ONNX v2 raises an Exception when using PyTorch < 1.8.0 (#12933)

* Raise an issue if the pytorch version is < 1.8.0

* Attempt to add a test to ensure it correctly raises.

* Missing docstring.

* Second attempt, patch with string absolute import.

* Let's do the call before checking it was called ...

* use the correct function ... 🤦

* Raise ImportError and AssertionError respectively when unable to find torch and torch version is not sufficient.

* Correct path mock patching

* relax constraint for torch_onnx_dict_inputs to ge instead of eq.

* Style.

* Split each version requirements for torch.

* Let's compare version directly.

* Import torch_version after checking pytorch is installed.

* @require_torch

tests/test_onnx_v2.py

@@ -24,7 +24,13 @@ from transformers.models.roberta import RobertaOnnxConfig
 
 # from transformers.models.t5 import T5OnnxConfig
 from transformers.models.xlm_roberta import XLMRobertaOnnxConfig
-from transformers.onnx import EXTERNAL_DATA_FORMAT_SIZE_LIMIT, OnnxConfig, ParameterFormat, validate_model_outputs
+from transformers.onnx import (
+    EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
+    OnnxConfig,
+    ParameterFormat,
+    export,
+    validate_model_outputs,
+)
 from transformers.onnx.config import DEFAULT_ONNX_OPSET, OnnxConfigWithPast
 from transformers.onnx.utils import (
     compute_effective_axis_dimension,
@@ -40,6 +46,15 @@ class OnnxUtilsTestCaseV2(TestCase):
     Cover all the utilities involved to export ONNX models
     """
 
+    @require_torch
+    @patch("transformers.onnx.convert.is_torch_onnx_dict_inputs_support_available", return_value=False)
+    def test_ensure_pytorch_version_ge_1_8_0(self, mock_is_torch_onnx_dict_inputs_support_available):
+        """
+        Ensure we raise an Exception if the pytorch version is unsupported (< 1.8.0)
+        """
+        self.assertRaises(AssertionError, export, None, None, None, None, None)
+        mock_is_torch_onnx_dict_inputs_support_available.assert_called()
+
     def test_compute_effective_axis_dimension(self):
         """
         When exporting ONNX model with dynamic axis (batch or sequence) we set batch_size and/or sequence_length = -1.