lint

onnxscript/converter.py

@@ -800,6 +800,9 @@ def translate_slice(slice_expr: ast.Slice) -> tuple[str, str, str]:
         non_scalar_indices.extend(scalar_indices)
         if non_scalar_indices:
             last_axis, _ = non_scalar_indices[-1]
+        else:
+            # TODO(justinchuby): Clarify what last_axis should be when non_scalar_indices is False
+            last_axis = None
         for axis, index_expr in non_scalar_indices:
             index_value = self._translate_expr(index_expr)
             axis_attr = self._make_onnx_attr("axis", axis)

onnxscript/function_libs/torch_lib/graph_building/_graph_building_torch.py

@@ -832,7 +832,7 @@ def _override_with_symbolic_value_info_proto(self, onnx_model: onnx.ModelProto):
         existing_value_info = {info.name: info for info in onnx_model.graph.value_info}
 
         # Override value_info for top level graph inputs.
-        for input in self.torch_graph.inputs():
+        for input in self.torch_graph.inputs():  # pylint: disable=not-an-iterable
             if input not in self._value_to_tensor:
                 raise RuntimeError(f"Input '{input.debugName()}' has no type.")
             tensor = self._value_to_tensor[input]
@@ -847,7 +847,7 @@ def _override_with_symbolic_value_info_proto(self, onnx_model: onnx.ModelProto):
                     break
 
         # Override value_info for top level graph outputs.
-        for output in self.torch_graph.outputs():
+        for output in self.torch_graph.outputs():  # pylint: disable=not-an-iterable
             if output not in self._value_to_tensor:
                 raise RuntimeError(f"Output '{output.debugName()}' has no type.")
             tensor = self._value_to_tensor[output]