fix config name

test/inductor/test_torchinductor.py

@@ -6474,7 +6474,11 @@ class CommonTemplate:
     # Constant folding was explicitly turned off due to issue #108388
     # Turn it back on for test
     @unittest.skipIf(config.triton.native_matmul, "native matmul has better precision")
-    @torch._inductor.config.patch(joint_graph_constant_folding=True)
+    @torch._inductor.config.patch(
+        joint_graph_constant_folding=True,
+        # Numerical accuracy failure for triton fp16
+        max_autotune_gemm_backends="ATEN",
+    )
     def test_remove_no_ops(self):
         def matmul_with_op(x, y, fn):
             return fn(x @ y)
@@ -6902,7 +6906,11 @@ def forward(self, arg0_1: "Sym(s77)", arg1_1: "Sym(s27)", arg2_1: "Sym(s53)", ar
         _, (code0, code1) = _run_and_get_stripped_kernels(b, x)
         self.assertEqual(code0, code1)
 
-    @config.patch(force_disable_caches=True)
+    @config.patch(
+        force_disable_caches=True,
+        # Test expects a single (fused) kernel to be generated
+        max_autotune_gemm_backends="ATEN",
+    )
     @skip_if_cpp_wrapper("run_and_get_kernels issue")
     @unittest.skipIf(config.triton.native_matmul, "matmul is now generated")
     def test_deterministic_codegen_with_suffix(self):
@@ -14115,6 +14123,8 @@ def forward(self, arg0_1: "Sym(s77)", arg1_1: "Sym(s27)", arg2_1: "Sym(s53)", ar
         code_disallowed = re.sub(r"AOT ID: .*", "AOT ID: ['test']", code_disallowed)
         return code_allowed != code_disallowed
 
+    # If matmul is implemented by triton there is more reuse
+    @config.patch(max_autotune_gemm_backends="ATEN")
     @unittest.skipIf(config.triton.native_matmul, "matmul is now generated")
     def test_allow_reuse_disable_if_exceed_peak(self):
         @torch.compile