Use docconvert to normalize docstring to Google style

onnx/__init__.py

@@ -284,8 +284,7 @@ def save_model(
     size_threshold: int = 1024,
     convert_attribute: bool = False,
 ) -> None:
-    """
-    Saves the ModelProto to the specified path and optionally, serialize tensors with raw data as external data before saving.
+    """Saves the ModelProto to the specified path and optionally, serialize tensors with raw data as external data before saving.
 
     Args:
         proto: should be a in-memory ModelProto
@@ -332,8 +331,7 @@ def save_tensor(
     f: IO[bytes] | str | os.PathLike,
     format: _SupportedFormat | None = None,  # noqa: A002
 ) -> None:
-    """
-    Saves the TensorProto to the specified path.
+    """Saves the TensorProto to the specified path.
 
     Args:
         proto: should be a in-memory TensorProto

onnx/backend/base.py

@@ -14,18 +14,15 @@
 
 
 class DeviceType:
-    """
-    Describes device type.
-    """
+    """Describes device type."""
 
     _Type = NewType("_Type", int)
     CPU: _Type = _Type(0)
     CUDA: _Type = _Type(1)
 
 
 class Device:
-    """
-    Describes device type and device id
+    """Describes device type and device id
     syntax: device_type:device_id(optional)
     example: 'CPU', 'CUDA', 'CUDA:1'
     """
@@ -56,8 +53,7 @@ def getitem(self: Any, key: Any) -> Any:
 
 
 class BackendRep:
-    """
-    BackendRep is the handle that a Backend returns after preparing to execute
+    """BackendRep is the handle that a Backend returns after preparing to execute
     a model repeatedly. Users will then pass inputs to the run function of
     BackendRep to retrieve the corresponding results.
     """
@@ -68,8 +64,7 @@ def run(self, inputs: Any, **kwargs: Any) -> Tuple[Any, ...]:
 
 
 class Backend:
-    """
-    Backend is the entity that will take an ONNX model with inputs,
+    """Backend is the entity that will take an ONNX model with inputs,
     perform a computation, and then return the output.
 
     For one-off execution, users can use run_node and run_model to obtain results quickly.
@@ -112,6 +107,7 @@ def run_node(
         **kwargs: Dict[str, Any],
     ) -> Optional[Tuple[Any, ...]]:
         """Simple run one operator and return the results.
+
         Args:
             outputs_info: a list of tuples, which contains the element type and
             shape of each output. First element of the tuple is the dtype, and
@@ -131,8 +127,7 @@ def run_node(
 
     @classmethod
     def supports_device(cls, device: str) -> bool:
-        """
-        Checks whether the backend is compiled with particular device support.
+        """Checks whether the backend is compiled with particular device support.
         In particular it's used in the testing suite.
         """
         return True

onnx/backend/test/case/model/__init__.py

@@ -42,7 +42,6 @@ def expect(
 
 def collect_testcases() -> List[TestCase]:
     """Collect model test cases defined in python/numpy code."""
-
     real_model_testcases = []
 
     model_tests = [