{"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/tensor2array","entry":"tensor2array","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":2,"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":5,"n_samples_ran":2,"n_samples_fingerprinted":1,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":1,"ran":1,"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":"2307.15139","paper":"/paper/online-clustered-codebook","title":"Online Clustered Codebook","date":"2023-07-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lyndonzheng/cvq-vae","path":"util.py","file_url":"https://github.com/lyndonzheng/cvq-vae/blob/HEAD/util.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0d6fa4426be1d4f0","mcp_get_code":{"code_sha256":"0d6fa4426be1d4f0"}},{"arxiv_id":"2005.11079","paper":"/paper/graph-random-neural-network","title":"Graph Random Neural Network for Semi-Supervised Learning on Graphs","date":"2020-05-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"junzhuang-code/graphss","path":"graphSS/models_SS.py","file_url":"https://github.com/junzhuang-code/graphss/blob/HEAD/graphSS/models_SS.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c05480a878ada1cf","mcp_get_code":{"code_sha256":"c05480a878ada1cf"}},{"arxiv_id":"1911.10444","paper":"/paper/normal-assisted-stereo-depth-estimation","title":"Normal Assisted Stereo Depth Estimation","date":"2019-11-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"udaykusupati/Normal-Assisted-Stereo","path":"utils.py","file_url":"https://github.com/udaykusupati/Normal-Assisted-Stereo/blob/HEAD/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1dea398d0e1f7446","mcp_get_code":{"code_sha256":"1dea398d0e1f7446"}},{"arxiv_id":"1905.00538","paper":"/paper/dpsnet-end-to-end-deep-plane-sweep-stereo-1","title":"DPSNet: End-to-end Deep Plane Sweep Stereo","date":"2019-05-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sunghoonim/DPSNet","path":"utils.py","file_url":"https://github.com/sunghoonim/DPSNet/blob/HEAD/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e5ca72bb116ddd00","mcp_get_code":{"code_sha256":"e5ca72bb116ddd00"}},{"arxiv_id":"1904.06397","paper":"/paper/multi-view-stereo-by-temporal-nonparametric","title":"Multi-View Stereo by Temporal Nonparametric Fusion","date":"2019-04-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"AaltoML/GP-MVS","path":"utils.py","file_url":"https://github.com/AaltoML/GP-MVS/blob/HEAD/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3b2cabd11b6ea325","mcp_get_code":{"code_sha256":"3b2cabd11b6ea325"}}]}