text: 'use strict';
  import * as utils from '../../../../utils.js';
  
  /* eslint-disable max-len */
  describe('CTS converted from NNAPI CTS', function() {
    const nn = navigator.ml.getNeuralNetworkContext();
  
    it('test softmax converted from softmax_float_2_relaxed test', async function() {
      // Converted test case (from: V1_1/softmax_float_2_relaxed.mod.py)
      const builder = nn.createModelBuilder();
      const input = builder.input('input', {type: 'float32', dimensions: [2, 5]});
      const inputBuffer = new Float32Array([1.0, 2.0, 3.0, 4.0, 5.0, -1.0, -2.0, -3.0, -4.0, -5.0]);
      const expected = [0.011656231, 0.031684921, 0.086128544, 0.234121657, 0.636408647, 0.636408647, 0.234121657, 0.086128544, 0.031684921, 0.011656231];
      const output = builder.softmax(input);
      const model = builder.createModel({output});
      const compilation = await model.compile();
      const outputs = await compilation.compute({'input': {buffer: inputBuffer}});
      utils.checkValue(outputs.output.buffer, expected, utils.ctsFp32RelaxedAccuracyCriteria);
    });
  });
  /* eslint-disable max-len */
  