{"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/rope","entry":"rope","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":4,"n_papers":5,"n_buckets":1,"n_distinct_outputs":1,"n_class_bearing":0,"not_compared":{"not_run_on_shared_input":{"n":0,"by_error":{}},"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/rope","buckets":[{"bucket":[[2,"float","float64"]],"n_implementations_compared":4,"n_papers":5,"n_not_digested":0,"not_digested_by_type":{},"clusters":[{"output_sha":"afce5d7b8ad38ece","size":4,"n_papers":5,"shape":[4,8,2,2,2],"dtype":"float32","type":"Tensor","finite":true,"max_difference_among_recorded_values":0.0,"members_with_recorded_values":4,"torch_reference_conventions_with_this_digest":[],"values":[-0.2297612428665161,-0.9732470512390137,0.9732470512390137,-0.2297612428665161,0.9998375177383423,-0.018025310710072517,0.018025310710072517,0.9998375177383423,0.03701161593198776,0.9993148446083069,-0.9993148446083069,0.03701161593198776,0.9998824000358582,0.015337160788476467,-0.015337160788476467,0.9998824000358582,0.8888105750083923,-0.45827481150627136,0.45827481150627136,0.8888105750083923,0.9999886751174927,-0.0047605144791305065,0.0047605144791305065,0.9999886751174927,0.7706810832023621,0.637221097946167,-0.637221097946167,0.7706810832023621,0.9999761581420898,0.006908815819770098,-0.006908815819770098,0.9999761581420898,0.6193753480911255,0.7850949764251709,-0.7850949764251709,0.6193753480911255,0.9999592304229736,0.00902837235480547,-0.00902837235480547,0.9999592304229736,0.5144147872924805,0.8575415015220642,-0.8575415015220642,0.5144147872924805,0.9999468922615051,0.010304530151188374,-0.010304530151188374,0.9999468922615051,0.7882964611053467,0.6152956485748291,-0.6152956485748291,0.7882964611053467,0.9999780654907227,0.006627560593187809,-0.006627560593187809,0.9999780654907227,0.8403383493423462,-0.5420622229576111,0.5420622229576111,0.8403383493423462,0.9999836087226868,-0.005728860851377249,0.005728860851377249,0.9999836087226868,0.868377149105072,-0.4959043562412262,0.4959043562412262,0.868377149105072,0.9999865293502808,-0.005188736133277416,0.005188736133277416,0.9999865293502808,0.5742196440696716,-0.8187012672424316,0.8187012672424316,0.5742196440696716,0.9999539852142334,-0.009591309353709221,0.009591309353709221,0.9999539852142334,0.9221479296684265,0.3868374526500702,-0.3868374526500702,0.9221479296684265,0.9999921321868896,0.003971985075622797,-0.003971985075622797,0.9999921321868896,0.002448145067319274,0.9999970197677612,-0.9999970197677612,0.002448145067319274,0.9998770356178284,0.01568283885717392,-0.01568283885717392,0.9998770356178284,0.9586617350578308,0.28454819321632385,-0.28454819321632385,0.9586617350578308,0.9999958276748657,0.0028853469993919134,-0.0028853469993919134,0.9999958276748657,-0.6825985312461853,-0.7307935357093811,0.7307935357093811,-0.6825985312461853,0.9997304081916809,-0.023219002410769463,0.023219002410769463,0.9997304081916809,0.8703991174697876,0.4923468232154846,-0.4923468232154846,0.8703991174697876,0.9999867677688599,0.005147817078977823,-0.005147817078977823,0.9999867677688599,0.8522481322288513,-0.5231378078460693,0.5231378078460693,0.8522481322288513,0.999984860420227,-0.005505257751792669,0.005505257751792669,0.999984860420227,0.9977966547012329,-0.0663466677069664,0.0663466677069664,0.9977966547012329,0.9999997615814209,-0.0006639543571509421,0.0006639543571509421,0.9999997615814209,-0.052055660635232925,0.9986441731452942,-0.9986441731452942,-0.052055660635232925,0.9998683333396912,0.016228042542