Adding upstream version 115.8.0esr.upstream/115.8.0esr

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

53 files changed, 39028 insertions, 0 deletions

diff --git a/testing/web-platform/tests/webnn/resources/test_data/abs.json b/testing/web-platform/tests/webnn/resources/test_data/abs.json
new file mode 100644
index 0000000000..c59054c3e5
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/abs.json
@@ -0,0 +1,334 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/add.json b/testing/web-platform/tests/webnn/resources/test_data/add.json
new file mode 100644
index 0000000000..0a12871ceb
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/add.json
@@ -0,0 +1,784 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json b/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json
new file mode 100644
index 0000000000..badcfc888d
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/average_pool2d.json
@@ -0,0 +1,1437 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/batch_normalization.json b/testing/web-platform/tests/webnn/resources/test_data/batch_normalization.json
new file mode 100644
index 0000000000..19f414bbfe
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/batch_normalization.json
@@ -0,0 +1,1089 @@
+{
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+            97.03362133579051,
+            -21.35103988063949,
+            -96.93823797160586,
+            -9.359310262561493,
+            80.2082435478892,
+            -85.36802529512583,
+            62.35185227095363,
+            -68.4724340974042,
+            -12.107167478351585
+          ],
+          "type": "float32"
+        },
+        "mean": {
+          "shape": [3],
+          "data": [
+            51.62914995931095,
+            99.36075401019252,
+            -96.14736495234415
+          ],
+          "type": "float32",
+          "constant": true
+        },
+        "variance": {
+          "shape": [3],
+          "data": [
+            30.448016067921067,
+            86.36218998771075,
+            73.88454888724165
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "epsilon": 1e-6 // A small value to prevent computational error due to divide-by-zero.
+      },
+      "expected": {
+        "shape": [2, 3, 2, 2],
+        "data": [
+          -16.842506408691406,
+          2.2579832077026367,
+          -20.842044830322266,
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+          -2.0609331130981445,
+          1.254050850868225,
+          18.43954849243164,
+          3.2196574211120605,
+          9.777103424072266
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "batchNormalization float32 4D NCHW tensor options.activation relu",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 2, 2],
+          "data": [
+            -41.30732967168238,
+            64.08864045143429,
+            -63.376671841233104,
+            -46.7903680211994,
+            83.0222726565018,
+            -80.08049213079853,
+            -62.144380499565784,
+            -0.10012771650340824,
+            -40.902161220312074,
+            56.963061967558474,
+            37.37249789808206,
+            57.04647733193906,
+            82.05679802728304,
+            -86.11642850667623,
+            76.88317547014259,
+            97.03362133579051,
+            -21.35103988063949,
+            -96.93823797160586,
+            -9.359310262561493,
+            80.2082435478892,
+            -85.36802529512583,
+            62.35185227095363,
+            -68.4724340974042,
+            -12.107167478351585
+          ],
+          "type": "float32"
+        },
+        "mean": {
+          "shape": [3],
+          "data": [
+            51.62914995931095,
+            99.36075401019252,
+            -96.14736495234415
+          ],
+          "type": "float32",
+          "constant": true
+        },
+        "variance": {
+          "shape": [3],
+          "data": [
+            30.448016067921067,
+            86.36218998771075,
+            73.88454888724165
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "activation": "relu"
+      },
+      "expected": {
+        "shape": [2, 3, 2, 2],
+        "data": [
+          0,
+          2.2579827308654785,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
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+          3.2196571826934814,
+          9.777103424072266
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "batchNormalization float32 4D NHWC tensor all options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -41.30732967168238,
+            83.0222726565018,
+            -40.902161220312074,
+            64.08864045143429,
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+            -96.93823797160586,
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+            76.88317547014259,
+            -9.359310262561493,
+            -68.4724340974042,
+            97.03362133579051,
+            80.2082435478892,
+            -12.107167478351585
+          ],
+          "type": "float32"
+        },
+        "mean": {
+          "shape": [3],
+          "data": [
+            51.62914995931095,
+            99.36075401019252,
+            -96.14736495234415
+          ],
+          "type": "float32",
+          "constant": true
+        },
+        "variance": {
+          "shape": [3],
+          "data": [
+            30.448016067921067,
+            86.36218998771075,
+            73.88454888724165
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "scale": {
+          "shape": [3],
+          "data": [
+            65.50171582968795,
+            -71.00757080938772,
+            -5.569730877611249
+          ],
+          "type": "float32"
+        },
+        "bias": {
+          "shape": [3],
+          "data": [
+            64.20446782594775,
+            75.28591851497856,
+            -84.57243127763437
+          ],
+          "type": "float32"
+        },
+        "axis": 3,
+        "epsilon": 1e-6,
+        "activation": "relu"
+      },
+      "expected": {
+        "shape": [2, 3, 2, 2],
+        "data": [
+          0,
+          200.12615966796875,
+          0,
+          212.10623168945312,
+          1446.3731689453125,
+          0,
+          0,
+          1309.32568359375,
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+          0,
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+          906.0018310546875,
+          0,
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+          221.62777709960938,
+          0
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/ceil.json b/testing/web-platform/tests/webnn/resources/test_data/ceil.json
new file mode 100644
index 0000000000..6fa623977f
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/ceil.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
+    {
+      "name": "ceil float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            67.38941577648342,
+            36.78218646695805,
+            99.10649131558534,
+            -22.587103876323283,
+            32.70173557917525,
+            17.688807510873474,
+            5.631034848468943,
+            12.965238190762022,
+            83.1319330049133,
+            -29.29246123472926,
+            19.844631250887133,
+            65.27903232818329,
+            26.311109519759952,
+            24.2856723456172,
+            -48.3976724829041,
+            -5.617412380605998,
+            61.53380759105448,
+            -87.81197726868459,
+            69.71428621372127,
+            5.0031021954943355,
+            84.3683411023199,
+            -9.390542062321572,
+            -27.85661776414834,
+            -34.89593295662057
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          68,
