Fix incorrect function signature in template (#165567)

Summary:
In https://github.com/pytorch/pytorch/pull/148305 we refactored the grid
argument out, but it's not reflected in our template.

Test Plan:
Included in commit.
python test/inductor/test_aot_inductor.py
AOTInductorTestABICompatibleGpu.test_cond_symint_input_disable_one_pass_cuda

Reviewers:

Subscribers:

Tasks:

Tags:

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165567
Approved by: https://github.com/desertfire

test/inductor/test_aot_inductor.py

@@ -2340,6 +2340,39 @@ class AOTInductorTestsTemplate:
             dynamic_shapes=dynamic_shapes,
         )
 
+    def test_cond_symint_input_disable_one_pass(self):
+        class M(torch.nn.Module):
+            def forward(self, x, y, z):
+                a = y.shape[0]
+                b = z.shape[0]
+
+                def true_fn(x):
+                    return x + a
+
+                def false_fn(x):
+                    return x + b * z
+
+                return torch.cond(x.shape[0] > 5, true_fn, false_fn, (x,))
+
+        input1 = (
+            torch.ones(3, 3, device=self.device),
+            torch.ones(5, device=self.device),
+            torch.ones(3, 3, device=self.device),
+        )
+        input2 = (
+            torch.ones(10, 3, device=self.device),
+            torch.ones(6, device=self.device),
+            torch.ones(10, 3, device=self.device),
+        )
+        inputs = (input1, input2)
+        dynamic_shapes = {"x": {0: Dim("d")}, "y": {0: Dim("d1")}, "z": {0: Dim("d")}}
+        with torch._inductor.config.patch({"triton.autotune_at_compile_time": False}):
+            self.check_model_with_multiple_inputs(
+                M(),
+                inputs,
+                dynamic_shapes=dynamic_shapes,
+            )
+
     def test_while_loop_simple(self):
         inputs = (
             torch.randn((10, 20), device=self.device),

torch/_inductor/codegen/wrapper.py

@@ -2631,7 +2631,6 @@ class PythonWrapperCodegen(CodeGen):
                         if len(kernel.launchers) == 0:
                             kernel.precompile()
                         kernel.save_gpu_kernel(
-                            grid=(0, 0, 0),   # use dummy grid
                             stream="stream",  # use dummy stream
                             launcher=kernel.launchers[0],
                         )