Fix mask creations of GPTNeoX and GPT2 (#31944)

* fix mask creation of gpt2 and gpt_neox caused by me

* forgot the reshape of masks when shape > 2

* add tests for gpt neox and gpt2

* nit on a comment

tests/models/gpt2/test_modeling_gpt2.py

@@ -426,6 +426,36 @@ class GPT2ModelTester:
                 self.parent.assertLessEqual(abs(torch.std(model.state_dict()[key]) - model_std), 0.001)
                 self.parent.assertLessEqual(abs(torch.mean(model.state_dict()[key]) - 0.0), 0.01)
 
+    def create_and_check_cached_forward_with_and_without_attention_mask(self, config, input_ids, *args):
+        # Relevant issue: https://github.com/huggingface/transformers/issues/31943
+        model = GPT2Model(config)
+        model.to(torch_device)
+        model.eval()
+
+        # We want this for SDPA, eager works with a `None` attention mask
+        assert (
+            model.config._attn_implementation == "sdpa"
+        ), "This test assumes the model to have the SDPA implementation for its attention calculations."
+
+        # Prepare cache and non_cache input, needs a full attention mask
+        cached_len = input_ids.shape[-1] // 2
+        input_mask = torch.ones(size=input_ids.size()).to(torch_device)
+        cache_inputs = {"input_ids": input_ids[:, :cached_len], "attention_mask": input_mask[:, :cached_len]}
+        non_cache_inputs = {"input_ids": input_ids[:, cached_len:], "attention_mask": input_mask}
+
+        # Cached forward once with the attention mask provided and the other time without it (which should assume full attention)
+        cache_outputs = model(**cache_inputs)
+        full_outputs_with_attention_mask = model(
+            **non_cache_inputs, past_key_values=cache_outputs.past_key_values
+        ).last_hidden_state
+        full_outputs_without_attention_mask = model(
+            non_cache_inputs["input_ids"], past_key_values=cache_outputs.past_key_values
+        ).last_hidden_state
+
+        self.parent.assertTrue(
+            torch.allclose(full_outputs_with_attention_mask, full_outputs_without_attention_mask, atol=1e-5)
+        )
+
     def prepare_config_and_inputs_for_common(self):
         config_and_inputs = self.prepare_config_and_inputs()
 
@@ -570,6 +600,10 @@ class GPT2ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_gpt2_weight_initialization(*config_and_inputs)
 
+    def test_cached_forward_with_and_without_attention_mask(self):
+        config_and_inputs = self.model_tester.prepare_config_and_inputs()
+        self.model_tester.create_and_check_cached_forward_with_and_without_attention_mask(*config_and_inputs)
+
     @unittest.skip(
         reason="This architecure seem to not compute gradients properly when using GC, check: https://github.com/huggingface/transformers/pull/27124"
     )