922,1.0985400676727295,-1.463806390762329,-0.4854681193828583,1.1372957229614258,-0.7250184416770935,-0.6618722677230835,-0.19992724061012268,1.1514394283294678,1.982889175415039,-0.2714869976043701,-0.3975509703159332,0.2125764787197113,0.8319791555404663,1.4335219860076904,-1.2040232419967651,0.3433533310890198,0.22366678714752197,-0.21204684674739838,-0.13238386809825897,1.184694528579712,-1.479430913925171,-1.1905570030212402,-2.0680742263793945,-0.7425822019577026,-0.012713957577943802,-0.16907231509685516,1.2173826694488525,-0.709074079990387,0.3742450773715973,0.022702597081661224,-0.4362029433250427,0.00391392083838582,-0.16384494304656982,-2.665717124938965,0.895301342010498,0.3325777053833008,0.812962532043457,-0.4980470836162567,-1.246457576751709,1.0319796800613403,0.8440517783164978,-2.2168080806732178,0.47569993138313293,-1.0907533168792725,-0.08749820291996002,2.1016592979431152,0.7723703980445862,0.16540314257144928,-0.01877530850470066,2.0942370891571045,-0.8387367129325867,1.654322624206543,0.4846275746822357,0.7167379260063171,-0.6244865655899048,0.022118685767054558,1.2303640842437744,-2.408447742462158,3.1044223308563232,-1.5213911533355713,-0.21435445547103882,0.0736190527677536,1.0778614282608032,-1.3870023488998413,0.6060231924057007,0.22837327420711517,-2.00654673576355,0.28421318531036377,0.4391850531101227,-1.3687102794647217,0.5158193111419678,1.9725817441940308,-0.026417039334774017,-0.6696537733078003,-1.1686570644378662,-2.796109437942505,1.0927388668060303,0.49750959873199463,-0.7385192513465881,0.267061322927475,0.14785639941692352,-0.6348524689674377,0.6621701121330261,-1.3677366971969604,0.21286723017692566,0.2371496558189392,-0.28564757108688354],"values_recorded":96,"members":[{"code_sha256_prefix":"7a7de2a8e080f047","path":"libs/uvit.py","papers":["2010.11929","2302.10586","2310.13545"],"paper_pages":[{"arxiv_id":"2010.11929","page":"/paper/an-image-is-worth-16x16-words-transformers-1"},{"arxiv_id":"2302.10586","page":"/paper/diffusion-models-and-semi-supervised-learners-1"},{"arxiv_id":"2310.13545","page":"/paper/scalelong-towards-more-stable-training-of-1"}],"arg_sig_recorded":[["imgs",4,"float","float32"]],"scalar_args":{"patch_size":"4"},"class_bearing":false}]},{"output_sha":"12975c1e9e51945b","size":1,"n_papers":1,"shape":[2,4,12],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[0.7231047749519348,0.6530793309211731,1.1372957229614258,-0.19992724061012268,-0.45303258299827576,0.12553228437900543,-0.7250184416770935,1.1514394283294678,-0.4213716387748718,1.020633339881897,-0.6618722677230835,1.982889175415039,1.4460861682891846,1.0985400676727295,-0.2714869976043701,0.8319791555404663,0.5928415060043335,-1.463806390762329,-0.3975509703159332,1.4335219860076904,-0.4836711883544922,-0.4854681193828583,0.2125764787197113,-1.2040232419967651,0.3433533310890198,-0.13238386809825897,-0.709074079990387,-0.4362029433250427,0.22366678714752197,1.184694528579712,0.3742450773715973,0.00391392083838582,-0.21204684674739838,-1.479430913925171,0.022702597081661224,-0.16384494304656982,-1.1905570030212402,-0.012713957577943802,-2.665717124938965,0.812962532043457,-2.0680742263793945,-0.16907231509685516,0.895301342010498,-0.4980470836162567,-0.7425822019577026,1.2173826694488525,0.3325777053833008,-1.246457576751709,1.0319796800613403,0.47569993138313293,1.654322624206543,-0.6244865655899048,0.8440517783164978,-1.0907533168792725,0.4846275746822357,0.022118685767054558,-2.2168080806