Fix ONNX test_quantize unittest (#6716)

.github/workflows/self-push.yml

@@ -45,7 +45,7 @@ jobs:
         source .env/bin/activate
         pip install --upgrade pip
         pip install torch!=1.6.0
-        pip install .[sklearn,testing]
+        pip install .[sklearn,testing,onnxruntime]
 
     - name: Are GPUs recognized by our DL frameworks
       run: |

.github/workflows/self-scheduled.yml

@@ -42,7 +42,7 @@ jobs:
         source .env/bin/activate
         pip install --upgrade pip
         pip install torch!=1.6.0
-        pip install .[sklearn,testing]
+        pip install .[sklearn,testing,onnxruntime]
 
     - name: Are GPUs recognized by our DL frameworks
       run: |

setup.py

@@ -74,16 +74,17 @@ extras["tf"] = [
     # "onnxconverter-common",
     # "keras2onnx"
     "onnxconverter-common @ git+git://github.com/microsoft/onnxconverter-common.git@f64ca15989b6dc95a1f3507ff6e4c395ba12dff5#egg=onnxconverter-common",
-    "keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx"
+    "keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx",
 ]
 extras["tf-cpu"] = [
     "tensorflow-cpu",
     # "onnxconverter-common",
     # "keras2onnx"
     "onnxconverter-common @ git+git://github.com/microsoft/onnxconverter-common.git@f64ca15989b6dc95a1f3507ff6e4c395ba12dff5#egg=onnxconverter-common",
-    "keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx"
+    "keras2onnx @ git+git://github.com/onnx/keras-onnx.git@cbdc75cb950b16db7f0a67be96a278f8d2953b48#egg=keras2onnx",
 ]
 extras["torch"] = ["torch"]
+extras["onnxruntime"] = ["onnxruntime>=1.4.0", "onnxruntime-tools>=1.4.2"]
 
 extras["serving"] = ["pydantic", "uvicorn", "fastapi", "starlette"]
 extras["all"] = extras["serving"] + ["tensorflow", "torch"]

src/transformers/convert_graph_to_onnx.py

@@ -364,7 +364,6 @@ def quantize(onnx_model_path: Path) -> Path:
 
     Returns: The Path generated for the quantized
     """
-    try:
     import onnx
     from onnxruntime.quantization import QuantizationMode, quantize
 
@@ -388,8 +387,6 @@ def quantize(onnx_model_path: Path) -> Path:
     onnx.save_model(quantized_model, quantized_model_path.as_posix())
 
     return quantized_model_path
-    except Exception as ie:
-        print(f"Error while quantizing the model:\n{str(ie)}")
 
 
 def verify(path: Path):