revert change to setup.py

faiss/python/setup.py

@@ -4,12 +4,10 @@
 # LICENSE file in the root directory of this source tree.
 
 from __future__ import print_function
-
+from setuptools import setup, find_packages
 import os
-import platform
 import shutil
-
-from setuptools import find_packages, setup
+import platform
 
 # make the faiss python package dir
 shutil.rmtree("faiss", ignore_errors=True)
@@ -22,8 +20,8 @@
 shutil.copyfile("extra_wrappers.py", "faiss/extra_wrappers.py")
 shutil.copyfile("array_conversions.py", "faiss/array_conversions.py")
 
-ext = ".pyd" if platform.system() == "Windows" else ".so"
-prefix = "Release/" * (platform.system() == "Windows")
+ext = ".pyd" if platform.system() == 'Windows' else ".so"
+prefix = "Release/" * (platform.system() == 'Windows')
 
 swigfaiss_generic_lib = f"{prefix}_swigfaiss{ext}"
 swigfaiss_avx2_lib = f"{prefix}_swigfaiss_avx2{ext}"
@@ -37,16 +35,10 @@
 found_callbacks = os.path.exists(callbacks_lib)
 found_swigfaiss_sve = os.path.exists(swigfaiss_sve_lib)
 
-assert (
-    found_swigfaiss_generic
-    or found_swigfaiss_avx2
-    or found_swigfaiss_avx512
-    or found_swigfaiss_sve
-), (
-    f"Could not find {swigfaiss_generic_lib} or "
-    f"{swigfaiss_avx2_lib} or {swigfaiss_avx512_lib} or {swigfaiss_sve_lib}. "
+assert (found_swigfaiss_generic or found_swigfaiss_avx2 or found_swigfaiss_avx512 or found_swigfaiss_sve), \
+    f"Could not find {swigfaiss_generic_lib} or " \
+    f"{swigfaiss_avx2_lib} or {swigfaiss_avx512_lib} or {swigfaiss_sve_lib}. " \
     f"Faiss may not be compiled yet."
-)
 
 if found_swigfaiss_generic:
     print(f"Copying {swigfaiss_generic_lib}")
@@ -72,7 +64,7 @@
     shutil.copyfile("swigfaiss_sve.py", "faiss/swigfaiss_sve.py")
     shutil.copyfile(swigfaiss_sve_lib, f"faiss/_swigfaiss_sve{ext}")
 
-long_description = """
+long_description="""
 Faiss is a library for efficient similarity search and clustering of dense
 vectors. It contains algorithms that search in sets of vectors of any size,
  up to ones that possibly do not fit in RAM. It also contains supporting
@@ -81,19 +73,20 @@
 are implemented on the GPU. It is developed by Facebook AI Research.
 """
 setup(
-    name="faiss",
-    version="1.8.0",
-    description="A library for efficient similarity search and clustering of dense vectors",
+    name='faiss',
+    version='1.8.0',
+    description='A library for efficient similarity search and clustering of dense vectors',
     long_description=long_description,
-    url="https://github.com/facebookresearch/faiss",
-    author="Matthijs Douze, Jeff Johnson, Herve Jegou, Lucas Hosseini",
-    author_email="matthijs@meta.com",
-    license="MIT",
-    keywords="search nearest neighbors",
-    install_requires=["numpy", "packaging"],
-    packages=["faiss", "faiss.contrib", "faiss.contrib.torch"],
+    url='https://github.com/facebookresearch/faiss',
+    author='Matthijs Douze, Jeff Johnson, Herve Jegou, Lucas Hosseini',
+    author_email='matthijs@meta.com',
+    license='MIT',
+    keywords='search nearest neighbors',
+
+    install_requires=['numpy', 'packaging'],
+    packages=['faiss', 'faiss.contrib', 'faiss.contrib.torch'],
     package_data={
-        "faiss": ["*.so", "*.pyd"],
+        'faiss': ['*.so', '*.pyd'],
     },
     zip_safe=False,
 )