{"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/resmlp-feedforward-networks-for-image","title":"ResMLP: Feedforward networks for image classification with data-efficient training","arxiv_id":"2105.03404","date":"2021-05-07","proceeding":"NeurIPS 2021 12","authors":["Hugo Touvron","Piotr Bojanowski","Mathilde Caron","Matthieu Cord","Alaaeldin El-Nouby","Edouard Grave","Gautier Izacard","Armand Joulin","Gabriel Synnaeve","Jakob Verbeek","Hervé Jégou"],"abstract":"We present ResMLP, an architecture built entirely upon multi-layer perceptrons for image classification. It is a simple residual network that alternates (i) a linear layer in which image patches interact, independently and identically across channels, and (ii) a two-layer feed-forward network in which channels interact independently per patch. When trained with a modern training strategy using heavy data-augmentation and optionally distillation, it attains surprisingly good accuracy/complexity trade-offs on ImageNet. We also train ResMLP models in a self-supervised setup, to further remove priors from employing a labelled dataset. Finally, by adapting our model to machine translation we achieve surprisingly good results. We share pre-trained models and our code based on the Timm library.","url_abs":"https://arxiv.org/abs/2105.03404v2","url_pdf":"https://arxiv.org/pdf/2105.03404v2.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":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/facebookresearch/deit","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/rwightman/pytorch-image-models","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/IMvision12/keras-vision-models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/Mayurji/Image-Classification-PyTorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/jaketae/res-mlp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/lalithjets/surgical_vqa","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/leaderj1001/Bag-of-MLP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/liuruiyang98/Jittor-MLP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"jax","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/lucidrains/res-mlp-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/martinsbruveris/tensorflow-image-models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/rishikksh20/ResMLP-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/xmu-xiaoma666/External-Attention-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/BR-IDL/PaddleViT/blob/main/image_classification/ResMLP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/MindCode-4/code-13/tree/main/res_mlp_ms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/MindCode-4/code-8/tree/main/res_mlp_ms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/mlp_family","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/megvii-research/basecls/tree/main/zoo/public/resmlp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://github.com/yeyinthtoon/tf2-resmlp","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"resmlp-feedforward-networks-for-image","repo_url":"https://gitlab.com/birder/birder","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"fine-grained-image-classification","task_name":"Fine-Grained Image Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"self-supervised-image-classification","task_name":"Self-Supervised Image Classification"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[{"method_slug":"affine-operator","method_name":"Affine Operator"},{"method_slug":"class-mlp","method_name":"Class-MLP"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"feedforward-network","method_name":"Feedforward Network"},{"method_slug":"layerscale","method_name":"LayerScale"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"resmlp","method_name":"ResMLP"},{"method_slug":"residual-connection","method_name":"Residual Connection"}],"datasets_introduced":[],"methods_introduced":[{"slug":"class-mlp","name":"Class-MLP","full_name":"Class-MLP"},{"slug":"resmlp","name":"ResMLP","full_name":"Residual Multi-Layer Perceptrons"}],"results":[{"leaderboard":"/sota/fine-grained-image-classification-on-oxford","task":"Fine-Grained Image Classification","dataset":"Oxford 102 Flowers","model":"ResMLP-24","rank_in_archive_order":17,"of":25,"metrics":{"Accuracy":"97.9%"},"uses_additional_data":true},{"leaderboard":"/sota/fine-grained-image-classification-on-oxford","task":"Fine-Grained Image Classification","dataset":"Oxford 102 Flowers","model":"ResMLP-12","rank_in_archive_order":19,"of":25,"metrics":{"Accuracy":"97.4%"},"uses_additional_data":true},{"leaderboard":"/sota/fine-grained-image-classification-on-stanford","task":"Fine-Grained Image Classification","dataset":"Stanford Cars","model":"ResMLP-24","rank_in_archive_order":79,"of":83,"metrics":{"Accuracy":"89.5%"},"uses_additional_data":false},{"leaderboard":"/sota/fine-grained-image-classification-on-stanford","task":"Fine-Grained Image Classification","dataset":"Stanford Cars","model":"ResMLP-12","rank_in_archive_order":81,"of":83,"metrics":{"Accuracy":"84.6%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-cifar-100","task":"Image Classification","dataset":"CIFAR-100","model":"ResMLP-24","rank_in_archive_order":29,"of":211,"metrics":{"Percentage correct":"89.5"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-cifar-100","task":"Image Classification","dataset":"CIFAR-100","model":"ResMLP-12","rank_in_archive_order":47,"of":211,"metrics":{"Percentage correct":"87.0"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-certificate","task":"Image Classification","dataset":"Certificate Verification","model":"ResMLP-24","rank_in_archive_order":1,"of":2,"metrics":{"Percentage correct":"98.7","Top-1 Accuracy":"98.7"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-certificate","task":"Image Classification","dataset":"Certificate Verification","model":"ResMLP-12","rank_in_archive_order":2,"of":2,"metrics":{"Percentage correct":"98.1","Top-1 Accuracy":"98.1"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-flowers-102","task":"Image Classification","dataset":"Flowers-102","model":"ResMLP24","rank_in_archive_order":32,"of":52,"metrics":{"Accuracy":"97.9"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-flowers-102","task":"Image Classification","dataset":"Flowers-102","model":"ResMLP12","rank_in_archive_order":38,"of":52,"metrics":{"Accuracy":"97.4"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-B24/8","rank_in_archive_order":418,"of":1060,"metrics":{"Number of params":"116M","Top 1 Accuracy":"83.6%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-S24","rank_in_archive_order":683,"of":1060,"metrics":{"GFLOPs":"6","Number of params":"30M","Top 1 Accuracy":"80.8%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-36","rank_in_archive_order":746,"of":1060,"metrics":{"Number of params":"45M","Top 1 Accuracy":"79.7%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-24","rank_in_archive_order":757,"of":1060,"metrics":{"Top 1 Accuracy":"79.4%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-12 (distilled, class-MLP)","rank_in_archive_order":822,"of":1060,"metrics":{"GFLOPs":"3","Number of params":"17.7M","Top 1 Accuracy":"78.6%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet","task":"Image Classification","dataset":"ImageNet","model":"ResMLP-S12","rank_in_archive_order":864,"of":1060,"metrics":{"Number of params":"15.4M","Top 1 Accuracy":"77.8%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-real","task":"Image Classification","dataset":"ImageNet ReaL","model":"ResMLP-36","rank_in_archive_order":41,"of":57,"metrics":{"Accuracy":"85.6%","Params":"45M"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-real","task":"Image Classification","dataset":"ImageNet ReaL","model":"ResMLP-24","rank_in_archive_order":42,"of":57,"metrics":{"Accuracy":"85.3%","Params":"30M"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-real","task":"Image Classification","dataset":"ImageNet ReaL","model":"ResMLP-12","rank_in_archive_order":44,"of":57,"metrics":{"Accuracy":"84.6%","Params":"15M"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-real","task":"Image Classification","dataset":"ImageNet ReaL","model":"ResMLP-B24/8 (22k)","rank_in_archive_order":57,"of":57,"metrics":{"Top 1 Accuracy":"84.4%"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-v2","task":"Image Classification","dataset":"ImageNet V2","model":"ResMLP-B24/8 22k","rank_in_archive_order":18,"of":33,"metrics":{"Top 1 Accuracy":"74.2"},"uses_additional_data":true},{"leaderboard":"/sota/image-classification-on-imagenet-v2","task":"Image Classification","dataset":"ImageNet V2","model":"ResMLP-B24/8","rank_in_archive_order":20,"of":33,"metrics":{"Top 1 Accuracy":"73.4"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-v2","task":"Image Classification","dataset":"ImageNet V2","model":"ResMLP-S24/16","rank_in_archive_order":25,"of":33,"metrics":{"Top 1 Accuracy":"69.8"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-imagenet-v2","task":"Image Classification","dataset":"ImageNet V2","model":"ResMLP-S12/16","rank_in_archive_order":31,"of":33,"metrics":{"Top 1 Accuracy":"66.0"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-stanford-cars","task":"Image Classification","dataset":"Stanford Cars","model":"ResMLP-24","rank_in_archive_order":16,"of":24,"metrics":{"Accuracy":"89.5"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-stanford-cars","task":"Image Classification","dataset":"Stanford Cars","model":"ResMLP-12","rank_in_archive_order":22,"of":24,"metrics":{"Accuracy":"84.6"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-inaturalist-2018","task":"Image Classification","dataset":"iNaturalist 2018","model":"ResMLP-24","rank_in_archive_order":51,"of":60,"metrics":{"Top-1 Accuracy":"64.3"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-inaturalist-2018","task":"Image Classification","dataset":"iNaturalist 2018","model":"ResMLP-12","rank_in_archive_order":55,"of":60,"metrics":{"Top-1 Accuracy":"60.2"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-inaturalist-2019","task":"Image Classification","dataset":"iNaturalist 2019","model":"ResMLP-24","rank_in_archive_order":17,"of":22,"metrics":{"Top-1 Accuracy":"72.5"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-inaturalist-2019","task":"Image Classification","dataset":"iNaturalist 2019","model":"ResMLP-12","rank_in_archive_order":19,"of":22,"metrics":{"Top-1 Accuracy":"71.0"},"uses_additional_data":false},{"leaderboard":"/sota/machine-translation-on-wmt2014-english-french","task":"Machine Translation","dataset":"WMT2014 English-French","model":"ResMLP-12","rank_in_archive_order":30,"of":57,"metrics":{"BLEU score":"40.6"},"uses_additional_data":false},{"leaderboard":"/sota/machine-translation-on-wmt2014-english-french","task":"Machine Translation","dataset":"WMT2014 