Use lru_cache for some environment detection utils (#3508)

vllm/utils.py

@@ -11,7 +11,7 @@
 import psutil
 import torch
 import asyncio
-from functools import partial
+from functools import partial, lru_cache
 from typing import (
     Awaitable,
     Callable,
@@ -120,6 +120,7 @@ def is_hip() -> bool:
     return torch.version.hip is not None
 
 
+@lru_cache(maxsize=None)
 def is_neuron() -> bool:
     try:
         import transformers_neuronx
@@ -128,6 +129,7 @@ def is_neuron() -> bool:
     return transformers_neuronx is not None
 
 
+@lru_cache(maxsize=None)
 def get_max_shared_memory_bytes(gpu: int = 0) -> int:
     """Returns the maximum shared memory per thread block in bytes."""
     # NOTE: This import statement should be executed lazily since
@@ -151,6 +153,7 @@ def random_uuid() -> str:
     return str(uuid.uuid4().hex)
 
 
+@lru_cache(maxsize=None)
 def in_wsl() -> bool:
     # Reference: https://github.com/microsoft/WSL/issues/4071
     return "microsoft" in " ".join(uname()).lower()
@@ -225,6 +228,7 @@ def set_cuda_visible_devices(device_ids: List[int]) -> None:
     os.environ["CUDA_VISIBLE_DEVICES"] = ",".join(map(str, device_ids))
 
 
+@lru_cache(maxsize=None)
 def get_nvcc_cuda_version() -> Optional[Version]:
     cuda_home = os.environ.get('CUDA_HOME')
     if not cuda_home: