Detach the tensors on batch-norm eval. (#1702)

* Detach the tensors on batch-norm eval.

* Fix pyo3 bindings.

* Black tweak.

* Formatting.

* Also update the pyo3-onnx formatting.

* Apply black.

candle-pyo3/py_src/candle/onnx/__init__.pyi

@@ -11,59 +11,69 @@ class ONNXModel:
 
     def __init__(self, path: str):
         pass
+
     @property
     def doc_string(self) -> str:
         """
         The doc string of the model.
         """
         pass
+
     @property
     def domain(self) -> str:
         """
         The domain of the operator set of the model.
         """
         pass
+
     def initializers(self) -> Dict[str, Tensor]:
         """
         Get the weights of the model.
         """
         pass
+
     @property
     def inputs(self) -> Optional[Dict[str, ONNXTensorDescription]]:
         """
         The inputs of the model.
         """
         pass
+
     @property
     def ir_version(self) -> int:
         """
         The version of the IR this model targets.
         """
         pass
+
     @property
     def model_version(self) -> int:
         """
         The version of the model.
         """
         pass
+
     @property
     def outputs(self) -> Optional[Dict[str, ONNXTensorDescription]]:
         """
         The outputs of the model.
         """
         pass
+
     @property
     def producer_name(self) -> str:
         """
         The producer of the model.
         """
         pass
+
     @property
     def producer_version(self) -> str:
         """
         The version of the producer of the model.
         """
         pass
+
     def run(self, inputs: Dict[str, Tensor]) -> Dict[str, Tensor]:
         """
         Run the model on the given inputs.
@@ -81,6 +91,7 @@ class ONNXTensorDescription:
         The data type of the tensor.
         """
         pass
+
     @property
     def shape(self) -> Tuple[Union[int, str, Any]]:
         """