[distributed][misc] be consistent with pytorch for libcudart.so (#6346)

[distributed][misc] keep consistent with how pytorch finds libcudart.so (#6346)

vllm/distributed/device_communicators/cuda_wrapper.py

@@ -4,6 +4,9 @@ convenient for use when we just need to call a few functions.
 """
 
 import ctypes
+import glob
+import os
+import sys
 from dataclasses import dataclass
 from typing import Any, Dict, List, Optional
 
@@ -33,6 +36,26 @@ class Function:
     argtypes: List[Any]
 
 
+def get_pytorch_default_cudart_library_path() -> str:
+    # code borrowed from https://github.com/pytorch/pytorch/blob/1cae60a87e5bdda8bcf55724a862eeed98a9747e/torch/__init__.py#L284 # noqa
+    lib_folder = "cuda_runtime"
+    lib_name = "libcudart.so.*[0-9]"
+    lib_path = None
+    for path in sys.path:
+        nvidia_path = os.path.join(path, "nvidia")
+        if not os.path.exists(nvidia_path):
+            continue
+        candidate_lib_paths = glob.glob(
+            os.path.join(nvidia_path, lib_folder, "lib", lib_name))
+        if candidate_lib_paths and not lib_path:
+            lib_path = candidate_lib_paths[0]
+        if lib_path:
+            break
+    if not lib_path:
+        raise ValueError(f"{lib_name} not found in the system path {sys.path}")
+    return lib_path
+
+
 class CudaRTLibrary:
     exported_functions = [
         # ​cudaError_t cudaSetDevice ( int  device )
@@ -77,9 +100,7 @@ class CudaRTLibrary:
 
     def __init__(self, so_file: Optional[str] = None):
         if so_file is None:
-            assert torch.version.cuda is not None
+            so_file = get_pytorch_default_cudart_library_path()
-            major_version = torch.version.cuda.split(".")[0]
-            so_file = f"libcudart.so.{major_version}"
         if so_file not in CudaRTLibrary.path_to_library_cache:
             lib = ctypes.CDLL(so_file)
             CudaRTLibrary.path_to_library_cache[so_file] = lib