Update setup.py

faiss/python/setup.py

@@ -39,6 +39,18 @@ if found_swigfaiss_avx2:
     print(f"Copying {swigfaiss_avx2_lib}")
     shutil.copyfile("swigfaiss_avx2.py", "faiss/swigfaiss_avx2.py")
     shutil.copyfile(swigfaiss_avx2_lib, f"faiss/_swigfaiss_avx2{ext}")
+ROCM_PATH = os.getenv('ROCM_PATH')
+dtk_path = ROCM_PATH + '/.info/rocm_version'
+with open(dtk_path, 'r') as file:
+    content = file.read().strip()
+dtk_version = content.replace('.', '')
+print(dtk_version)
+cwd = os.path.dirname(os.path.abspath(__file__))
+ver_path = os.path.join(cwd, "faiss", "__init__.py")
+with open(ver_path, 'w') as f:
+    f.write("__version__ = '1.7.2'\n")
+    version = '1.7.2' + '+das.dtk' + dtk_version
+    f.write(f"__dcu_version__ = '{version}'\n")
 
 long_description="""
 Faiss is a library for efficient similarity search and clustering of dense
@@ -50,7 +62,7 @@ are implemented on the GPU. It is developed by Facebook AI Research.
 """
 setup(
     name='faiss',
-    version='1.7.2-dtk22.10-gitb7348e7df780',
+    version='1.7.2' + "+das.dtk" + dtk_version,
     description='A library for efficient similarity search and clustering of dense vectors',
     long_description=long_description,
     url='https://github.com/facebookresearch/faiss',