English-French","model":"ResMLP-6","rank_in_archive_order":34,"of":57,"metrics":{"BLEU score":"40.3"},"uses_additional_data":false},{"leaderboard":"/sota/machine-translation-on-wmt2014-english-german","task":"Machine Translation","dataset":"WMT2014 English-German","model":"ResMLP-12","rank_in_archive_order":55,"of":91,"metrics":{"BLEU score":"26.8"},"uses_additional_data":false},{"leaderboard":"/sota/machine-translation-on-wmt2014-english-german","task":"Machine Translation","dataset":"WMT2014 English-German","model":"ResMLP-6","rank_in_archive_order":59,"of":91,"metrics":{"BLEU score":"26.4"},"uses_additional_data":false},{"leaderboard":"/sota/self-supervised-image-classification-on","task":"Self-Supervised Image Classification","dataset":"ImageNet","model":"DINO (ResMLP-24)","rank_in_archive_order":93,"of":144,"metrics":{"Number of Params":"30M","Top 1 Accuracy":"72.8%"},"uses_additional_data":false},{"leaderboard":"/sota/self-supervised-image-classification-on","task":"Self-Supervised Image Classification","dataset":"ImageNet","model":"DINO (ResMLP-12)","rank_in_archive_order":109,"of":144,"metrics":{"Number of Params":"15M","Top 1 Accuracy":"67.5%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2105.03404","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.03404"}},"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/rwightman/pytorch-image-models","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/facebookresearch/deit","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/rishikksh20/ResMLP-pytorch","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lucidrains/res-mlp-pytorch","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/lalithjets/surgical_vqa","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/liuruiyang98/Jittor-MLP","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/BR-IDL/PaddleViT/blob/main/image_classification/ResMLP","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/martinsbruveris/tensorflow-image-models","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/IMvision12/keras-vision-models","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/yeyinthtoon/tf2-resmlp","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/MindCode-4/code-13/tree/main/res_mlp_ms","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://gitlab.com/birder/birder","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/mlp_family","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Mayurji/Image-Classification-PyTorch","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/megvii-research/basecls/tree/main/zoo/public/resmlp","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/xmu-xiaoma666/External-Attention-pytorch","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jaketae/res-mlp","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/leaderj1001/Bag-of-MLP","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/MindCode-4/code-8/tree/main/res_mlp_ms","reach":null}],"summary":{"ran_honours":1,"ran_violates":1,"unverified":5},"by_repo_kind":{"listed":{"samples":7,"ran":2,"repositories":4}},"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":"27cbea18b00696e9","entry":"check_sizes","repo":"jaketae/res-mlp","repo_kind":"listed","path":"res_mlp/core.py","file_url":"https://github.com/jaketae/res-mlp/blob/HEAD/res_mlp/core.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"27cbea18b00696e9"}},{"code_sha256_prefix":"e6f9d3b5ad66ee20","entry":"pair","repo":"lucidrains/res-mlp-pytorch","repo_kind":"listed","path":"res_mlp_pytorch/res_mlp_pytorch.py","file_url":"https://github.com/lucidrains/res-mlp-pytorch/blob/HEAD/res_mlp_pytorch/res_mlp_pytorch.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e6f9d3b5ad66ee20"}},{"code_sha256_prefix":"c5a2d135cecde44d","entry":"PatchEmbed","repo":"yeyinthtoon/tf2-resmlp","repo_kind":"listed","path":"resmlp/layers.py","file_url":"https://github.com/yeyinthtoon/tf2-resmlp/blob/HEAD/resmlp/layers.py","link_basis":"harvester_set","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":"c5a2d135cecde44d"}},{"code_sha256_prefix":"6a660e5991846119","entry":"adjust_block_compatibility","repo":"megvii-research/basecls","repo_kind":"listed","path":"basecls/layers/wrapper.py","file_url":"https://github.com/megvii-research/basecls/blob/HEAD/basecls/layers/wrapper.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":"6a660e5991846119"}},{"code_sha256_prefix":"3099f730f63abb47","entry":"layers_scale_mlp_blocks","repo":"yeyinthtoon/tf2-resmlp","repo_kind":"listed","path":"resmlp/resmlp.py","file_url":"https://github.com/yeyinthtoon/tf2-resmlp/blob/HEAD/resmlp/resmlp.py","link_basis":"harvester_set","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":"3099f730f63abb47"}},{"code_sha256_prefix":"6c615e583ce7944d","entry":"mlp_block","repo":"yeyinthtoon/tf2-resmlp","repo_kind":"listed","path":"resmlp/resmlp.py","file_url":"https://github.com/yeyinthtoon/tf2-resmlp/blob/HEAD/resmlp/resmlp.py","link_basis":"harvester_set","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":"6c615e583ce7944d"}},{"code_sha256_prefix":"87c6692221a5e172","entry":"resmlp","repo":"yeyinthtoon/tf2-resmlp","repo_kind":"listed","path":"resmlp/resmlp.py","file_url":"https://github.com/yeyinthtoon/tf2-resmlp/blob/HEAD/resmlp/resmlp.py","link_basis":"harvester_set","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":"87c6692221a5e172"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}