feature_use: Remove JK from naming for feature use. (pytorch#143529)

See discussion in pytorch#142819 but
TL;DR, since we're loging use but not direct JK reads, it's less
confusing to use the logging

Pull Request resolved: pytorch#143529
Approved by: https://github.com/ezyang

Author: c00w

torch/_inductor/async_compile.py

@@ -186,9 +186,7 @@ def triton(self, kernel_name: str, source_code: str, device_str: str = "cuda"):
 
         kernel = TritonCodeCache.load(kernel_name, source_code)
         if self.use_process_pool():
-            set_feature_use(
-                "pytorch/inductor:enable_parallel_compile_version (post_warmup)", True
-            )
+            set_feature_use("parallel_compile_post_warmup", True)
             # We want to support changing these env vars after (and while) the
             # process pool is running, so pass them to the subprocess to reset.
             env_vars = ["TORCHINDUCTOR_CACHE_DIR", "TRITON_CACHE_DIR"]
@@ -202,9 +200,7 @@ def triton(self, kernel_name: str, source_code: str, device_str: str = "cuda"):
                 ),
             )
         else:
-            set_feature_use(
-                "pytorch/inductor:enable_parallel_compile_version (post_warmup)", False
-            )
+            set_feature_use("parallel_compile_post_warmup", False)
             with dynamo_timed(
                 "async_compile.precompile",
                 log_pt2_compile_event=True,

torch/_inductor/compile_fx.py

@@ -630,7 +630,7 @@ def _compile_fx_inner(
         )
         local = config.fx_graph_cache
         remote = fx_graph_remote_cache
-        set_feature_use("pytorch/remote_cache:fx_graph_memcache_version", use_cache)
+        set_feature_use("fx_cache", use_cache)
 
         # TODO: This is a hack purely to get some info to extract_tensor_metadata_for_cache_key,
         # figure out how to not have to modify example inputs

torch/_inductor/triton_bundler.py

@@ -143,13 +143,9 @@ def collect(
         """
         if not TritonBundler.is_enabled():
             cls.end_compile()
-            set_feature_use(
-                "pytorch/remote_cache:bundle_triton_into_fx_graph_cache_v2", False
-            )
+            set_feature_use("triton_bundling", False)
             return [], None
-        set_feature_use(
-            "pytorch/remote_cache:bundle_triton_into_fx_graph_cache_v2", True
-        )
+        set_feature_use("triton_bundling", True)
 
         with dynamo_timed(key="TritonBundler.collect", log_pt2_compile_event=True):
             entries = cls._entries