+          37,
+          100,
+          -22,
+          33,
+          18,
+          6,
+          13,
+          84,
+          -29,
+          20,
+          66,
+          27,
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+          -5,
+          62,
+          -87,
+          70,
+          6,
+          85,
+          -9,
+          -27,
+          -34
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "ceil float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            67.38941577648342,
+            36.78218646695805,
+            99.10649131558534,
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+            -9.390542062321572,
+            -27.85661776414834,
+            -34.89593295662057
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          68,
+          37,
+          100,
+          -22,
+          33,
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+          70,
+          6,
+          85,
+          -9,
+          -27,
+          -34
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "ceil float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            67.38941577648342,
+            36.78218646695805,
+            99.10649131558534,
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+            -87.81197726868459,
+            69.71428621372127,
+            5.0031021954943355,
+            84.3683411023199,
+            -9.390542062321572,
+            -27.85661776414834,
+            -34.89593295662057
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          68,
+          37,
+          100,
+          -22,
+          33,
+          18,
+          6,
+          13,
+          84,
+          -29,
+          20,
+          66,
+          27,
+          25,
+          -48,
+          -5,
+          62,
+          -87,
+          70,
+          6,
+          85,
+          -9,
+          -27,
+          -34
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "ceil float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            67.38941577648342,
+            36.78218646695805,
+            99.10649131558534,
+            -22.587103876323283,
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+            26.311109519759952,
+            24.2856723456172,
+            -48.3976724829041,
+            -5.617412380605998,
+            61.53380759105448,
+            -87.81197726868459,
+            69.71428621372127,
+            5.0031021954943355,
+            84.3683411023199,
+            -9.390542062321572,
+            -27.85661776414834,
+            -34.89593295662057
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          68,
+          37,
+          100,
+          -22,
+          33,
+          18,
+          6,
+          13,
+          84,
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+          6,
+          85,
+          -9,
+          -27,
+          -34
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "ceil float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            67.38941577648342,
+            36.78218646695805,
+            99.10649131558534,
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+            24.2856723456172,
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+            -5.617412380605998,
+            61.53380759105448,
+            -87.81197726868459,
+            69.71428621372127,
+            5.0031021954943355,
+            84.3683411023199,
+            -9.390542062321572,
+            -27.85661776414834,
+            -34.89593295662057
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          68,
+          37,
+          100,
+          -22,
+          33,
+          18,
+          6,
+          13,
+          84,
+          -29,
+          20,
+          66,
+          27,
+          25,
+          -48,
+          -5,
+          62,
+          -87,
+          70,
+          6,
+          85,
+          -9,
+          -27,
+          -34
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/clamp.json b/testing/web-platform/tests/webnn/resources/test_data/clamp.json
new file mode 100644
index 0000000000..93ab5ca0c1
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/clamp.json
@@ -0,0 +1,1102 @@
+{
+  "tests": [
+    // default options
+    {
+      "name": "clamp float32 1D tensor default options",
+      "inputs": {
+        "x": { // use 'x' for input operand name
+          "shape": [24],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
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+            9.524681107378463,
+            3.7292487446449307,
+            6.4816868736447475,
+            -1.5374205904252634,
+            -7.343102426698445,
+            7.880751290929794,
+            -2.056408790509967,
+            6.34386375786449,
+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -9.817828178405762,
+          -6.024064064025879,
+          -4.0725626945495605,
+          -6.575078010559082,
+          -7.755683898925781,
+          9.524681091308594,
+          3.7292487621307373,
+          6.481687068939209,
+          -1.537420630455017,
+          -7.34310245513916,
+          7.880751132965088,
+          -2.0564088821411133,
+          6.3438639640808105,
+          5.525737762451172,
+          0.8433118462562561,
+          -8.199960708618164,
+          -7.786487102508545,
+          9.280223846435547,
+          -2.3130595684051514,
+          9.549695014953613,
+          5.788925647735596,
+          5.549378395080566,
+          7.409400463104248,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "clamp float32 2D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
+            -7.7556836912181915,
+            9.524681107378463,
+            3.7292487446449307,
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+            -2.056408790509967,
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+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
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+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -9.817828178405762,
+          -6.024064064025879,
+          -4.0725626945495605,
+          -6.575078010559082,
+          -7.755683898925781,
+          9.524681091308594,
+          3.7292487621307373,
+          6.481687068939209,
+          -1.537420630455017,
+          -7.34310245513916,
+          7.880751132965088,
+          -2.0564088821411133,
+          6.3438639640808105,
+          5.525737762451172,
+          0.8433118462562561,
+          -8.199960708618164,
+          -7.786487102508545,
+          9.280223846435547,
+          -2.3130595684051514,
+          9.549695014953613,
+          5.788925647735596,
+          5.549378395080566,
+          7.409400463104248,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "clamp float32 3D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
+            -7.7556836912181915,
+            9.524681107378463,
+            3.7292487446449307,
+            6.4816868736447475,
+            -1.5374205904252634,
+            -7.343102426698445,
+            7.880751290929794,
+            -2.056408790509967,
+            6.34386375786449,
+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
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+            7.409400528051194,
+            -2.1236145770503745
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
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+          -6.024064064025879,
+          -4.0725626945495605,
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+          7.409400463104248,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "clamp float32 4D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [3, 2, 2, 2],
