code: def cat(
      g: jit_utils.GraphContext,
      tensor_list,
      dim,
      scale=None,
      zero_point=None,
  ):
      tensors = symbolic_helper._unpack_list(tensor_list)
      input = tensors[0]
      if input not in symbolic_helper._quantized_ops:
          return opset9.cat(g, tensor_list, dim)
  
      dim = symbolic_helper._parse_arg(dim, "i")
      kwargs = {
          "Y_scale_f": tensors[0].node()["Y_scale"],
          "Y_zero_point_i": tensors[0].node()["Y_zero_point"],
      }
      output = g.op(
          "_caffe2::Int8Concat", *tensors, axis_i=dim, **kwargs
      )
      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 20 for calling a global function with example usage: cat(g, tensor_list, dim, scale, zero_point) and returns: output, opset9