code: def test_quantized_add(self):
      class QAddModule(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.quant1 = torch.ao.quantization.QuantStub()
              self.quant2 = torch.ao.quantization.QuantStub()
              self.dequant = torch.ao.quantization.DeQuantStub()
  
          def forward(self, x, y):
              res = torch.ops.quantized.add(
                  self.quant1(x), self.quant2(y), 1.0, 0
              )
              return self.dequant(res)
  
      x = np.random.random(2).astype("float32")
      y = np.random.random(2).astype("float32")
      self.generic_test(QAddModule(), (x, y), input_names=["x", "y"])
  
imports: import io
  import caffe2.python.onnx.backend
  import numpy
  import onnx
  import pytorch_test_common
  import torch.ao.nn.quantized
  import torch.nn
  import torch.onnx
  from torch.testing._internal import common_utils
label_desc: Use image node_id 3 for calling the TestQuantizedOps obj's underlying member method code with example usage: obj.test_quantized_add() and returns: self