Prepare deprecated ONNX exporter for torch v1.11 (#15388)

* Prepare deprecated ONNX exporter for PyTorch v1.11

* Add deprecation warning

src/transformers/convert_graph_to_onnx.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
 from argparse import ArgumentParser
 from os import listdir, makedirs
 from pathlib import Path
@@ -278,18 +279,32 @@ def convert_pytorch(nlp: Pipeline, opset: int, output: Path, use_external_format
         input_names, output_names, dynamic_axes, tokens = infer_shapes(nlp, "pt")
         ordered_input_names, model_args = ensure_valid_input(nlp.model, tokens, input_names)
 
-        export(
-            nlp.model,
-            model_args,
-            f=output.as_posix(),
-            input_names=ordered_input_names,
-            output_names=output_names,
-            dynamic_axes=dynamic_axes,
-            do_constant_folding=True,
-            use_external_data_format=use_external_format,
-            enable_onnx_checker=True,
-            opset_version=opset,
-        )
+        # PyTorch deprecated the `enable_onnx_checker` and `use_external_data_format` arguments in v1.11,
+        # so we check the torch version for backwards compatibility
+        if parse(torch.__version__) <= parse("1.10.99"):
+            export(
+                nlp.model,
+                model_args,
+                f=output.as_posix(),
+                input_names=ordered_input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                do_constant_folding=True,
+                use_external_data_format=use_external_format,
+                enable_onnx_checker=True,
+                opset_version=opset,
+            )
+        else:
+            export(
+                nlp.model,
+                model_args,
+                f=output.as_posix(),
+                input_names=ordered_input_names,
+                output_names=output_names,
+                dynamic_axes=dynamic_axes,
+                do_constant_folding=True,
+                opset_version=opset,
+            )
 
 
 def convert_tensorflow(nlp: Pipeline, opset: int, output: Path):
@@ -356,6 +371,10 @@ def convert(
     Returns:
 
     """
+    warnings.warn(
+        "The `transformers.convert_graph_to_onnx` package is deprecated and will be removed in version 5 of Transformers",
+        FutureWarning,
+    )
     print(f"ONNX opset version set to: {opset}")
 
     # Load the pipeline