// META: title=test WebNN API softsign operation
// META: global=window
// META: variant=?cpu
// META: variant=?gpu
// META: variant=?npu
// META: script=../resources/utils.js
// META: timeout=long

'use strict';

// https://www.w3.org/TR/webnn/#api-mlgraphbuilder-softsign-method
// Compute the softsign function of the input tensor. The calculation follows
// the expression x / (1 + |x|).
//
// MLOperand softsign(MLOperand input);

const softsignTests = [
  {
    'name': 'softsign positive float32 1D constant tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            1.5834133625030518, 4.078719139099121, 8.883357048034668,
            8.070859909057617,  8.211773872375488, 2.4554004669189453,
            0.653374195098877,  7.866281032562256, 3.123955249786377,
            8.013792037963867,  3.940986156463623, 1.813172698020935,
            2.3906760215759277, 1.335968017578125, 9.416410446166992,
            0.4432569146156311, 5.236661911010742, 9.42424201965332,
            7.816190242767334,  5.849185943603516, 8.780370712280273,
            5.120515823364258,  7.117222309112549, 4.599106788635254
          ],
          'descriptor': {shape: [24], dataType: 'float32'},
          'constant': true
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            0.6129152178764343,  0.8030999898910522, 0.8988198041915894,
            0.8897568583488464,  0.8914432525634766, 0.7105979323387146,
            0.3951762318611145,  0.8872131109237671, 0.7575143575668335,
            0.8890588879585266,  0.7976112365722656, 0.6445294618606567,
            0.7050735354423523,  0.5719119310379028, 0.9039976596832275,
            0.30712267756462097, 0.8396578431129456, 0.9040697813034058,
            0.8865723013877869,  0.8539972305297852, 0.8977543711662292,
            0.8366150856018066,  0.8768051266670227, 0.8214001059532166
          ],
          'descriptor': {shape: [24], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign positive float32 0D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [1.5834133625030518],
          'descriptor': {shape: [], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [0.6129152178764343],
          'descriptor': {shape: [], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign negative float32 0D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [-2.597844123840332],
          'descriptor': {shape: [], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [-0.7220557928085327],
          'descriptor': {shape: [], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign positive float32 1D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            1.5834133625030518, 4.078719139099121, 8.883357048034668,
            8.070859909057617,  8.211773872375488, 2.4554004669189453,
            0.653374195098877,  7.866281032562256, 3.123955249786377,
            8.013792037963867,  3.940986156463623, 1.813172698020935,
            2.3906760215759277, 1.335968017578125, 9.416410446166992,
            0.4432569146156311, 5.236661911010742, 9.42424201965332,
            7.816190242767334,  5.849185943603516, 8.780370712280273,
            5.120515823364258,  7.117222309112549, 4.599106788635254
          ],
          'descriptor': {shape: [24], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            0.6129152178764343,  0.8030999898910522, 0.8988198041915894,
            0.8897568583488464,  0.8914432525634766, 0.7105979323387146,
            0.3951762318611145,  0.8872131109237671, 0.7575143575668335,
            0.8890588879585266,  0.7976112365722656, 0.6445294618606567,
            0.7050735354423523,  0.5719119310379028, 0.9039976596832275,
            0.30712267756462097, 0.8396578431129456, 0.9040697813034058,
            0.8865723013877869,  0.8539972305297852, 0.8977543711662292,
            0.8366150856018066,  0.8768051266670227, 0.8214001059532166
          ],
          'descriptor': {shape: [24], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign negative float32 1D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -2.597844123840332,  -0.4449555575847626, -9.095475196838379,
            -3.7480077743530273, -1.3867290019989014, -8.220329284667969,
            -3.538342237472534,  -9.364588737487793,  -6.283252239227295,
            -5.002012252807617,  -8.245729446411133,  -3.775470495223999,
            -4.087255001068115,  -7.381676197052002,  -5.8829216957092285,
            -8.338910102844238,  -6.60154914855957,   -4.491941928863525,
            -3.5247786045074463, -4.43991231918335,   -5.234262466430664,
            -1.5911732912063599, -9.106277465820312,  -8.523774147033691
          ],
          'descriptor': {shape: [24], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.7220557928085327, -0.3079372048377991, -0.9009457230567932,
            -0.7893853783607483, -0.5810165405273438, -0.891543984413147,
            -0.7796552181243896, -0.9035176634788513, -0.8626986742019653,
            -0.8333892226219177, -0.8918419480323792, -0.7905965447425842,
