text: describe('CTS Supplement Test', function() {
    const assert = chai.assert;
    const nn = navigator.ml.getNeuralNetworkContext();
    it('check result for Concatenation axis 1 example', async function() {
      let model = await nn.createModel(options);
  
      let float32TensorType = {type: nn.TENSOR_FLOAT32, dimensions: [2, 2, 2, 2]};
      const tensorLength = product(float32TensorType.dimensions);
  
      model.addOperand(float32TensorType);
      model.addOperand(float32TensorType);
      let inputData1 = new Float32Array(tensorLength);
      inputData1.set([201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0, 208.0,
                      209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0, 216.0]);
      model.setOperandValue(1, inputData1);
      model.addOperand({type: nn.INT32});
      let axis = 1;
      model.setOperandValue(2, new Int32Array([axis]));
  
      let outputFloat32TensorType = {type: nn.TENSOR_FLOAT32, dimensions: [2, 4, 2, 2]};
      const outputTensorLength = product(outputFloat32TensorType.dimensions);
  
      model.addOperand(outputFloat32TensorType);
      model.addOperation(nn.CONCATENATION, [0, 1, 2], [3]);
  
      model.identifyInputsAndOutputs([0], [3]);
      await model.finish();
  
      let compilation = await model.createCompilation();
      compilation.setPreference(prefer);
      await compilation.finish();
  
      let execution = await compilation.createExecution();
  
      let inputData0 = new Float32Array(tensorLength);
      inputData0.set([101.0, 102.0, 103.0, 104.0, 105.0, 106.0, 107.0, 108.0,
                      109.0, 110.0, 111.0, 112.0, 113.0, 114.0, 115.0, 116.0]);
      execution.setInput(0, inputData0);
  
      let outputData = new Float32Array(outputTensorLength);
      execution.setOutput(0, outputData);
      await execution.startCompute();
  
      let expectedData = new Float32Array(outputTensorLength);
      expectedData.set([101.0, 102.0, 103.0, 104.0, 105.0, 106.0, 107.0, 108.0,
                        201.0, 202.0, 203.0, 204.0, 205.0, 206.0, 207.0, 208.0,
                        109.0, 110.0, 111.0, 112.0, 113.0, 114.0, 115.0, 116.0,
                        209.0, 210.0, 211.0, 212.0, 213.0, 214.0, 215.0, 216.0]);
  
      for (let i = 0; i < outputTensorLength; ++i) {
        assert.isTrue(almostEqualCTS(outputData[i], expectedData[i]));
      }
    });
  });
  