+          "data": [
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+            -2.31305948485121,
+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 2, 2, 2],
+        "data": [
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+          -8.199960708618164,
+          -7.786487102508545,
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+          -2.3130595684051514,
+          9.549695014953613,
+          5.788925647735596,
+          5.549378395080566,
+          7.409400463104248,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "clamp float32 5D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 1, 1, 2, 3],
+          "data": [
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+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
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+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 1, 1, 2, 3],
+        "data": [
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+          -2.123614549636841
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+        "type": "float32"
+      }
+    },
+    // default options.maxValue and specified options.minValue
+    {
+      "name": "clamp float32 4D tensor default options.maxValue and specified negative options.minValue",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 3],
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+            7.409400528051194,
+            -2.1236145770503745
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+          "type": "float32"
+        }
+      },
+      "expected": {
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+        "shape": [2, 1, 4, 3],
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+          -1
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+        "type": "float32"
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+      "options": {
+        "minValue": -1.0
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+    },
+    {
+      "name": "clamp float32 3D tensor default options.maxValue and specified options.minValue=0.0",
+      "inputs": {
+        "x": {
+          "shape": [6, 2, 2],
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+            7.409400528051194,
+            -2.1236145770503745
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [6, 2, 2],
+        "data": [
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+          0
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+        "type": "float32"
+      },
+      "options": {
+        "minValue": 0.0
+      }
+    },
+    {
+      "name": "clamp float32 2D tensor default options.maxValue and specified positive options.minValue",
+      "inputs": {
+        "x": {
+          "shape": [3, 8],
+          "data": [
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+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 8],
+        "data": [
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+          1,
+          1,
+          1,
+          1,
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+          1
+        ],
+        "type": "float32"
+      },
+      "options": {
+        "minValue": 1.0
+      }
+    },
+    // default options.minValue and specified options.maxValue
+    {
+      "name": "clamp float32 5D tensor default options.minValue and specified negative options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 1, 2, 3],
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+            5.788925460130297,
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+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 3],
+        "data": [
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+          -2,
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+        ],
+        "type": "float32"
+      },
+      "options": {
+        "maxValue": -2.0
+      }
+    },
+    {
+      "name": "clamp float32 1D tensor default options.minValue and specified options.maxValue=0.0",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
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+            5.788925460130297,
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+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
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+          -6.024064064025879,
+          -4.0725626945495605,
+          -6.575078010559082,
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+          0,
+          0,
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+        ],
+        "type": "float32"
+      },
+      "options": {
+        "maxValue": 0.0
+      }
+    },
+    {
+      "name": "clamp float32 3D tensor default options.minValue and specified positive options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [3, 4, 2],
+          "data": [
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+            -7.786487326213716,
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+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 4, 2],
+        "data": [
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+          -6.024064064025879,
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+        ],
+        "type": "float32"
+      },
+      "options": {
+        "maxValue": 3.0
+      }
+    },
+    // specified both options.minValue and options.maxValue
+    {
+      "name": "clamp float32 5D tensor specified both negative options.minValue and options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [3, 2, 1, 1, 4],
+          "data": [
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+            7.409400528051194,
+            -2.1236145770503745
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 2, 1, 1, 4],
+        "data": [
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+        "type": "float32"
+      },
+      "options": {
+        "minValue": -8.0,
+        "maxValue": -1.0
+      }
+    },
+    {
+      "name": "clamp float32 4D tensor specified negative options.minValue and options.maxValue=0.0",
+      "inputs": {
+        "x": {
+          "shape": [1, 4, 3, 2],
+          "data": [
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+            7.409400528051194,
+            -2.1236145770503745
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 4, 3, 2],
+        "data": [
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+          0,
+          0,
+          -6,
+          -6,
+          0,
+          -2.3130595684051514,
+          0,
+          0,
+          0,
+          0,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      },
+      "options": {
+        "minValue": -6.0,
+        "maxValue": 0.0
+      }
+    },
+    {
+      "name": "clamp float32 3D tensor specified negative options.minValue and positive options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [2, 6, 2],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
+            -7.7556836912181915,
+            9.524681107378463,
+            3.7292487446449307,
+            6.4816868736447475,
+            -1.5374205904252634,
+            -7.343102426698445,
+            7.880751290929794,
+            -2.056408790509967,
+            6.34386375786449,
+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 6, 2],
+        "data": [
+          -3,
+          -3,
+          -3,
+          -3,
+          -3,
+          4,
+          3.7292487621307373,
+          4,
+          -1.537420630455017,
+          -3,
+          4,
+          -2.0564088821411133,
+          4,
+          4,
+          0.8433118462562561,
+          -3,
+          -3,
+          4,
+          -2.3130595684051514,
+          4,
+          4,
+          4,
+          4,
+          -2.123614549636841