732178,-0.08749820291996002,0.7167379260063171,1.2303640842437744,2.1016592979431152,-0.01877530850470066,-2.408447742462158,-0.21435445547103882,0.7723703980445862,2.0942370891571045,3.1044223308563232,0.0736190527677536,0.16540314257144928,-0.8387367129325867,-1.5213911533355713,1.0778614282608032,-1.3870023488998413,-2.00654673576355,-2.796109437942505,-0.7385192513465881,0.6060231924057007,0.28421318531036377,1.0927388668060303,0.267061322927475,0.22837327420711517,0.4391850531101227,0.49750959873199463,0.14785639941692352,-1.3687102794647217,-0.026417039334774017,-0.6348524689674377,0.21286723017692566,0.5158193111419678,-0.6696537733078003,0.6621701121330261,0.2371496558189392,1.9725817441940308,-1.1686570644378662,-1.3677366971969604,-0.28564757108688354],"values_recorded":96,"members":[{"code_sha256_prefix":"49c15b51568e396b","path":"src/cv/vit/vit_torch.py","papers":["2010.11929"],"paper_pages":[{"arxiv_id":"2010.11929","page":"/paper/an-image-is-worth-16x16-words-transformers-1"}],"arg_sig_recorded":[["images",4,"float","float32"]],"scalar_args":{"n_patches":"2"},"class_bearing":false}]}]},{"bucket":[[5,"float","float32"]],"n_implementations_compared":2,"n_papers":2,"n_not_digested":0,"not_digested_by_type":{},"clusters":[{"output_sha":"89be171afeec29e2","size":1,"n_papers":1,"shape":[2,12,8],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[-1.1107560396194458,-1.1730422973632812,-1.153886079788208,1.6099485158920288,-0.8834818005561829,-0.3033652901649475,-0.7872069478034973,-1.1028218269348145,0.8985224962234497,-0.9597907662391663,1.6579723358154297,0.017496809363365173,0.2903594672679901,-0.34540775418281555,-1.0316343307495117,0.5321722030639648,1.6145302057266235,0.6805564165115356,-1.2984472513198853,1.4965091943740845,-1.1580840349197388,-1.738380789756775,1.2174726724624634,-0.7067435383796692,-0.14161428809165955,0.515856146812439,-0.2921791672706604,-0.32154542207717896,-1.5930107831954956,-1.0300383567810059,0.044205859303474426,-0.7658928036689758,-0.7862235307693481,0.028399042785167694,-2.3161141872406006,-0.06598131358623505,0.14232149720191956,0.1038346067070961,-0.4954170882701874,-0.9538744688034058,0.1333187073469162,0.23887701332569122,0.34575366973876953,-0.355526328086853,0.15009130537509918,0.11544095724821091,-0.8429698944091797,-0.3209018111228943,-1.4114540815353394,0.5484159588813782,-1.475331425666809,-0.9221066236495972,0.38093143701553345,-0.9863946437835693,-1.8141356706619263,-2.4891045093536377,0.9628362059593201,0.3624333143234253,0.17942270636558533,1.3358933925628662,-0.6426793336868286,1.2003166675567627,1.2347735166549683,-1.2195813655853271,1.08425772190094,0.19805815815925598,-0.500424861907959,-0.8479506373405457,-1.8440903425216675,-0.9599392414093018,-0.2089516520500183,-0.21852001547813416,-0.36485445499420166,-0.45970606803894043,0.4214843213558197,-0.501682460308075,-0.3962119221687317,1.7353484630584717,-0.38931897282600403,0.2524699866771698,-0.487968385219574,-0.5008582472801208,-0.7648671269416809,-0.0165925994515419,0.004794058855623007,-0.10023845732212067,-0.4212897717952728,-0.34519606828689575,-0.2785039246082306,-0.1769121289253235,-1.2450716495513916,-0.14889924228191376,0.15418283641338348,1.0964465141296387,-0.25530773401260376,-1.0466793775558472,0.03220515698194504,-2.0900726318359375,0.3003831207752228,0.028272826224565506,1.229662537574768,1.0642337799072266,-0.3466217517852783,0.8152093291282654,0.07432570308446884,-1.2040106058120728