├── .github └── workflows │ └── python-publish.yml ├── .gitignore ├── LICENSE ├── README.md ├── res_mlp_pytorch ├── __init__.py └── res_mlp_pytorch.py ├── resmlp.png └── setup.py /.github/workflows/python-publish.yml: -------------------------------------------------------------------------------- 1 | # This workflow will upload a Python Package using Twine when a release is created 2 | # For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries 3 | 4 | name: Upload Python Package 5 | 6 | on: 7 | release: 8 | types: [created] 9 | 10 | jobs: 11 | deploy: 12 | 13 | runs-on: ubuntu-latest 14 | 15 | steps: 16 | - uses: actions/checkout@v2 17 | - name: Set up Python 18 | uses: actions/setup-python@v2 19 | with: 20 | python-version: '3.x' 21 | - name: Install dependencies 22 | run: | 23 | python -m pip install --upgrade pip 24 | pip install setuptools wheel twine 25 | - name: Build and publish 26 | env: 27 | TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }} 28 | TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }} 29 | run: | 30 | python setup.py sdist bdist_wheel 31 | twine upload dist/* 32 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 Phil Wang 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | ## ResMLP - Pytorch 4 | 5 | Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch 6 | 7 | ## Install 8 | 9 | ```bash 10 | $ pip install res-mlp-pytorch 11 | ``` 12 | 13 | ## Usage 14 | 15 | ```python 16 | import torch 17 | from res_mlp_pytorch import ResMLP 18 | 19 | model = ResMLP( 20 | image_size = 256, 21 | patch_size = 16, 22 | dim = 512, 23 | depth = 12, 24 | num_classes = 1000 25 | ) 26 | 27 | img = torch.randn(1, 3, 256, 256) 28 | pred = model(img) # (1, 1000) 29 | ``` 30 | 31 | Rectangular image 32 | 33 | ```python 34 | import torch 35 | from res_mlp_pytorch import ResMLP 36 | 37 | model = ResMLP( 38 | image_size = (128, 256), # (128 x 256) 39 | patch_size = 16, 40 | dim = 512, 41 | depth = 12, 42 | num_classes = 1000 43 | ) 44 | 45 | img = torch.randn(1, 3, 128, 256) 46 | pred = model(img) # (1, 1000) 47 | ``` 48 | 49 | ## Citations 50 | 51 | ```bibtex 52 | @misc{touvron2021resmlp, 53 | title = {ResMLP: Feedforward networks for image classification with data-efficient training}, 54 | author = {Hugo Touvron and Piotr Bojanowski and Mathilde Caron and Matthieu Cord and Alaaeldin El-Nouby and Edouard Grave and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Hervé Jégou}, 55 | year = {2021}, 56 | eprint = {2105.03404}, 57 | archivePrefix = {arXiv}, 58 | primaryClass = {cs.CV} 59 | } 60 | ``` 61 | -------------------------------------------------------------------------------- /res_mlp_pytorch/__init__.py: -------------------------------------------------------------------------------- 1 | from res_mlp_pytorch.res_mlp_pytorch import ResMLP 2 | -------------------------------------------------------------------------------- /res_mlp_pytorch/res_mlp_pytorch.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from torch import nn, einsum 3 | from einops.layers.torch import Rearrange, Reduce 4 | 5 | # helpers 6 | 7 | def pair(val): 8 | return (val, val) if not isinstance(val, tuple) else val 9 | 10 | # classes 11 | 12 | class Affine(nn.Module): 13 | def __init__(self, dim): 14 | super().__init__() 15 | self.g = nn.Parameter(torch.ones(1, 1, dim)) 16 | self.b = nn.Parameter(torch.zeros(1, 1, dim)) 17 | 18 | def forward(self, x): 19 | return x * self.g + self.b 20 | 21 | class PreAffinePostLayerScale(nn.Module): # https://arxiv.org/abs/2103.17239 22 | def __init__(self, dim, depth, fn): 23 | super().__init__() 24 | if depth <= 18: 25 | init_eps = 0.1 26 | elif depth > 18 and depth <= 24: 27 | init_eps = 1e-5 28 | else: 29 | init_eps = 1e-6 30 | 31 | scale = torch.zeros(1, 1, dim).fill_(init_eps) 32 | self.scale = nn.Parameter(scale) 33 | self.affine = Affine(dim) 34 | self.fn = fn 35 | 36 | def forward(self, x): 37 | return self.fn(self.affine(x)) * self.scale + x 38 | 39 | def ResMLP(*, image_size, patch_size, dim, depth, num_classes, expansion_factor = 4): 40 | image_height, image_width = pair(image_size) 41 | assert (image_height % patch_size) == 0 and (image_width % patch_size) == 0, 'image height and width must be divisible by patch size' 42 | num_patches = (image_height // patch_size) * (image_width // patch_size) 43 | wrapper = lambda i, fn: PreAffinePostLayerScale(dim, i + 1, fn) 44 | 45 | return nn.Sequential( 46 | Rearrange('b c (h p1) (w p2) -> b (h w) (p1 p2 c)', p1 = patch_size, p2 = patch_size), 47 | nn.Linear((patch_size ** 2) * 3, dim), 48 | *[nn.Sequential( 49 | wrapper(i, nn.Conv1d(num_patches, num_patches, 1)), 50 | wrapper(i, nn.Sequential( 51 | nn.Linear(dim, dim * expansion_factor), 52 | nn.GELU(), 53 | nn.Linear(dim * expansion_factor, dim) 54 | )) 55 | ) for i in range(depth)], 56 | Affine(dim), 57 | Reduce('b n c -> b c', 'mean'), 58 | nn.Linear(dim, num_classes) 59 | ) 60 | -------------------------------------------------------------------------------- /resmlp.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lucidrains/res-mlp-pytorch/562814a406cc418bdb4710aa3bdc569206ac171b/resmlp.png -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup, find_packages 2 | 3 | setup( 4 | name = 'res-mlp-pytorch', 5 | packages = find_packages(exclude=[]), 6 | version = '0.0.6', 7 | license='MIT', 8 | description = 'ResMLP - Pytorch', 9 | author = 'Phil Wang', 10 | author_email = 'lucidrains@gmail.com', 11 | url = 'https://github.com/lucidrains/res-mlp-pytorch', 12 | keywords = [ 13 | 'artificial intelligence', 14 | 'deep learning', 15 | 'image recognition' 16 | ], 17 | install_requires=[ 18 | 'einops>=0.3', 19 | 'torch>=1.6' 20 | ], 21 | classifiers=[ 22 | 'Development Status :: 4 - Beta', 23 | 'Intended Audience :: Developers', 24 | 'Topic :: Scientific/Engineering :: Artificial Intelligence', 25 | 'License :: OSI Approved :: MIT License', 26 | 'Programming Language :: Python :: 3.6', 27 | ], 28 | ) 29 | --------------------------------------------------------------------------------