+        ],
+        "type": "float32"
+      },
+      "options": {
+        "minValue": -3.0,
+        "maxValue": 4.0
+      }
+    },
+    {
+      "name": "clamp float32 2D tensor specified options.minValue=0.0 and positive options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [6, 4],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
+            -7.7556836912181915,
+            9.524681107378463,
+            3.7292487446449307,
+            6.4816868736447475,
+            -1.5374205904252634,
+            -7.343102426698445,
+            7.880751290929794,
+            -2.056408790509967,
+            6.34386375786449,
+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [6, 4],
+        "data": [
+          0,
+          0,
+          0,
+          0,
+          0,
+          6,
+          3.7292487621307373,
+          6,
+          0,
+          0,
+          6,
+          0,
+          6,
+          5.525737762451172,
+          0.8433118462562561,
+          0,
+          0,
+          6,
+          0,
+          6,
+          5.788925647735596,
+          5.549378395080566,
+          6,
+          0
+        ],
+        "type": "float32"
+      },
+      "options": {
+        "minValue": 0.0,
+        "maxValue": 6.0
+      }
+    },
+    {
+      "name": "clamp float32 1D tensor specified both positive options.minValue and options.maxValue",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            -9.817828475355284,
+            -6.024063916325786,
+            -4.072562498632983,
+            -6.575078191902692,
+            -7.7556836912181915,
+            9.524681107378463,
+            3.7292487446449307,
+            6.4816868736447475,
+            -1.5374205904252634,
+            -7.343102426698445,
+            7.880751290929794,
+            -2.056408790509967,
+            6.34386375786449,
+            5.52573787183,
+            0.8433118207347725,
+            -8.19996033345526,
+            -7.786487326213716,
+            9.280223823954241,
+            -2.31305948485121,
+            9.549695091037119,
+            5.788925460130297,
+            5.549378312916486,
+            7.409400528051194,
+            -2.1236145770503745
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          2,
+          2,
+          2,
+          2,
+          2,
+          7,
+          3.7292487621307373,
+          6.481687068939209,
+          2,
+          2,
+          7,
+          2,
+          6.3438639640808105,
+          5.525737762451172,
+          2,
+          2,
+          2,
+          7,
+          2,
+          7,
+          5.788925647735596,
+          5.549378395080566,
+          7,
+          2
+        ],
+        "type": "float32"
+      },
+      "options": {
+        "minValue": 2.0,
+        "maxValue": 7.0
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/concat.json b/testing/web-platform/tests/webnn/resources/test_data/concat.json
new file mode 100644
index 0000000000..9ecc393f89
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/concat.json
@@ -0,0 +1,1799 @@
+{
+  "tests": [
+    // concat 1D tensors
+    {
+      "name": "concat two float32 1D tensors of same shape along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [12],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [12],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 1D tensors of different 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [4],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [8],
+          "data": [
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [12],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat four float32 1D tensors of same 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [6],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [6],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [6],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [6],
+          "data": [
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat four float32 1D tensors of different 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [2],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [4],
+          "data": [
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [8],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [10],
+          "data": [
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    // concat 2D tensors
+    {
+      "name": "concat two float32 2D tensors of same shape along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [2, 6],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [2, 6],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat two float32 2D tensors of same others dimensions except different 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 6],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [3, 6],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat four float32 2D tensors of same shape along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [3, 2],
+          "data": [
+            -0.39444134019222243,
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+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
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+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [3, 2],
+          "data": [
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+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [3, 2],
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+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635
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+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [3, 2],
+          "data": [
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+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [12, 2],
+        "data": [
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+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat two float32 2D tensors of same others dimensions except different 2nd dimension along axis 1",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [2, 10],
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+            -0.9906398615400507,
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+            -0.44735022799701873,
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+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
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+            -0.9158143500894873,
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+            0.6653799854931952,
+            0.03886038855553897
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+          "type": "float32"
+        },
+        {
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+          "shape": [2, 2],
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+            0.1211843166661235
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+      ],
+      "axis": 1,
+      "expected": {
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 2D tensors of same shape along axis 1",
+      "inputs": [
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+          "name": "input1",
+          "shape": [4, 2],
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+            0.3379962524218807,
+            -0.9906398615400507,
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+            0.3227640108329237,
+            -0.44735022799701873,
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+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [4, 2],
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+            -0.40284849555754754,
+            -0.9531654171044694,
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+            -0.34188115459083157,
+            -0.9158143500894873
