Migrate from lru_cache to cache (#155613)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/155613
Approved by: https://github.com/ezyang
ghstack dependencies: #155612

torch/_inductor/select_algorithm.py

@@ -1124,7 +1124,7 @@ class TritonTemplateKernel(TritonKernel):
         ]
 
 
-@functools.lru_cache(None)
+@functools.cache
 def _jinja2_env():
     try:
         import jinja2
@@ -1726,7 +1726,7 @@ class ExternKernelChoice:
     def call_name(self):
         return f"extern_kernels.{self.name}"
 
-    @functools.lru_cache(None)  # noqa: B019
+    @functools.cache  # noqa: B019
     def hash_key(self):
         fn = self.to_callable()
         parts = [
@@ -1933,7 +1933,7 @@ class ExternKernelCaller(ChoiceCaller):
         return f"extern_{self.choice.name}"
 
 
-@functools.lru_cache(None)
+@functools.cache
 def get_mm_log_filename() -> Optional[str]:
     mm_file_name = os.environ.get("TORCHINDUCTOR_MM_LOGGING_FILE", None)
     if not mm_file_name:
@@ -2052,7 +2052,7 @@ class NoValidChoicesError(RuntimeError):
     pass
 
 
-@functools.lru_cache(None)
+@functools.cache
 def get_num_workers() -> int:
     if "TORCHINDUCTOR_COMPILE_THREADS" in os.environ:
         return int(os.environ["TORCHINDUCTOR_COMPILE_THREADS"])
@@ -2194,7 +2194,7 @@ class AlgorithmSelectorCache(PersistentCache):
                 # CUDATemplateCaller still needs to go through autotuning process to retrieve workspace size.
                 return choices[0].output_node()
 
-        @functools.lru_cache(None)
+        @functools.cache
         def make_benchmark_fn():
             return self.make_benchmark_fn(choices, input_nodes, layout, input_gen_fns)
 
@@ -2506,7 +2506,7 @@ class AlgorithmSelectorCache(PersistentCache):
                 future.add_done_callback(on_complete)
                 futures[future] = c
 
-        @functools.lru_cache(None)
+        @functools.cache
         @restore_stdout_stderr()
         def wait_on_futures():
             log.debug("Waiting on futures")