Add MBART to models exportable with ONNX (#13049)

* Add MBART to models exportable with ONNX

* unittest mock

* Add tests

* Misc fixes

tests/test_onnx_v2.py

@@ -10,6 +10,7 @@ from transformers import (  # LongformerConfig,; T5Config,
     DistilBertConfig,
     GPT2Config,
     GPTNeoConfig,
+    MBartConfig,
     RobertaConfig,
     XLMRobertaConfig,
     is_torch_available,
@@ -22,6 +23,7 @@ from transformers.models.distilbert import DistilBertOnnxConfig
 # from transformers.models.longformer import LongformerOnnxConfig
 from transformers.models.gpt2 import GPT2OnnxConfig
 from transformers.models.gpt_neo import GPTNeoOnnxConfig
+from transformers.models.mbart import MBartOnnxConfig
 from transformers.models.roberta import RobertaOnnxConfig
 
 # from transformers.models.t5 import T5OnnxConfig
@@ -154,7 +156,8 @@ class OnnxConfigWithPastTestCaseV2(TestCase):
                 )
 
                 self.assertTrue(
-                    OnnxConfigWithPast.with_past(config()).use_past, "OnnxConfigWithPast.default() should use_past"
+                    OnnxConfigWithPast.with_past(config()).use_past,
+                    "OnnxConfigWithPast.from_model_config() should use_past",
                 )
 
     @patch.multiple(OnnxConfigWithPast, __abstractmethods__=set())
@@ -190,6 +193,7 @@ if is_torch_available():
         DistilBertModel,
         GPT2Model,
         GPTNeoModel,
+        MBartModel,
         RobertaModel,
         XLMRobertaModel,
     )
@@ -204,6 +208,7 @@ if is_torch_available():
         # ("LongFormer", "longformer-base-4096", LongformerModel, LongformerConfig, LongformerOnnxConfig),
         ("Roberta", "roberta-base", RobertaModel, RobertaConfig, RobertaOnnxConfig),
         ("XLM-Roberta", "roberta-base", XLMRobertaModel, XLMRobertaConfig, XLMRobertaOnnxConfig),
+        ("MBart", "sshleifer/tiny-mbart", MBartModel, MBartConfig, MBartOnnxConfig),
         # ("T5", "t5-small", T5Model, T5Config, T5OnnxConfig),
     }
 
@@ -226,11 +231,11 @@ class OnnxExportTestCaseV2(TestCase):
 
         for name, model, model_class, config_class, onnx_config_class in PYTORCH_EXPORT_DEFAULT_MODELS:
             with self.subTest(name):
-                self.assertTrue(hasattr(onnx_config_class, "default"))
+                self.assertTrue(hasattr(onnx_config_class, "from_model_config"))
 
                 tokenizer = AutoTokenizer.from_pretrained(model)
                 model = model_class(config_class.from_pretrained(model))
-                onnx_config = onnx_config_class.default(model.config)
+                onnx_config = onnx_config_class.from_model_config(model.config)
 
                 with NamedTemporaryFile("w") as output:
                     onnx_inputs, onnx_outputs = export(