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+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [4, 2],
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+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
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+          -0.7993468642234802,
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat four float32 2D tensors of same others dimensions except different 2nd dimension along axis 1",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [3, 1],
+          "data": [
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+            0.8619825316530809,
+            0.3379962524218807
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+          "type": "float32"
+        },
+        {
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+          "shape": [3, 2],
+          "data": [
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+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [3, 2],
+          "data": [
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+            -0.9531654171044694,
+            -0.6731740531810844,
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+            -0.15864110312378976,
+            -0.34188115459083157
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+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [3, 3],
+          "data": [
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+            0.1211843166661235
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+          "type": "float32"
+        }
+      ],
+      "axis": 1,
+      "expected": {
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+        "shape": [3, 8],
+        "data": [
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+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    // concat 3D tensors
+    {
+      "name": "concat two float32 3D tensors of same others dimensions except different 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [2, 1, 3],
+          "data": [
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+            0.3227640108329237
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+          "type": "float32"
+        },
+        {
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+          "shape": [6, 1, 3],
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+            0.1211843166661235
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+          "type": "float32"
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+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [8, 1, 3],
+        "data": [
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+        "type": "float32"
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+    },
+    {
+      "name": "concat four float32 3D tensors of same others dimensions except different 2nd dimension along axis 1",
+      "inputs": [
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+          "name": "input1",
+          "shape": [3, 1, 1],
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+            0.3379962524218807
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+          "type": "float32"
+        },
+        {
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+          "shape": [3, 2, 1],
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+        },
+        {
+          "name": "input3",
+          "shape": [3, 2, 1],
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+            -0.34188115459083157
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+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [3, 3, 1],
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+            0.1211843166661235
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+          "type": "float32"
+        }
+      ],
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [3, 8, 1],
+        "data": [
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+          -0.3418811559677124,
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+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 3D tensors of same shape along axis 2",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [2, 2, 2],
+          "data": [
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+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932
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+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [2, 2, 2],
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+            -0.34188115459083157,
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+          "type": "float32"
+        },
+        {
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+          "shape": [2, 2, 2],
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+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 2,
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 6],
+        "data": [
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+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    // concat 4D tensors
+    {
+      "name": "concat two float32 4D tensors of same others dimensions except different 1st dimension along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 3, 1, 2],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [3, 3, 1, 2],
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+            0.1211843166661235
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+          "type": "float32"
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+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [4, 3, 1, 2],
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+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 4D tensors of same shape along axis 1",
+      "inputs": [
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+          "name": "input1",
+          "shape": [2, 2, 1, 2],
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+          "type": "float32"
+        },
+        {
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+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [2, 2, 1, 2],
+          "data": [
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [2, 6, 1, 2],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
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+          -0.7206121683120728,
+          -0.7993468642234802,
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+          -0.44735023379325867,
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+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 4D tensors of same others dimensions except different 3rd dimension along axis 2",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 2, 2, 1],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 2, 8, 1],
+          "data": [
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [1, 2, 2, 1],
+          "data": [
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 2,
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 12, 1],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.5182055234909058,
+          -0.8742017149925232,
+          0.337996244430542,
+          -0.990639865398407,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat four float32 4D tensors of same others dimensions except different 4th dimension along axis 3",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 3, 1, 1],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 3, 1, 1],
+          "data": [
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [1, 3, 1, 2],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape": [1, 3, 1, 4],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 3,
+      "expected": {
+        "name": "output",
+        "shape": [1, 3, 1, 8],
+        "data": [
+          -0.3944413363933563,
+          -0.990639865398407,
