code: def test_cat(self):
      class QConcatModule(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.quant1 = torch.ao.quantization.QuantStub()
              self.dequant = torch.ao.quantization.DeQuantStub()
  
          def forward(self, x, y):
              res = torch.ops.quantized.cat(
                  [self.quant1(x), self.quant1(y)],
                  dim=1,
                  scale=1.0,
                  zero_point=0,
              )
              return self.dequant(res)
  
      x = np.random.rand(1, 2, 3, 4).astype("float32")
      y = np.random.rand(1, 4, 3, 4).astype("float32")
      self.generic_test(
          QConcatModule(),
          (
              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 12 for calling the TestQuantizedOps obj's underlying member method code with example usage: obj.test_cat() and returns: self