repo_description: 🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
repo_topics: attention deep-learning deep-learning-tutorial gan literate-programming lora machine-learning neural-networks optimizers pytorch reinforcement-learning transformer transformers
code: import setuptools
  
  with open("readme.md", "r", encoding="utf-8") as f:
      long_description = f.read()
  
  setuptools.setup(
      name='labml_nn',
      version='0.5.1',
      author="Varuna Jayasiri, Nipun Wijerathne",
      author_email="[REDACTED_EMAIL], [REDACTED_EMAIL]",
      description="🧑‍🏫 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit), optimizers (adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, diffusion, etc. 🧠",
      long_description=long_description,
      long_description_content_type="text/markdown",
      url="https://github.com/labmlai/annotated_deep_learning_paper_implementations",
      project_urls={
          'Documentation': 'https://nn.labml.ai'
      },
      packages=setuptools.find_packages(exclude=('labml', 'labml.*',
                                                 'labml_samples', 'labml_samples.*',
                                                 'labml_helpers', 'labml_helpers.*',
                                                 'test',
                                                 'test.*')),
      install_requires=['labml',
                        'torch',
                        'torchtext',
                        'torchvision',
                        'einops',
                        'numpy',
                        'fairscale'],
      classifiers=[
          "Programming Language :: Python :: 3",
          "License :: OSI Approved :: MIT License",
          'Intended Audience :: Developers',
          'Intended Audience :: Science/Research',
          'Topic :: Scientific/Engineering',
          'Topic :: Scientific/Engineering :: Mathematics',
          'Topic :: Scientific/Engineering :: Artificial Intelligence',
          'Topic :: Software Development',
          'Topic :: Software Development :: Libraries',
          'Topic :: Software Development :: Libraries :: Python Modules',
      ],
      keywords='machine learning',
  )
  