{"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/get-mnist-dataloaders","entry":"get_mnist_dataloaders","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-25T09:33:49+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":5,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":5},"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":"2405.10284","paper":"/paper/quantum-vision-transformers-for-quark-gluon","title":"Quantum Vision Transformers for Quark-Gluon Classification","date":"2024-05-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"salcc/QuantumTransformers","path":"quantum_transformers/qmlperfcomp/torch_backend/data.py","file_url":"https://github.com/salcc/QuantumTransformers/blob/HEAD/quantum_transformers/qmlperfcomp/torch_backend/data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"6057b841ec3be6c2","mcp_get_code":{"code_sha256":"6057b841ec3be6c2"}},{"arxiv_id":"2403.07591","paper":"/paper/robustifying-and-boosting-training-free","title":"Robustifying and Boosting Training-Free Neural Architecture Search","date":"2024-03-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hzf1174/RoBoT","path":"foresight/dataset.py","file_url":"https://github.com/hzf1174/RoBoT/blob/HEAD/foresight/dataset.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"7491772a906c4046","mcp_get_code":{"code_sha256":"7491772a906c4046"}},{"arxiv_id":"2305.12396","paper":"/paper/joint-feature-and-differentiable-k-nn-graph","title":"Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy","date":"2023-05-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GhadaSokar/WAST","path":"utils.py","file_url":"https://github.com/GhadaSokar/WAST/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":"7e27d849c088883d","mcp_get_code":{"code_sha256":"7e27d849c088883d"}},{"arxiv_id":"1811.11212","paper":"/paper/self-supervised-generative-adversarial","title":"Self-Supervised GANs via Auxiliary Rotation Loss","date":"2018-11-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vandit15/Self-Supervised-Gans-Pytorch","path":"dataloaders.py","file_url":"https://github.com/vandit15/Self-Supervised-Gans-Pytorch/blob/HEAD/dataloaders.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e2092604fc016e70","mcp_get_code":{"code_sha256":"e2092604fc016e70"}},{"arxiv_id":"1804.00104","paper":"/paper/learning-disentangled-joint-continuous-and","title":"Learning Disentangled Joint Continuous and Discrete Representations","date":"2018-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Schlumberger/joint-vae","path":"utils/dataloaders.py","file_url":"https://github.com/Schlumberger/joint-vae/blob/HEAD/utils/dataloaders.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bdf803549274d512","mcp_get_code":{"code_sha256":"bdf803549274d512"}}]}