            -0.8034303188323975, -0.8806921243667603, -0.8547128438949585,
            -0.8929211497306824, -0.8684478402137756, -0.8179150223731995,
            -0.7789947390556335, -0.8161734938621521, -0.8395960927009583,
            -0.6140744686126709, -0.9010515809059143, -0.894999623298645
          ],
          'descriptor': {shape: [24], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign float32 2D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.343496322631836,  -6.920152187347412,  2.699638843536377,
            -8.663105010986328,  -3.1905343532562256, 7.657886981964111,
            6.650215148925781,   6.058011054992676,   0.6634320616722107,
            5.8058037757873535,  -0.32821124792099,   1.2704304456710815,
            -9.946120262145996,  6.905375003814697,   -0.031071536242961884,
            -3.9696409702301025, 6.270823001861572,   -2.639260768890381,
            3.0513505935668945,  7.426476955413818,   -8.454667091369629,
            7.135868072509766,   -4.986093997955322,  -7.859614849090576
          ],
          'descriptor': {shape: [4, 6], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.8929736614227295, -0.8737397789955139,  0.7297033667564392,
            -0.8965135812759399, -0.7613669633865356,  0.8844983577728271,
            0.8692847490310669,  0.8583170175552368,   0.3988332748413086,
            0.8530665636062622,  -0.24710771441459656, 0.5595548748970032,
            -0.9086434245109558, 0.8735038042068481,   -0.03013519011437893,
            -0.798778235912323,  0.8624640107154846,   -0.7252188920974731,
            0.7531687617301941,  0.88132643699646,     -0.8942321538925171,
            0.8770874738693237,  -0.8329461812973022,  -0.8871282935142517
          ],
          'descriptor': {shape: [4, 6], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign float32 3D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.343496322631836,  -6.920152187347412,  2.699638843536377,
            -8.663105010986328,  -3.1905343532562256, 7.657886981964111,
            6.650215148925781,   6.058011054992676,   0.6634320616722107,
            5.8058037757873535,  -0.32821124792099,   1.2704304456710815,
            -9.946120262145996,  6.905375003814697,   -0.031071536242961884,
            -3.9696409702301025, 6.270823001861572,   -2.639260768890381,
            3.0513505935668945,  7.426476955413818,   -8.454667091369629,
            7.135868072509766,   -4.986093997955322,  -7.859614849090576
          ],
          'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.8929736614227295, -0.8737397789955139,  0.7297033667564392,
            -0.8965135812759399, -0.7613669633865356,  0.8844983577728271,
            0.8692847490310669,  0.8583170175552368,   0.3988332748413086,
            0.8530665636062622,  -0.24710771441459656, 0.5595548748970032,
            -0.9086434245109558, 0.8735038042068481,   -0.03013519011437893,
            -0.798778235912323,  0.8624640107154846,   -0.7252188920974731,
            0.7531687617301941,  0.88132643699646,     -0.8942321538925171,
            0.8770874738693237,  -0.8329461812973022,  -0.8871282935142517
          ],
          'descriptor': {shape: [2, 3, 4], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign float32 4D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.343496322631836,  -6.920152187347412,  2.699638843536377,
            -8.663105010986328,  -3.1905343532562256, 7.657886981964111,
            6.650215148925781,   6.058011054992676,   0.6634320616722107,
            5.8058037757873535,  -0.32821124792099,   1.2704304456710815,
            -9.946120262145996,  6.905375003814697,   -0.031071536242961884,
            -3.9696409702301025, 6.270823001861572,   -2.639260768890381,
            3.0513505935668945,  7.426476955413818,   -8.454667091369629,
            7.135868072509766,   -4.986093997955322,  -7.859614849090576
          ],
          'descriptor': {shape: [1, 2, 3, 4], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.8929736614227295, -0.8737397789955139,  0.7297033667564392,
            -0.8965135812759399, -0.7613669633865356,  0.8844983577728271,
            0.8692847490310669,  0.8583170175552368,   0.3988332748413086,
            0.8530665636062622,  -0.24710771441459656, 0.5595548748970032,
            -0.9086434245109558, 0.8735038042068481,   -0.03013519011437893,
            -0.798778235912323,  0.8624640107154846,   -0.7252188920974731,
            0.7531687617301941,  0.88132643699646,     -0.8942321538925171,
            0.8770874738693237,  -0.8329461812973022,  -0.8871282935142517
          ],
          'descriptor': {shape: [1, 2, 3, 4], dataType: 'float32'}
        }
      }
    }
  },
  {
    'name': 'softsign float32 5D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.343496322631836,  -6.920152187347412,  2.699638843536377,
            -8.663105010986328,  -3.1905343532562256, 7.657886981964111,
            6.650215148925781,   6.058011054992676,   0.6634320616722107,
            5.8058037757873535,  -0.32821124792099,   1.2704304456710815,