,2.224367618560791,-1.968330979347229,-0.14361454546451569,-0.5652943849563599,2.0826871395111084,-0.5413988828659058,0.08996745944023132,2.7164814472198486,0.9118784666061401,-0.1322486847639084,-0.45716461539268494,1.6674236059188843,1.051621913909912,-1.4645459651947021,0.48608702421188354,-1.3709510564804077,-0.9026029109954834,1.3064075708389282,0.3387507200241089,0.9185423851013184,1.6571323871612549,0.40030455589294434,0.9957132935523987,-0.4584314525127411,-0.47547414898872375,0.6714489459991455,1.1353662014007568,-1.0774542093276978,0.4497837722301483,-1.897004246711731,-0.04156797006726265,2.36010479927063,-1.1869113445281982,-1.6869542598724365,-0.6356520056724548,0.8571401834487915,0.6746817231178284,0.011369176208972931,0.4537210464477539,0.026012180373072624,0.7318887710571289,-0.6087607145309448,-1.2037216424942017,0.15681609511375427,-0.1616237759590149,-0.3745802938938141,0.5330355167388916,-1.0646568536758423,0.024492330849170685,0.8799611926078796,3.3869268894195557,-0.8109546899795532,0.27133822441101074,0.42707058787345886,-0.39796876907348633,1.6056129932403564,-0.6594845056533813,1.5907549858093262,-0.02053935080766678,-1.157633662223816,0.5572047233581543,0.35014471411705017,-2.014885902404785,-0.10445431619882584,-1.1461224555969238,0.7624952793121338,-0.195414736866951,-0.5806121230125427,0.2471310794353485,0.0405825637280941,-0.588148295879364,0.3018113970756531,-0.4178919494152069,-0.927975594997406,0.19126677513122559,0.024112114682793617,-1.2296181917190552,1.0587294101715088,1.3179566860198975,-0.29502859711647034,1.4699900150299072,0.3482152819633484,0.3617081344127655,-1.2479674816131592,0.5765359997749329,0.6441925168037415],"values_recorded":192,"members":[{"code_sha256_prefix":"18f75e876d5831d4","path":"UniLumos/UniLumos/src/schedulers/rectified_flow.py","papers":["2511.01678"],"paper_pages":[{"arxiv_id":"2511.01678","page":"/paper/arxiv-2511-01678"}],"arg_sig_recorded":[["x",5,"float","float32"]],"scalar_args":{"patch_size":"(1, 2, 2)"},"class_bearing":false}]},{"output_sha":"e811a39241138ff7","size":1,"n_papers":1,"shape":[2,2,2,16],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[-1.1107560396194458,-1.153886079788208,0.8985224962234497,1.6579723358154297,-0.8834818005561829,-0.7872069478034973,0.2903594672679901,-1.0316343307495117,-0.7862235307693481,-2.3161141872406006,0.1333187073469162,0.34575366973876953,0.14232149720191956,-0.4954170882701874,0.15009130537509918,-0.8429698944091797,1.6145302057266235,-1.2984472513198853,-0.14161428809165955,-0.2921791672706604,-1.1580840349197388,1.2174726724624634,-1.5930107831954956,0.044205859303474426,-1.4114540815353394,-1.475331425666809,0.9628362059593201,0.17942270636558533,0.38093143701553345,-1.8141356706619263,-0.6426793336868286,1.2347735166549683,-1.1730422973632812,1.6099485158920288,-0.9597907662391663,0.017496809363365173,-0.3033652901649475,-1.1028218269348145,-0.34540775418281555,0.5321722030639648,0.028399042785167694,-0.06598131358623505,0.23887701332569122,-0.355526328086853,0.1038346067070961,-0.9538744688034058,0.11544095724821091,-0.3209018111228943,0.6805564165115356,1.4965091943740845,0.515856146812439,-0.32154542207717896,-1.738380789756775,-0.7067435383796692,-1.0300383567810059,-0.7658928036689758,0.5484159588813782,-0.9221066236495972,0.3624333143234253,1.3358933925628662,-0.9863946437835693,-2.4891045093536377,1.2003166675567627,-1.2195813655853271,0.03220515698194504,0.3003831207752228,0.07432570308