{"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":"/paper/prior-guided-one-shot-neural-architecture","title":"Prior-Guided One-shot Neural Architecture Search","arxiv_id":"2206.13329","date":"2022-06-27","proceeding":null,"authors":["Peijie Dong","Xin Niu","Lujun Li","Linzhen Xie","Wenbin Zou","Tian Ye","Zimian Wei","Hengyue Pan"],"abstract":"Neural architecture search methods seek optimal candidates with efficient weight-sharing supernet training. However, recent studies indicate poor ranking consistency about the performance between stand-alone architectures and shared-weight networks. In this paper, we present Prior-Guided One-shot NAS (PGONAS) to strengthen the ranking correlation of supernets. Specifically, we first explore the effect of activation functions and propose a balanced sampling strategy based on the Sandwich Rule to alleviate weight coupling in the supernet. Then, FLOPs and Zen-Score are adopted to guide the training of supernet with ranking correlation loss. Our PGONAS ranks 3rd place in the supernet Track Track of CVPR2022 Second lightweight NAS challenge. Code is available in https://github.com/pprp/CVPR2022-NAS?competition-Track1-3th-solution.","url_abs":"https://arxiv.org/abs/2206.13329v1","url_pdf":"https://arxiv.org/pdf/2206.13329v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"prior-guided-one-shot-neural-architecture","repo_url":"https://github.com/pprp/CVPR2022-NAS-competition-Track1-3th-solution","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"architecture-search","task_name":"Neural Architecture Search"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2206.13329","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.13329"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/pprp/CVPR2022-NAS-competition-Track1-3th-solution","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":3},"by_repo_kind":{"official":{"samples":3,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"b3570c8b9c3a3b4f","entry":"check_search_space","repo":"pprp/CVPR2022-NAS-competition-Track1-3th-solution","repo_kind":"official","path":"paddleslim/nas/ofa/get_sub_model.py","file_url":"https://github.com/pprp/CVPR2022-NAS-competition-Track1-3th-solution/blob/HEAD/paddleslim/nas/ofa/get_sub_model.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"b3570c8b9c3a3b4f"}},{"code_sha256_prefix":"703c0a73cd86bd8a","entry":"get_prune_params_config","repo":"pprp/CVPR2022-NAS-competition-Track1-3th-solution","repo_kind":"official","path":"paddleslim/nas/ofa/get_sub_model.py","file_url":"https://github.com/pprp/CVPR2022-NAS-competition-Track1-3th-solution/blob/HEAD/paddleslim/nas/ofa/get_sub_model.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"703c0a73cd86bd8a"}},{"code_sha256_prefix":"61ad37c40aee8672","entry":"make_divisible","repo":"pprp/CVPR2022-NAS-competition-Track1-3th-solution","repo_kind":"official","path":"model.py","file_url":"https://github.com/pprp/CVPR2022-NAS-competition-Track1-3th-solution/blob/HEAD/model.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"61ad37c40aee8672"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}