            -9.946120262145996,  6.905375003814697,   -0.031071536242961884,
            -3.9696409702301025, 6.270823001861572,   -2.639260768890381,
            3.0513505935668945,  7.426476955413818,   -8.454667091369629,
            7.135868072509766,   -4.986093997955322,  -7.859614849090576
          ],
          'descriptor': {shape: [1, 2, 1, 3, 4], dataType: 'float32'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.8929736614227295, -0.8737397789955139,  0.7297033667564392,
            -0.8965135812759399, -0.7613669633865356,  0.8844983577728271,
            0.8692847490310669,  0.8583170175552368,   0.3988332748413086,
            0.8530665636062622,  -0.24710771441459656, 0.5595548748970032,
            -0.9086434245109558, 0.8735038042068481,   -0.03013519011437893,
            -0.798778235912323,  0.8624640107154846,   -0.7252188920974731,
            0.7531687617301941,  0.88132643699646,     -0.8942321538925171,
            0.8770874738693237,  -0.8329461812973022,  -0.8871282935142517
          ],
          'descriptor': {shape: [1, 2, 1, 3, 4], dataType: 'float32'}
        }
      }
    }
  },

  // float16 tests
  {
    'name': 'softsign positive float16 1D constant tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            1.5830078125, 4.078125,     8.8828125, 8.0703125,   8.2109375,
            2.455078125,  0.6533203125, 7.8671875, 3.123046875, 8.015625,
            3.94140625,   1.8134765625, 2.390625,  1.3359375,   9.4140625,
            0.443359375,  5.23828125,   9.421875,  7.81640625,  5.84765625,
            8.78125,      5.12109375,   7.1171875, 4.59765625
          ],
          'descriptor': {shape: [24], dataType: 'float16'},
          'constant': true
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            0.61279296875, 0.80322265625, 0.89892578125,  0.8896484375,
            0.8916015625,  0.71044921875, 0.395263671875, 0.88720703125,
            0.75732421875, 0.88916015625, 0.7978515625,   0.64453125,
            0.705078125,   0.57177734375, 0.90380859375,  0.30712890625,
            0.83984375,    0.90380859375, 0.88671875,     0.85400390625,
            0.89794921875, 0.83642578125, 0.876953125,    0.8212890625
          ],
          'descriptor': {shape: [24], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign positive float16 0D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [1.5830078125],
          'descriptor': {shape: [], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [0.61279296875],
          'descriptor': {shape: [], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign negative float16 0D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [-2.59765625],
          'descriptor': {shape: [], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [-0.72216796875],
          'descriptor': {shape: [], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign positive float16 1D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            1.5830078125, 4.078125,     8.8828125, 8.0703125,   8.2109375,
            2.455078125,  0.6533203125, 7.8671875, 3.123046875, 8.015625,
            3.94140625,   1.8134765625, 2.390625,  1.3359375,   9.4140625,
            0.443359375,  5.23828125,   9.421875,  7.81640625,  5.84765625,
            8.78125,      5.12109375,   7.1171875, 4.59765625
          ],
          'descriptor': {shape: [24], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            0.61279296875, 0.80322265625, 0.89892578125,  0.8896484375,
            0.8916015625,  0.71044921875, 0.395263671875, 0.88720703125,
            0.75732421875, 0.88916015625, 0.7978515625,   0.64453125,
            0.705078125,   0.57177734375, 0.90380859375,  0.30712890625,
            0.83984375,    0.90380859375, 0.88671875,     0.85400390625,
            0.89794921875, 0.83642578125, 0.876953125,    0.8212890625
          ],
          'descriptor': {shape: [24], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign negative float16 1D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -2.59765625, -0.445068359375, -9.09375,   -3.748046875, -1.38671875,
            -8.21875,    -3.5390625,      -9.3671875, -6.28515625,  -5.00390625,
            -8.2421875,  -3.775390625,    -4.0859375, -7.3828125,   -5.8828125,
            -8.3359375,  -6.6015625,      -4.4921875, -3.525390625, -4.44140625,
            -5.234375,   -1.5908203125,   -9.109375,  -8.5234375
          ],
          'descriptor': {shape: [24], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.72216796875, -0.30810546875, -0.90087890625, -0.78955078125,
            -0.5810546875,  -0.8916015625,  -0.77978515625, -0.9033203125,
            -0.86279296875, -0.83349609375, -0.8916015625,  -0.79052734375,
            -0.80322265625, -0.880859375,   -0.8544921875,  -0.89306640625,
            -0.86865234375, -0.81787109375, -0.77880859375, -0.81640625,
            -0.83935546875, -0.6142578125,  -0.90087890625, -0.89501953125
          ],
