[LED Test] fix common inputs pt for flaky pt-tf led test (#9459)

* fix common inputs pt flakey led

* fix other tests correspondingly

tests/test_modeling_led.py

@@ -110,7 +110,8 @@ class LEDModelTester:
         # because its local attention only attends to `self.attention_window + 1` locations
         # (assuming no token with global attention, otherwise the last dimension of attentions
         # is x + self.attention_window + 1, where x is the number of tokens with global attention)
-        self.encoder_key_length = self.attention_window + 1
+        # x is set to 1
+        self.encoder_key_length = self.attention_window + 2
 
         # because of padding `encoder_seq_length`, is different from `seq_length`. Relevant for
         # the `test_attention_outputs` and `test_hidden_states_output` tests
@@ -149,6 +150,10 @@ class LEDModelTester:
 
     def prepare_config_and_inputs_for_common(self):
         config, inputs_dict = self.prepare_config_and_inputs()
+        global_attention_mask = torch.zeros_like(inputs_dict["input_ids"])
+        global_attention_mask[:, -1] = 1
+        inputs_dict["global_attention_mask"] = global_attention_mask
+
         return config, inputs_dict
 
     def create_and_check_decoder_model_past_large_inputs(self, config, inputs_dict):
@@ -196,9 +201,11 @@ class LEDModelTester:
             encoder.save_pretrained(tmpdirname)
             encoder = LEDEncoder.from_pretrained(tmpdirname).to(torch_device)
 
-        encoder_last_hidden_state_2 = encoder(inputs_dict["input_ids"], attention_mask=inputs_dict["attention_mask"])[
-            0
-        ]
+        encoder_last_hidden_state_2 = encoder(
+            inputs_dict["input_ids"],
+            attention_mask=inputs_dict["attention_mask"],
+            global_attention_mask=inputs_dict["global_attention_mask"],
+        )[0]
 
         self.parent.assertTrue((encoder_last_hidden_state_2 - encoder_last_hidden_state).abs().max().item() < 1e-3)
 
@@ -390,7 +397,8 @@ class LEDModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
             )
             out_len = len(outputs)
 
-            correct_outlen = 5
+            # global attention outputs are added as well => so +1 here
+            correct_outlen = 6
 
             # loss is at first position
             if "labels" in inputs_dict: