split thunderfx executor from default benchmark executors

thunder/benchmarks/targets.py

@@ -152,16 +152,16 @@ def interpreter_fwd(module: Callable):
     return fn_
 
 
-executors = (
-    torch_executor,
-    torch_compile_executor,
-    thunder_executor,
-    thunderfx_executor,
-)
+executors = (torch_executor, torch_compile_executor, thunder_executor)
 executors_ids = (
     "torch",
     "torch.compile",
     "thunder",
+)
+
+torchbench_executors = (*executors, thunderfx_executor)
+torchbench_executors_ids = (
+    *executors_ids,
     "thunderfx",
 )
 
@@ -844,8 +844,8 @@ def test_resnet50(benchmark, executor: Callable, compute_type: ComputeType):
 )
 @pytest.mark.parametrize(
     "executor,",
-    executors,
-    ids=executors_ids,
+    torchbench_executors,
+    ids=torchbench_executors_ids,
 )
 @parametrize_compute_type
 def test_torchbench(benchmark, module_name, executor, compute_type: ComputeType):
@@ -870,8 +870,8 @@ def test_torchbench(benchmark, module_name, executor, compute_type: ComputeType)
 )
 @pytest.mark.parametrize(
     "executor,",
-    executors,
-    ids=executors_ids,
+    torchbench_executors,
+    ids=torchbench_executors_ids,
 )
 @parametrize_compute_type
 def test_torchbench_canary(benchmark, module_name, executor, compute_type: ComputeType):