+          -0.44735023379325867,
+          0.11028251051902771,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          0.861982524394989,
+          0.576785683631897,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.337996244430542,
+          0.32276400923728943,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    // concat 5D tensors
+    {
+      "name": "concat four float32 5D tensors of same shape along axis 0",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 2, 1, 1, 3],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 2, 1, 1, 3],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [1, 2, 1, 1, 3],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input4",
+          "shape":[1, 2, 1, 1, 3],
+          "data": [
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 0,
+      "expected": {
+        "name": "output",
+        "shape": [4, 2, 1, 1, 3],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat two float32 5D tensors of same others dimensions except different 2nd dimension along axis 1",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 2, 3, 1, 1],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 6, 3, 1, 1],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 1,
+      "expected": {
+        "name": "output",
+        "shape": [1, 8, 3, 1, 1],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat three float32 5D tensors of same others dimensions except different 3rd dimension along axis 2",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 2, 1, 1, 2],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 2, 2, 1, 2],
+          "data": [
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input3",
+          "shape": [1, 2, 3, 1, 2],
+          "data": [
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 2,
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 6, 1, 2],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.337996244430542,
+          -0.990639865398407,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat two float32 5D tensors of same others dimensions except different 4th dimension along axis 3",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [3, 1, 1, 1, 2],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [3, 1, 1, 3, 2],
+          "data": [
+            -0.44735022799701873,
+            0.11028251232581932,
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 3,
+      "expected": {
+        "name": "output",
+        "shape": [3, 1, 1, 4, 2],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.337996244430542,
+          -0.990639865398407,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.576785683631897,
+          0.32276400923728943,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "concat two float32 5D tensors of same others dimensions except different 5th dimension along axis 4",
+      "inputs": [
+        {
+          "name": "input1",
+          "shape": [1, 2, 1, 1, 4],
+          "data": [
+            -0.39444134019222243,
+            0.8619825316530809,
+            0.3379962524218807,
+            -0.9906398615400507,
+            0.576785657225761,
+            0.3227640108329237,
+            -0.44735022799701873,
+            0.11028251232581932
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "input2",
+          "shape": [1, 2, 1, 1, 8],
+          "data": [
+            -0.5945112749179908,
+            -0.40284849555754754,
+            -0.9531654171044694,
+            -0.6731740531810844,
+            0.4918989118791477,
+            -0.15864110312378976,
+            -0.34188115459083157,
+            -0.9158143500894873,
+            -0.7206121708970712,
+            -0.7993468785008635,
+            0.6653799854931952,
+            0.03886038855553897,
+            0.5182055416768865,
+            -0.8742016938344297,
+            -0.479021891130635,
+            0.1211843166661235
+          ],
+          "type": "float32"
+        }
+      ],
+      "axis": 4,
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 1, 12],
+        "data": [
+          -0.3944413363933563,
+          0.861982524394989,
+          0.337996244430542,
+          -0.990639865398407,
+          -0.5945112705230713,
+          -0.402848482131958,
+          -0.9531654119491577,
+          -0.6731740236282349,
+          0.49189892411231995,
+          -0.15864109992980957,
+          -0.3418811559677124,
+          -0.9158143401145935,
+          0.576785683631897,
+          0.32276400923728943,
+          -0.44735023379325867,
+          0.11028251051902771,
+          -0.7206121683120728,
+          -0.7993468642234802,
+          0.6653800010681152,
+          0.03886038810014725,
+          0.5182055234909058,
+          -0.8742017149925232,
+          -0.4790218770503998,
+          0.1211843192577362
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/conv2d.json b/testing/web-platform/tests/webnn/resources/test_data/conv2d.json
new file mode 100644
index 0000000000..850897df4e
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/conv2d.json
@@ -0,0 +1,2144 @@
+{
+  "tests": [
+    {
+      "name": "conv2d float32 4D input and filter(non-constant) tensors default options",
+      "inputs": {
+        "input": {
+          "shape": [1, 1, 5, 5],
+          "data": [
+            0.6124474607869732,
+            0.8857858599952035,
+            0.13667134799354397,
+            0.564529098909835,
+            0.8965171985225997,
+            0.36792828664768873,
+            0.6811466319147079,
+            0.04795110047019757,
+            0.33355462154327986,
+            0.19882695924603588,
+            0.4116714070095846,
+            0.07934240242135737,
+            0.42724633975875426,
+            0.5358005687699703,
+            0.5910805999797129,
+            0.2841543363273238,
+            0.414725865128835,
+            0.026906268886554896,
+            0.3621256577250671,
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json b/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json
new file mode 100644
index 0000000000..c7026f91ee
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/conv_transpose2d.json
@@ -0,0 +1,2087 @@
+{
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+          2.121230363845825,
+          1.141642689704895,
+          0.4301592707633972,
+          0.18141157925128937,
+          1.0035220384597778,
+          1.3417718410491943,
+          0.8345021605491638,
+          0.2249351441860199,
+          0.027173593640327454,
+          0.3026771545410156,
+          0.5856420397758484,
+          0.40328359603881836,
+          0.09216563403606415
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "convTranspose2d float32 4D input and filter tensors options.bias",
+      "inputs": {
+        "input": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            0.11095754619056808,
+            0.8681362056660518,
+            0.7342095941654914,
+            0.43077004493855875,
+            0.5981626867187566,
+            0.1232164990736122,
+            0.16109748910776922,
+            0.08840264384189989,
+            0.2910097194319563
+          ],
+          "type": "float32"
+        },
+        "filter": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            0.6161394585554596,
+            0.262246148184051,
+            0.7951397994036709,
+            0.87305609470791,
+            0.8309101763741125,
+            0.8549605393357718,
+            0.5552039743814143,
+            0.8400921243865438,
+            0.8530843869413023
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "bias": {
+          "shape": [1],
+          "data": [
+            0.4516736859570645
