add torch.concat to normalization pass (pytorch#156574)

Summary: In the normalization pass, we also add torch.concat to it to normalize it as torch.cat

Test Plan:
```
buck2 test 'fbcode//mode/dev-nosan' fbcode//caffe2/test/inductor:split_cat_fx_passes -- test_cat_normalization
```

Buck UI: https://www.internalfb.com/buck2/597fd4f1-0aa7-4372-8a66-5a690d9b63a4
Test UI: https://www.internalfb.com/intern/testinfra/testrun/1688850152284203
Network: Up: 84KiB  Down: 34KiB  (reSessionID-3916e009-7117-41ce-b6f9-089873aa50dd)
Executing actions. Remaining     0/3                                                                                              1.1s exec time total
Command: test.     Finished 2 local
Time elapsed: 3:47.1s
Tests finished: Pass 2. Fail 0. Fatal 0. Skip 0. Build failure 0

Rollback Plan:

Differential Revision: D77125331

Pull Request resolved: pytorch#156574
Approved by: https://github.com/Mingming-Ding

Author: mengluy0125

test/inductor/test_split_cat_fx_passes.py

@@ -115,6 +115,33 @@ def normalize_reshape_with_dynamic_shape(x):
             )
             counters.clear()
 
+    @torch._inductor.config.patch(
+        pre_grad_fusion_options={
+            "normalization_pass": {},
+        },
+        post_grad_fusion_options={},
+    )
+    def test_cat_normalization(self):
+        def caoncat_only(x):
+            return torch.concat(list(torch.split(x, 2, 1)), dim=1)
+
+        args = [
+            torch.randn(2, 32),
+        ]
+        for fn, dynamic, expected_cat_norm_count in [
+            (caoncat_only, False, 2),
+        ]:
+            expected = fn(*args)
+            actual = torch.compile(fn, dynamic=dynamic)(*args)
+
+            torch.testing.assert_close(actual, expected)
+            self.assertEqual(
+                counters["inductor"]["normalization_pass"],
+                expected_cat_norm_count,
+                msg=f"for {fn}",
+            )
+            counters.clear()
+
     @patch
     def test_consecutive_split_merge(self):
         def multi_split(x):

torch/_inductor/fx_passes/split_cat.py

@@ -302,7 +302,7 @@ def normalize_unbind_default(match: Match, *args, **kwargs):
 
 
 @register_graph_pattern(
-    CallFunctionVarArgs(torch.cat, users=MULTIPLE),
+    CallFunctionVarArgs([torch.cat, torch.concat], users=MULTIPLE),
     pass_dict=construct_pattern_matcher_pass("normalization_pass"),
 )
 def normalize_cat_default(match: Match, *args, **kwargs):
@@ -347,6 +347,7 @@ def is_empty_tensor(x):
         cat_node.args == new_args
         and cat_node.kwargs == new_kwargs
         and cat_node.op == "call_function"
+        and cat_node.target == torch.cat
     ):
         return