{"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/path-level-network-transformation-for","title":"Path-Level Network Transformation for Efficient Architecture Search","arxiv_id":"1806.02639","date":"2018-06-07","proceeding":"ICML 2018 7","authors":["Han Cai","Jiacheng Yang","Wei-Nan Zhang","Song Han","Yong Yu"],"abstract":"We introduce a new function-preserving transformation for efficient neural\narchitecture search. This network transformation allows reusing previously\ntrained networks and existing successful architectures that improves sample\nefficiency. We aim to address the limitation of current network transformation\noperations that can only perform layer-level architecture modifications, such\nas adding (pruning) filters or inserting (removing) a layer, which fails to\nchange the topology of connection paths. Our proposed path-level transformation\noperations enable the meta-controller to modify the path topology of the given\nnetwork while keeping the merits of reusing weights, and thus allow efficiently\ndesigning effective structures with complex path topologies like Inception\nmodels. We further propose a bidirectional tree-structured reinforcement\nlearning meta-controller to explore a simple yet highly expressive\ntree-structured architecture space that can be viewed as a generalization of\nmulti-branch architectures. We experimented on the image classification\ndatasets with limited computational resources (about 200 GPU-hours), where we\nobserved improved parameter efficiency and better test results (97.70% test\naccuracy on CIFAR-10 with 14.3M parameters and 74.6% top-1 accuracy on ImageNet\nin the mobile setting), demonstrating the effectiveness and transferability of\nour designed architectures.","url_abs":"http://arxiv.org/abs/1806.02639v1","url_pdf":"http://arxiv.org/pdf/1806.02639v1.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":"path-level-network-transformation-for","repo_url":"https://github.com/han-cai/PathLevel-EAS","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"path-level-network-transformation-for","repo_url":"https://github.com/han-cai/EAS","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"path-level-network-transformation-for","repo_url":"https://github.com/han-cai/RL4AS_NetTrans","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":null,"task_name":"GPU"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"architecture-search","task_name":"Neural Architecture Search"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/architecture-search-on-cifar-10-image","task":"Neural Architecture Search","dataset":"CIFAR-10 Image Classification","model":"PathLevel EAS + c/o","rank_in_archive_order":9,"of":19,"metrics":{"Params":"14.3M","Percentage error":"2.30"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.02639","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.02639"}},"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/han-cai/PathLevel-EAS","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/han-cai/EAS","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/han-cai/RL4AS_NetTrans","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":2},"by_repo_kind":{"listed":{"samples":2,"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":"eef736bffae400ce","entry":"apply_noise","repo":"han-cai/EAS","repo_kind":"listed","path":"code/models/layers.py","file_url":"https://github.com/han-cai/EAS/blob/HEAD/code/models/layers.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"eef736bffae400ce"}},{"code_sha256_prefix":"9470c2923bc9415e","entry":"get_magnifier","repo":"han-cai/EAS","repo_kind":"listed","path":"code/models/layers.py","file_url":"https://github.com/han-cai/EAS/blob/HEAD/code/models/layers.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9470c2923bc9415e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}