add setup in runtime

app.py

@@ -10,6 +10,55 @@ import requests
 import csv
 import spaces
 
+from setuptools import setup, find_packages
+from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CppExtension
+
+setup(
+    name='featup',
+    version='0.1.2',
+    packages=find_packages(),
+    install_requires=[
+        'torch',
+        'kornia',
+        'omegaconf',
+        'pytorch-lightning',
+        'torchvision',
+        'tqdm',
+        'torchmetrics',
+        'scikit-learn',
+        'numpy',
+        'matplotlib',
+        'timm==0.4.12',
+    ],
+    author='Mark Hamilton, Stephanie Fu',
+    author_email='markth@mit.edu, fus@berkeley.edu',
+    description='Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024',
+    long_description=open('README.md').read(),
+    long_description_content_type='text/markdown',
+    url='https://github.com/mhamilton723/FeatUp',
+    classifiers=[
+        'Programming Language :: Python :: 3',
+        'License :: OSI Approved :: MIT License',
+        'Operating System :: OS Independent',
+    ],
+    python_requires='>=3.6',
+    ext_modules=[
+        CUDAExtension(
+            'adaptive_conv_cuda_impl',
+            [
+                'featup/adaptive_conv_cuda/adaptive_conv_cuda.cpp',
+                'featup/adaptive_conv_cuda/adaptive_conv_kernel.cu',
+            ]),
+        CppExtension(
+            'adaptive_conv_cpp_impl',
+            ['featup/adaptive_conv_cuda/adaptive_conv.cpp'],
+            undef_macros=["NDEBUG"]),
+    ],
+    cmdclass={
+        'build_ext': BuildExtension
+    }
+)
+
 
 def plot_feats(image, lr, hr):
     assert len(image.shape) == len(lr.shape) == len(hr.shape) == 3