Fix weekly CI pipeline errors (#1741)

1. Fix type annotation for _add_attribute_to_torchscript_node and
removed runtime type checking because int like inputs are not correctly
recognized by beartype
2. Fix `test_tensor_proto_tensor_bfloat16` with latest onnx-weekly
3. pytorch-nightly errors will be fixed separately

onnxscript/function_libs/torch_lib/graph_building/_graph_building_torch.py

@@ -425,11 +425,19 @@ def eval_function(  # type: ignore[override]
         return self._graph.add_function_call(function, inputs, attributes)
 
 
-@runtime_typing.checked
 def _add_attribute_to_torchscript_node(
     node: torch.Node,
     key: str,
-    value: Union[float, int, str, bytes, Sequence[float], Sequence[int], torch.Tensor],
+    value: Union[
+        float,
+        int,
+        str,
+        bytes,
+        Sequence[float],
+        Sequence[int],
+        torch.Tensor,
+        ir.TensorProtocol,
+    ],
 ):
     """Initializes the right attribute based on type of value."""
     if isinstance(value, float):

onnxscript/ir/serde_test.py

@@ -84,6 +84,10 @@ def test_tensor_proto_tensor(self, _: str, dtype: int):
             self.skipTest("numpy<1.25 does not support bool dtype in from_dlpack")
         np.testing.assert_array_equal(np.from_dlpack(tensor), tensor.numpy())
 
+    @unittest.skipIf(
+        version_utils.onnx_older_than("1.17"),
+        "numpy_helper.to_array was not correctly implemented in onnx<1.17",
+    )
     def test_tensor_proto_tensor_bfloat16(self):
         expected_array = np.array(
             [[-3.0, -1.0, -0.5, -0.0, +0.0, 0.5, 1.0, 42.0, 2.0]], dtype=ml_dtypes.bfloat16
@@ -95,15 +99,17 @@ def test_tensor_proto_tensor_bfloat16(self):
             np.array([[-3.0, -1.0, -0.5, -0.0, +0.0, 0.5, 1.0, 42.0, 2.0]]),
         )
         tensor = serde.TensorProtoTensor(tensor_proto)
-        np.testing.assert_array_equal(tensor.numpy().view(ml_dtypes.bfloat16), expected_array)
+        np.testing.assert_array_equal(tensor.numpy(), expected_array)
         raw_data = tensor.tobytes()
         tensor_proto_from_raw_data = onnx.TensorProto(
             dims=tensor_proto.dims,
             data_type=tensor_proto.data_type,
             raw_data=raw_data,
         )
         array_from_raw_data = onnx.numpy_helper.to_array(tensor_proto_from_raw_data)
-        np.testing.assert_array_equal(array_from_raw_data, expected_array)
+        np.testing.assert_array_equal(
+            array_from_raw_data.view(ml_dtypes.bfloat16), expected_array
+        )
         # Test dlpack
         with self.assertRaises(BufferError):
             # NumPy does not support bfloat16 in from_dlpack