code: def sigmoid(g: jit_utils.GraphContext, input):
      if input not in symbolic_helper._quantized_ops:
          return opset9.sigmoid(g, input)
      # Caffe2 expects the output scale to be 1/2^8
      # and output zero_point to be 0 (quint8 type)
      out_scale = 1.0 / 256
      zero_point = 0
      kwargs = {
          "Y_scale_f": out_scale,
          "Y_zero_point_i": zero_point,
      }
      output = g.op("_caffe2::Int8Sigmoid", input, **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 21 for calling a global function with example usage: sigmoid(g, input) and returns: output, opset9