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "shape": [1, 1, 5, 5],
+        "data": [
+          0.5200390219688416,
+          1.01566481590271,
+          1.2199413776397705,
+          1.3345069885253906,
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+          0.9886226654052734,
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+          2.9867470264434814,
+          2.5694668292999268,
+          1.41475510597229,
+          0.8314860463142395,
+          1.3567005395889282,
+          1.8553334474563599,
+          1.3828538656234741,
+          0.8055896162986755,
+          0.5411156415939331,
+          0.6360918879508972,
+          0.8249395489692688,
+          0.7715635895729065,
+          0.6999295353889465
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "convTranspose2d float32 4D input and filter tensors, both negative input tensor and options.bias",
+      "inputs": {
+        "input": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            -0.1088905666228781,
+            -0.2980190376593821,
+            -0.39077856560563506,
+            -0.5624061411820445,
+            -0.732209362325523,
+            -0.8421320780728827,
+            -0.3059865397862138,
+            -0.9766599001467926,
+            -0.014158561610918996
+          ],
+          "type": "float32"
+        },
+        "filter": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            0.6161394585554596,
+            0.262246148184051,
+            0.7951397994036709,
+            0.87305609470791,
+            0.8309101763741125,
+            0.8549605393357718,
+            0.5552039743814143,
+            0.8400921243865438,
+            0.8530843869413023
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "bias": {
+          "shape": [1],
+          "data": [
+            -0.8457866242505638
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "shape": [1, 1, 5, 5],
+        "data": [
+          -0.9128783941268921,
+          -1.0579640865325928,
+          -1.2512983083724976,
+          -1.1852335929870605,
+          -1.1565102338790894,
+          -1.2873748540878296,
+          -1.7950842380523682,
+          -2.6857638359069824,
+          -2.2283377647399902,
+          -1.8494995832443237,
+          -1.5857856273651123,
+          -2.8912975788116455,
+          -3.738619565963745,
+          -3.5343525409698486,
+          -1.910401463508606,
+          -1.425180196762085,
+          -2.8317112922668457,
+          -3.49372935295105,
+          -3.0246617794036865,
+          -1.5763013362884521,
+          -1.0156716108322144,
+          -1.645089030265808,
+          -1.935164213180542,
+          -1.6908544301986694,
+          -0.8578650951385498
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "convTranspose2d float32 4D input and filter tensors options.activation=relu",
+      "inputs": {
+        "input": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            0.11095754619056808,
+            0.8681362056660518,
+            0.7342095941654914,
+            0.43077004493855875,
+            0.5981626867187566,
+            0.1232164990736122,
+            0.16109748910776922,
+            0.08840264384189989,
+            0.2910097194319563
+          ],
+          "type": "float32"
+        },
+        "filter": {
+          "shape": [1, 1, 3, 3],
+          "data": [
+            0.6161394585554596,
+            0.262246148184051,
+            0.7951397994036709,
+            0.87305609470791,
+            0.8309101763741125,
+            0.8549605393357718,
+            0.5552039743814143,
+            0.8400921243865438,
+            0.8530843869413023
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
+        "activation": "relu" // relu operator
+      },
+      "expected": {
+        "shape": [1, 1, 5, 5],
+        "data": [
+          0.06836532801389694,
+          0.5639911890029907,
+          0.7682676911354065,
+          0.8828333020210266,
+          0.5837992429733276,
+          0.36228659749031067,
+          1.3316468000411987,
+          2.0325205326080322,
+          1.8602205514907837,
+          0.7256945967674255,
+          0.5369489789009094,
+          1.5520836114883423,
+          2.5350732803344727,
+          2.117793083190918,
+          0.963081419467926,
+          0.3798123896121979,
+          0.9050268530845642,
+          1.403659701347351,
+          0.9311801791191101,
+          0.35391589999198914,
+          0.08944196254014969,
+          0.1844182312488556,
+          0.3732658624649048,
+          0.3198899030685425,
+          0.24825584888458252
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/cos.json b/testing/web-platform/tests/webnn/resources/test_data/cos.json
new file mode 100644
index 0000000000..4d99232550
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/cos.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
+    {
+      "name": "cos float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            85.56368722678593,
+            -45.09983640817779,
+            -94.6775036804249,
+            83.49029219662862,
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+            70.1804254973957,
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+            -83.00758001757269,
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+            -32.51877900985289,
+            -48.376587517032775,
+            -58.02735967650854,
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+            -98.67289449592316,
+            -63.611559926077675,
+            26.857246203003186,
+            83.70417131490925,
+            76.56606838780263,
+            -47.83436545380422
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.7380040884017944,
+          0.43789437413215637,
+          0.9090799689292908,
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+          -0.1531042903661728,
+          -0.43673399090766907,
+          0.39213326573371887,
+          -0.7580515146255493
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "cos float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            85.56368722678593,
+            -45.09983640817779,
+            -94.6775036804249,
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+            83.70417131490925,
+            76.56606838780263,
+            -47.83436545380422
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -0.7380040884017944,
+          0.43789437413215637,
+          0.9090799689292908,
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+          -0.1531042903661728,
+          -0.43673399090766907,
+          0.39213326573371887,
+          -0.7580515146255493
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "cos float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            85.56368722678593,
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+            83.70417131490925,
+            76.56606838780263,
+            -47.83436545380422
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          -0.7380040884017944,
+          0.43789437413215637,
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+          -0.1531042903661728,
+          -0.43673399090766907,
+          0.39213326573371887,
+          -0.7580515146255493
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "cos float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            85.56368722678593,
+            -45.09983640817779,
+            -94.6775036804249,
+            83.49029219662862,
+            -31.367904335227692,
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+            -59.05887786348942,
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+            -98.67289449592316,