          'descriptor': {shape: [24], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign float16 2D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.34375,      -6.921875,    2.69921875,        -8.6640625,
            -3.19140625,   7.65625,      6.6484375,         6.05859375,
            0.66357421875, 5.8046875,    -0.328125,         1.2705078125,
            -9.9453125,    6.90625,      -0.03106689453125, -3.96875,
            6.26953125,    -2.638671875, 3.05078125,        7.42578125,
            -8.453125,     7.13671875,   -4.984375,         -7.859375
          ],
          'descriptor': {shape: [4, 6], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.89306640625, -0.87353515625, 0.7294921875,
            -0.896484375,   -0.76123046875, 0.88427734375,
            0.869140625,    0.8583984375,   0.39892578125,
            0.85302734375,  -0.2470703125,  0.5595703125,
            -0.90869140625, 0.87353515625,  -0.0301361083984375,
            -0.798828125,   0.8623046875,   -0.72509765625,
            0.7529296875,   0.88134765625,  -0.89404296875,
            0.876953125,    -0.8330078125,  -0.88720703125
          ],
          'descriptor': {shape: [4, 6], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign float16 3D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.34375,      -6.921875,    2.69921875,        -8.6640625,
            -3.19140625,   7.65625,      6.6484375,         6.05859375,
            0.66357421875, 5.8046875,    -0.328125,         1.2705078125,
            -9.9453125,    6.90625,      -0.03106689453125, -3.96875,
            6.26953125,    -2.638671875, 3.05078125,        7.42578125,
            -8.453125,     7.13671875,   -4.984375,         -7.859375
          ],
          'descriptor': {shape: [2, 3, 4], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.89306640625, -0.87353515625, 0.7294921875,
            -0.896484375,   -0.76123046875, 0.88427734375,
            0.869140625,    0.8583984375,   0.39892578125,
            0.85302734375,  -0.2470703125,  0.5595703125,
            -0.90869140625, 0.87353515625,  -0.0301361083984375,
            -0.798828125,   0.8623046875,   -0.72509765625,
            0.7529296875,   0.88134765625,  -0.89404296875,
            0.876953125,    -0.8330078125,  -0.88720703125
          ],
          'descriptor': {shape: [2, 3, 4], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign float16 4D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.34375,      -6.921875,    2.69921875,        -8.6640625,
            -3.19140625,   7.65625,      6.6484375,         6.05859375,
            0.66357421875, 5.8046875,    -0.328125,         1.2705078125,
            -9.9453125,    6.90625,      -0.03106689453125, -3.96875,
            6.26953125,    -2.638671875, 3.05078125,        7.42578125,
            -8.453125,     7.13671875,   -4.984375,         -7.859375
          ],
          'descriptor': {shape: [1, 2, 3, 4], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.89306640625, -0.87353515625, 0.7294921875,
            -0.896484375,   -0.76123046875, 0.88427734375,
            0.869140625,    0.8583984375,   0.39892578125,
            0.85302734375,  -0.2470703125,  0.5595703125,
            -0.90869140625, 0.87353515625,  -0.0301361083984375,
            -0.798828125,   0.8623046875,   -0.72509765625,
            0.7529296875,   0.88134765625,  -0.89404296875,
            0.876953125,    -0.8330078125,  -0.88720703125
          ],
          'descriptor': {shape: [1, 2, 3, 4], dataType: 'float16'}
        }
      }
    }
  },
  {
    'name': 'softsign float16 5D tensor',
    'graph': {
      'inputs': {
        'softsignInput': {
          'data': [
            -8.34375,      -6.921875,    2.69921875,        -8.6640625,
            -3.19140625,   7.65625,      6.6484375,         6.05859375,
            0.66357421875, 5.8046875,    -0.328125,         1.2705078125,
            -9.9453125,    6.90625,      -0.03106689453125, -3.96875,
            6.26953125,    -2.638671875, 3.05078125,        7.42578125,
            -8.453125,     7.13671875,   -4.984375,         -7.859375
          ],
          'descriptor': {shape: [1, 2, 1, 3, 4], dataType: 'float16'}
        }
      },
      'operators': [{
        'name': 'softsign',
        'arguments': [{'input': 'softsignInput'}],
        'outputs': 'softsignOutput'
      }],
      'expectedOutputs': {
        'softsignOutput': {
          'data': [
            -0.89306640625, -0.87353515625, 0.7294921875,
            -0.896484375,   -0.76123046875, 0.88427734375,
            0.869140625,    0.8583984375,   0.39892578125,
            0.85302734375,  -0.2470703125,  0.5595703125,
            -0.90869140625, 0.87353515625,  -0.0301361083984375,
            -0.798828125,   0.8623046875,   -0.72509765625,
            0.7529296875,   0.88134765625,  -0.89404296875,
            0.876953125,    -0.8330078125,  -0.88720703125
          ],
          'descriptor': {shape: [1, 2, 1, 3, 4], dataType: 'float16'}
        }
      }
    }
  }
];

webnn_conformance_test(
    softsignTests, buildAndExecuteGraph, getPrecisionTolerance);