934418,-0.016228042542934418,0.9998683333396912,0.9080835580825806,-0.4187890887260437,0.4187890887260437,0.9080835580825806,0.9999906420707703,-0.004321100655943155,0.004321100655943155,0.9999906420707703,0.9186344742774963,0.3951084315776825,-0.3951084315776825,0.9186344742774963,0.999991774559021,0.00406184745952487,-0.00406184745952487,0.999991774559021,0.9997447729110718,0.022592302411794662,-0.022592302411794662,0.9997447729110718,1.0,0.0002259422471979633,-0.0002259422471979633,1.0,0.3802013099193573,0.9249037504196167,-0.9249037504196167,0.3802013099193573,0.9999302625656128,0.011807549744844437,-0.011807549744844437,0.9999302625656128,0.8593146204948425,0.5114473700523376,-0.5114473700523376,0.8593146204948425,0.9999855756759644,0.005368656478822231,-0.005368656478822231,0.9999855756759644,0.5539674162864685,-0.832538366317749,0.832538366317749,0.5539674162864685,0.9999516010284424,-0.009836583398282528,0.009836583398282528,0.9999516010284424,0.6998471617698669,0.714292585849762,-0.714292585849762,0.6998471617698669,0.9999683499336243,0.007956043817102909,-0.007956043817102909,0.9999683499336243,0.9075958728790283,-0.4198448956012726,0.4198448956012726,0.9075958728790283,0.9999906420707703,-0.004332730546593666,0.004332730546593666,0.9999906420707703,0.5857608914375305,-0.8104839324951172,0.8104839324951172,0.5857608914375305,0.9999553561210632,-0.009449637494981289,0.009449637494981289,0.9999553561210632,0.5254790782928467,-0.8508065342903137,0.8508065342903137,0.5254790782928467,0.9999482035636902,-0.0101750073954463,0.0101750073954463,0.9999482035636902,0.33820661902427673,0.9410718679428101,-0.9410718679428101,0.33820661902427673,0.999924898147583,0.012257550843060017,-0.012257550843060017,0.999924898147583,0.2922497093677521,-0.9563420414924622,0.9563420414924622,0.2922497093677521,0.9999188184738159,-0.012741833925247192,0.012741833925247192,0.9999188184738159,0.24602246284484863,0.9692641496658325,-0.9692641496658325,0.24602246284484863,0.9999125599861145,0.013221833854913712,-0.013221833854913712,0.9999125599861145,0.8286475539207458,0.5597707033157349,-0.5597707033157349,0.8286475539207458,0.9999823570251465,0.005941056180745363,-0.005941056180745363,0.9999823570251465],"values_recorded":256,"members":[{"code_sha256_prefix":"17724d4203fa5863","path":"modeling/restok.py","papers":["2412.07517","2601.03955"],"paper_pages":[{"arxiv_id":"2412.07517","page":"/paper/fireflow-fast-inversion-of-rectified-flow-for"},{"arxiv_id":"2601.03955","page":"/paper/arxiv-2601-03955"}],"arg_sig_recorded":[["pos",2,"float","float64"]],"scalar_args":{"dim":"4","theta":"10000"},"class_bearing":false},{"code_sha256_prefix":"002c583990a22f88","path":"src/flux/sampling.py","papers":["2606.17584"],"paper_pages":[{"arxiv_id":"2606.17584","page":"/paper/arxiv-2606-17584"}],"arg_sig_recorded":[["pos",2,"float","float64"]],"scalar_args":{"dim":"4","theta":"10000"},"class_bearing":false},{"code_sha256_prefix":"16c24bf237fed814","path":"models/kv_edit.py","papers":["2502.17363"],"paper_pages":[{"arxiv_id":"2502.17363","page":"/paper/kv-edit-training-free-image-editing-for"}],"arg_sig_recorded":[["pos",2,"float","float64"]],"scalar_args":{"dim":"4","theta":"10000"},"class_bearing":false},{"code_sha256_prefix":"6d4efcd033e6cec0","path":"library/flux_models.py","papers":["2502.01105"],"paper_pages":[{"arxiv_id":"2502.01105","page":"/paper/layertracer-cognitive-aligned-layered-svg"}],"arg_sig_recorded":[["pos",2,"float","float64"]],"scalar_args":{"dim":"4","theta":"10000"},"class_bearing":false}]}]}]}