Fix attn mask ignore logic in training-time trace (#32613)

* fix attn mask logic for training-time trace

* add test

* fix

* fix

* fix

* fix

* fix

* format

* [run-slow] llama

* avoid accelearate

* [run-slow] llama

tests/test_modeling_common.py

@@ -4937,6 +4937,49 @@ class ModelTesterMixin:
         for i in range(n_iter):
             _ = model.generate(**input_ids, do_sample=False)
 
+    @slow
+    @require_torch_gpu
+    def test_torch_compile_for_training(self):
+        if version.parse(torch.__version__) < version.parse("2.3"):
+            self.skipTest(reason="This test requires torch >= 2.3 to run.")
+
+        if not hasattr(self, "_torch_compile_train_cls"):
+            self.skipTest(f"{self.__class__.__name__} doesn't have the attribute `_torch_compile_train_cls`.")
+
+        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
+        cls = self._torch_compile_train_cls
+        model = cls(config).to(torch_device)
+
+        inputs = {
+            "input_ids": torch.randint(low=1, high=model.config.vocab_size, size=(2, 10), device=torch_device),
+            "attention_mask": torch.tensor(
+                [[1, 1, 1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]],
+                dtype=torch.int64,
+                device=torch_device,
+            ),
+            "position_ids": torch.arange(0, 10, device=torch_device).unsqueeze(0),
+            "labels": torch.randint(low=1, high=model.config.vocab_size, size=(2, 10), device=torch_device),
+        }
+
+        # eager backward
+        set_seed(42)
+        loss = model(**inputs).loss
+        loss.backward()
+
+        params = {name: param.grad.clone().detach().cpu() for name, param in model.named_parameters()}
+        model.zero_grad()
+        del loss
+
+        model = torch.compile(model, fullgraph=True, mode="reduce-overhead")
+        # forward compilation
+        set_seed(42)
+        loss = model(**inputs).loss
+        # backward compilation
+        loss.backward()
+        # check grad matches
+        for name, param in model._orig_mod.named_parameters():
+            torch.testing.assert_close(param.grad.detach().cpu(), params[name], rtol=1e-4, atol=1e-4)
+
     @slow
     @require_torch_gpu  # Testing cuda graphs.
     @require_read_token