More fixes following transformers 4.32 release (#1311)

* more fixes * nit * remove duplicate test * nit bis
huggingface · Aug 23, 2023 · 8289f28 · 8289f28
1 parent 7e932ec
commit 8289f28
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Showing 7 changed files with 41 additions and 13 deletions.
diff --git a/optimum/exporters/onnx/model_configs.py b/optimum/exporters/onnx/model_configs.py
@@ -1213,6 +1213,7 @@ class SamOnnxConfig(OnnxConfig):
     NORMALIZED_CONFIG_CLASS = NormalizedEncoderDecoderConfig
     DUMMY_INPUT_GENERATOR_CLASSES = (DummyVisionInputGenerator, DummyPointsGenerator)
     DEFAULT_ONNX_OPSET = 12  # einsum op not supported with opset 11
+    MIN_TORCH_VERSION = version.parse("2.0.99")  # See: https://github.com/huggingface/optimum/pull/1301
 
     def __init__(self, config: "PretrainedConfig", task: str = "feature-extraction"):
         super().__init__(config, task)

diff --git a/optimum/onnxruntime/modeling_seq2seq.py b/optimum/onnxruntime/modeling_seq2seq.py
@@ -35,6 +35,7 @@
 )
 from transformers.file_utils import add_start_docstrings_to_model_forward
 from transformers.modeling_outputs import BaseModelOutput, Seq2SeqLMOutput
+from transformers.models.auto.modeling_auto import MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES
 
 import onnxruntime as ort
 
@@ -1083,6 +1084,37 @@ class ORTModelForSpeechSeq2Seq(ORTModelForConditionalGeneration, GenerationMixin
     auto_model_class = AutoModelForSpeechSeq2Seq
     main_input_name = "input_features"
 
+    def __init__(
+        self,
+        encoder_session: ort.InferenceSession,
+        decoder_session: ort.InferenceSession,
+        config: "PretrainedConfig",
+        onnx_paths: List[str],
+        decoder_with_past_session: Optional[ort.InferenceSession] = None,
+        use_cache: bool = True,
+        use_io_binding: Optional[bool] = None,
+        model_save_dir: Optional[Union[str, Path, TemporaryDirectory]] = None,
+        preprocessors: Optional[List] = None,
+        generation_config: Optional[GenerationConfig] = None,
+        **kwargs,
+    ):
+        super().__init__(
+            encoder_session=encoder_session,
+            decoder_session=decoder_session,
+            config=config,
+            onnx_paths=onnx_paths,
+            decoder_with_past_session=decoder_with_past_session,
+            use_cache=use_cache,
+            use_io_binding=use_io_binding,
+            model_save_dir=model_save_dir,
+            preprocessors=preprocessors,
+            generation_config=generation_config,
+            **kwargs,
+        )
+        # Following a breaking change in transformers that relies directly on the mapping name and not on the greedy model mapping (that can be extended), we need to hardcode the ortmodel in this dictionary. Other pipelines do not seem to have controlflow depending on the mapping name.
+        # See: https://github.com/huggingface/transformers/pull/24960/files
+        MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES["ort_speechseq2seq"] = self.__class__.__name__
+
     def _initialize_encoder(self, session: ort.InferenceSession) -> ORTEncoder:
         return ORTEncoderForSpeech(session, self)
 

diff --git a/tests/exporters/exporters_utils.py b/tests/exporters/exporters_utils.py
@@ -95,7 +95,7 @@
     "resnet": "hf-internal-testing/tiny-random-resnet",
     "roberta": "hf-internal-testing/tiny-random-RobertaModel",
     "roformer": "hf-internal-testing/tiny-random-RoFormerModel",
-    "sam": "fxmarty/sam-vit-tiny-random",
+    # "sam": "fxmarty/sam-vit-tiny-random",  # TODO: re-enable once PyTorch 2.1 is released, see https://github.com/huggingface/optimum/pull/1301
     "segformer": "hf-internal-testing/tiny-random-SegformerModel",
     "splinter": "hf-internal-testing/tiny-random-SplinterModel",
     "squeezebert": "hf-internal-testing/tiny-random-SqueezeBertModel",

diff --git a/tests/exporters/onnx/test_exporters_onnx_cli.py b/tests/exporters/onnx/test_exporters_onnx_cli.py
@@ -129,12 +129,6 @@ def _onnx_export(
             except MinimumVersionError as e:
                 pytest.skip(f"Skipping due to minimum version requirements not met. Full error: {e}")
 
-    def test_all_models_tested(self):
-        # make sure we test all models
-        missing_models_set = TasksManager._SUPPORTED_CLI_MODEL_TYPE - set(PYTORCH_EXPORT_MODELS_TINY.keys())
-        if len(missing_models_set) > 0:
-            self.fail(f"Not testing all models. Missing models: {missing_models_set}")
-
     @parameterized.expand(PYTORCH_STABLE_DIFFUSION_MODEL.items())
     @require_torch
     @require_vision

diff --git a/tests/exporters/onnx/test_onnx_export.py b/tests/exporters/onnx/test_onnx_export.py
@@ -338,7 +338,8 @@ def _onnx_export_sd(self, model_type: str, model_name: str, device="cpu"):
     def test_all_models_tested(self):
         # make sure we test all models
         missing_models_set = TasksManager._SUPPORTED_CLI_MODEL_TYPE - set(PYTORCH_EXPORT_MODELS_TINY.keys())
-        if len(missing_models_set) > 0:
+        assert "sam" in missing_models_set  # See exporters_utils.py
+        if len(missing_models_set) > 1:
             self.fail(f"Not testing all models. Missing models: {missing_models_set}")
 
     @parameterized.expand(_get_models_to_test(PYTORCH_EXPORT_MODELS_TINY))

diff --git a/tests/onnxruntime/test_modeling.py b/tests/onnxruntime/test_modeling.py
@@ -1387,9 +1387,9 @@ class ORTModelForSequenceClassificationIntegrationTest(ORTModelTestMixin):
         "distilbert",
         "electra",
         "flaubert",
-        "gpt2",
-        "gpt_neo",
-        "gptj",
+        # "gpt2",  # see tasks.py
+        # "gpt_neo",  # see tasks.py
+        # "gptj",  # see tasks.py
         "ibert",
         # TODO: these two should be supported, but require image inputs not supported in ORTModel
         # "layoutlm"
@@ -1418,7 +1418,7 @@ def test_load_vanilla_transformers_which_is_not_supported(self):
         with self.assertRaises(Exception) as context:
             _ = ORTModelForSequenceClassification.from_pretrained(MODEL_NAMES["t5"], export=True)
 
-        self.assertIn("Unrecognized configuration class", str(context.exception))
+        self.assertIn("that is a custom or unsupported", str(context.exception))
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES)
     def test_compare_to_transformers(self, model_arch):

diff --git a/tests/onnxruntime/test_optimization.py b/tests/onnxruntime/test_optimization.py
@@ -93,7 +93,7 @@ class ORTOptimizerTest(unittest.TestCase):
         # (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-big_bird"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-distilbert"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-electra"),
-        (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-gpt2"),
+        (ORTModelForCausalLM, "hf-internal-testing/tiny-random-gpt2"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-roberta"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-xlm-roberta"),
     )