code: def generic_unary_test(self, op):
      class QModule(torch.nn.Module):
          def __init__(self, op):
              super().__init__()
              self.quant1 = torch.ao.quantization.QuantStub()
              self.op = op
              self.dequant = torch.ao.quantization.DeQuantStub()
  
          def forward(self, x):
              res = self.op(self.quant1(x))
              return self.dequant(res)
  
      x = np.random.random((1, 2)).astype("float32")
      self.generic_test(QModule(op), (x,), input_names=["x"])
  
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 2 for calling the TestQuantizedOps obj's underlying member method code with example usage: obj.generic_unary_test(op) and returns: self