code: def _permute_helper(g: jit_utils.GraphContext, input, axes):
      quant_args = {
          "axes_i": axes,
          "Y_scale_f": symbolic_helper._node_get(
              input.node(), "Y_scale"
          ),
          "Y_zero_point_i": symbolic_helper._node_get(
              input.node(), "Y_zero_point"
          ),
      }
      output = g.op("_caffe2::Int8Transpose", input, **quant_args)
      symbolic_helper._quantized_ops.add(output)
      return output
  
imports: import importlib
  import inspect
  from torch.onnx import symbolic_helper, symbolic_opset9
  from torch.onnx._internal import jit_utils, registration
label_desc: Use image node_id 2 for calling a global function with example usage: _permute_helper(g, input, axes) and returns: output