446884,2.224367618560791,1.229662537574768,-0.3466217517852783,-0.14361454546451569,2.0826871395111084,0.9957132935523987,-0.47547414898872375,-0.04156797006726265,-1.1869113445281982,1.1353662014007568,0.4497837722301483,-0.6356520056724548,0.6746817231178284,0.08996745944023132,0.9118784666061401,0.48608702421188354,-0.9026029109954834,-0.45716461539268494,1.051621913909912,0.3387507200241089,1.6571323871612549,0.4537210464477539,0.7318887710571289,0.5330355167388916,0.024492330849170685,-1.2037216424942017,-0.1616237759590149,3.3869268894195557,0.27133822441101074,-2.0900726318359375,0.028272826224565506,-1.2040106058120728,-1.968330979347229,1.0642337799072266,0.8152093291282654,-0.5652943849563599,-0.5413988828659058,-0.4584314525127411,0.6714489459991455,2.36010479927063,-1.6869542598724365,-1.0774542093276978,-1.897004246711731,0.8571401834487915,0.011369176208972931,2.7164814472198486,-0.1322486847639084,-1.3709510564804077,1.3064075708389282,1.6674236059188843,-1.4645459651947021,0.9185423851013184,0.40030455589294434,0.026012180373072624,-0.6087607145309448,-1.0646568536758423,0.8799611926078796,0.15681609511375427,-0.3745802938938141,-0.8109546899795532,0.42707058787345886],"values_recorded":128,"members":[{"code_sha256_prefix":"039179bb223e6c09","path":"lam/lam/modules/lam.py","papers":["2503.18938"],"paper_pages":[{"arxiv_id":"2503.18938","page":"/paper/adaworld-learning-adaptable-world-models-with"}],"arg_sig_recorded":[["videos",5,"float","float32"]],"scalar_args":{"size":"2"},"class_bearing":false}]}]},{"bucket":[[3,"float","float32"]],"n_implementations_compared":1,"n_papers":1,"n_not_digested":0,"not_digested_by_type":{},"clusters":[{"output_sha":"97ff8dd6438ff11f","size":1,"n_papers":1,"shape":[2,32],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":null,"members_with_recorded_values":1,"torch_reference_conventions_with_this_digest":[],"values":[-0.8931272625923157,-0.9571838974952698,1.682853102684021,1.8682522773742676,-1.2588046789169312,-1.1814329624176025,-0.2582058608531952,-0.8039284944534302,-2.139214038848877,-1.1923047304153442,0.011872420087456703,-0.8975064754486084,-0.848949134349823,-1.0145355463027954,-0.7722031474113464,-0.6859840750694275,1.8797812461853027,-0.33936411142349243,-0.7452988624572754,-0.0975174680352211,-0.08752579241991043,0.7487973570823669,0.7744670510292053,-0.9978419542312622,0.95430988073349,-1.271640658378601,0.9237498044967651,1.155332088470459,-0.7546214461326599,1.6535718441009521,-0.30625444650650024,-0.581495463848114,0.15099599957466125,0.9990944862365723,-1.434759497642517,0.6304919123649597,-0.34014570713043213,0.044029541313648224,-0.3811257779598236,1.7415422201156616,0.8366092443466187,0.9828868508338928,-0.16943085193634033,-0.14383146166801453,0.15168990194797516,0.38964250683784485,0.40691596269607544,0.9042900204658508,-0.5704304575920105,0.5280088782310486,1.1243221759796143,0.18848304450511932,-0.40352779626846313,-0.7085897922515869,0.9569169282913208,-0.9634317755699158,-1.0338436365127563,1.8763816356658936,1.2410037517547607,1.2408666610717773,-0.9114314913749695,-1.2724858522415161,1.836632490158081,-0.8599306344985962],"values_recorded":64,"members":[{"code_sha256_prefix":"06c91d3233a2f559","path":"modeling/bagel/bagel.py","papers":["2511.07222"],"paper_pages":[{"arxiv_id":"2511.07222","page":"/paper/arxiv-2511-07222"}],"arg_sig_recorded":[["image",3,"float","float32"]],"scalar_args":{"patch_size":"4"},"class_bearing":false}]}]}]}