Add Flaubert OnnxConfig to Transformers (#16279)

* Add Flaubert to ONNX to make it available for conversion.

* Fixed features for FlauBERT. fixup command remove flaubert to docs list.
Co-authored-by: ChainYo <t.chaigneau.tc@gmail.com>

docs/source/serialization.mdx

@@ -52,6 +52,7 @@ Ready-made configurations include the following architectures:
 - Data2VecText
 - DistilBERT
 - ELECTRA
+- FlauBERT
 - GPT Neo
 - I-BERT
 - LayoutLM

src/transformers/models/flaubert/__init__.py

@@ -22,7 +22,7 @@ from ...file_utils import _LazyModule, is_tf_available, is_torch_available
 
 
 _import_structure = {
-    "configuration_flaubert": ["FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FlaubertConfig"],
+    "configuration_flaubert": ["FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FlaubertConfig", "FlaubertOnnxConfig"],
     "tokenization_flaubert": ["FlaubertTokenizer"],
 }
 
@@ -52,7 +52,7 @@ if is_tf_available():
 
 
 if TYPE_CHECKING:
-    from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig
+    from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
     from .tokenization_flaubert import FlaubertTokenizer
 
     if is_torch_available():

src/transformers/models/flaubert/configuration_flaubert.py

@@ -14,6 +14,10 @@
 # limitations under the License.
 """ Flaubert configuration, based on XLM."""
 
+from collections import OrderedDict
+from typing import Mapping
+
+from ...onnx import OnnxConfig
 from ...utils import logging
 from ..xlm.configuration_xlm import XLMConfig
 
@@ -137,3 +141,14 @@ class FlaubertConfig(XLMConfig):
         self.layerdrop = layerdrop
         self.pre_norm = pre_norm
         super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, **kwargs)
+
+
+class FlaubertOnnxConfig(OnnxConfig):
+    @property
+    def inputs(self) -> Mapping[str, Mapping[int, str]]:
+        return OrderedDict(
+            [
+                ("input_ids", {0: "batch", 1: "sequence"}),
+                ("attention_mask", {0: "batch", 1: "sequence"}),
+            ]
+        )

src/transformers/onnx/features.py

@@ -8,6 +8,7 @@ from ..models.bert import BertOnnxConfig
 from ..models.camembert import CamembertOnnxConfig
 from ..models.distilbert import DistilBertOnnxConfig
 from ..models.electra import ElectraOnnxConfig
+from ..models.flaubert import FlaubertOnnxConfig
 from ..models.gpt2 import GPT2OnnxConfig
 from ..models.gpt_neo import GPTNeoOnnxConfig
 from ..models.ibert import IBertOnnxConfig
@@ -179,6 +180,15 @@ class FeaturesManager:
             "question-answering",
             onnx_config_cls=DistilBertOnnxConfig,
         ),
+        "flaubert": supported_features_mapping(
+            "default",
+            "masked-lm",
+            "causal-lm",
+            "sequence-classification",
+            "token-classification",
+            "question-answering",
+            onnx_config_cls=FlaubertOnnxConfig,
+        ),
         "marian": supported_features_mapping(
             "default",
             "default-with-past",