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 reshape converted from reshape_weights_as_inputs test', async function() {
      // Converted test case (from: V1_0/reshape_weights_as_inputs.mod.py)
      const builder = nn.createModelBuilder();
      const op1 = builder.input('op1', {type: 'float32', dimensions: [1, 1, 3, 3]});
      const op1Buffer = new Float32Array([1, 2, 3, 4, 5, 6, 7, 8, 9]);
      const op2 = [-1];
      const expected = [1, 2, 3, 4, 5, 6, 7, 8, 9];
      const op3 = builder.reshape(op1, op2);
      const model = builder.createModel({op3});
      const compilation = await model.compile();
      const outputs = await compilation.compute({'op1': {buffer: op1Buffer}});
      utils.checkValue(outputs.op3.buffer, expected, utils.ctsFp32RestrictAccuracyCriteria);
    });
  });
  /* eslint-disable max-len */
  