+            -63.611559926077675,
+            26.857246203003186,
+            83.70417131490925,
+            76.56606838780263,
+            -47.83436545380422
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          -0.7380040884017944,
+          0.43789437413215637,
+          0.9090799689292908,
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+          -0.1531042903661728,
+          -0.43673399090766907,
+          0.39213326573371887,
+          -0.7580515146255493
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "cos float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            85.56368722678593,
+            -45.09983640817779,
+            -94.6775036804249,
+            83.49029219662862,
+            -31.367904335227692,
+            70.1804254973957,
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+            61.51649571682452,
+            -32.51877900985289,
+            -48.376587517032775,
+            -58.02735967650854,
+            89.79197789644661,
+            -84.53326629430444,
+            -58.23252607768894,
+            -76.14168597373077,
+            -59.05887786348942,
+            77.38546821194151,
+            -98.67289449592316,
+            -63.611559926077675,
+            26.857246203003186,
+            83.70417131490925,
+            76.56606838780263,
+            -47.83436545380422
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          -0.7380040884017944,
+          0.43789437413215637,
+          0.9090799689292908,
+          -0.23584702610969543,
+          0.9988471865653992,
+          0.48416373133659363,
+          -0.7358400821685791,
+          0.24218930304050446,
+          0.25266921520233154,
+          0.4510514736175537,
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+          0.09197491407394409,
+          -0.2537800967693329,
+          -0.9583188891410828,
+          -0.11282006651163101,
+          0.736129879951477,
+          -0.80721116065979,
+          -0.4045141637325287,
+          -0.283336341381073,
+          0.7111190557479858,
+          -0.1531042903661728,
+          -0.43673399090766907,
+          0.39213326573371887,
+          -0.7580515146255493
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/div.json b/testing/web-platform/tests/webnn/resources/test_data/div.json
new file mode 100644
index 0000000000..d72544e8ec
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/div.json
@@ -0,0 +1,784 @@
+{
+  "tests": [
+    {
+      "name": "div float32 1D tensors",
+      "inputs": {
+        "a": {
+          "shape": [24],
+          "data": [
+            60.42374184854583,
+            -86.92247771592565,
+            -19.496113538677307,
+            -15.150616021872224,
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+            44.565997906464105,
+            -34.892785072690245,
+            -74.09375203216162
+          ],
+          "type": "float32"
+        },
+        "b": {
+          "shape": [24],
+          "data": [
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+            -85.32865597192423,
+            -68.20919717822437,
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+            -10.000411029009541,
+            18.318865013229242,
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+            -5.957828048196006,
+            89.49882849628409,
+            94.95791079054848,
+            -79.00059056550418,
+            -79.87597038424425,
+            74.997874802068,
+            25.86537368134097,
+            91.54433121797925,
+            81.65287344691947,
+            48.214831959279195,
+            63.37012091471408,
+            10.62638472655793,
+            46.12662564540156,
+            77.2232730204774
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "ouput",
+        "shape": [24],
+        "data": [
+          -0.6358450651168823,
+          -1.3840086460113525,
+          0.22848258912563324,
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+            14.369060854798647,
+            13.94319409117783,
+            16.861190475721344,
+            4.816806540352701,
+            44.15916607007162,
+            -13.083211898368276,
+            44.565997906464105,
+            -34.892785072690245,
+            -74.09375203216162
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "ouput",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          -0.6922348141670227,
+          0.48120367527008057,
+          2.145423412322998,
+          2.7607734203338623,
+          -3.10864520072937,
+          -0.9206274151802063,
+          -0.6847651600837708,
+          -0.5914608240127563,
+          1.337254285812378,
+          -0.7458055019378662,
+          -1.0726968050003052,
+          12.770289421081543,
+          -1.2953946590423584,
+          11.376836776733398,
+          -0.4729740023612976,
+          -2.910935878753662,
+          -2.999844551086426,
+          -2.48069167137146,
+          -8.683640480041504,
+          -0.9471967220306396,
+          3.1970295906066895,
+          -0.9385499358177185,
+          1.19874107837677,
+          0.5645201802253723
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/elu.json b/testing/web-platform/tests/webnn/resources/test_data/elu.json
new file mode 100644
index 0000000000..68c0c80c59
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/elu.json
@@ -0,0 +1,472 @@
+{ // elu: The calculation follows the expression max(0, x) + alpha * (exp(min(0, x)) - 1).
+  "tests": [
+    {
+      "name": "elu float32 1D tensor default options", // default options: {alpha: 1}
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.9790657162666321,
+          1.3590080738067627,
+          -0.9790199995040894,
+          7.839725494384766,
+          -0.9987577199935913,
+          0.5456406474113464,
+          5.776711463928223,
+          7.263273239135742,
+          -0.999400794506073,
+          5.665064334869385,
+          -0.9987848997116089,
+          -0.9643816947937012,
+          -0.7019122838973999,
+          7.255547046661377,
+          8.903468132019043,
+          -0.982044517993927,
+          7.114678382873535,
+          -0.10607059299945831,
+          -0.9749990105628967,
+          6.135150909423828,
+          -0.99994957447052
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 2D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.9790657162666321,
+          1.3590080738067627,
+          -0.9790199995040894,
+          7.839725494384766,
+          -0.9987577199935913,
+          0.5456406474113464,
+          5.776711463928223,
+          7.263273239135742,
+          -0.999400794506073,
+          5.665064334869385,
+          -0.9987848997116089,
+          -0.9643816947937012,
+          -0.7019122838973999,
+          7.255547046661377,
+          8.903468132019043,
+          -0.982044517993927,
+          7.114678382873535,
+          -0.10607059299945831,
+          -0.9749990105628967,
+          6.135150909423828,
+          -0.99994957447052
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 3D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.9790657162666321,
+          1.3590080738067627,
+          -0.9790199995040894,
+          7.839725494384766,
+          -0.9987577199935913,
+          0.5456406474113464,
+          5.776711463928223,
+          7.263273239135742,
+          -0.999400794506073,
+          5.665064334869385,
+          -0.9987848997116089,
+          -0.9643816947937012,
+          -0.7019122838973999,
+          7.255547046661377,
+          8.903468132019043,
+          -0.982044517993927,
+          7.114678382873535,
+          -0.10607059299945831,
+          -0.9749990105628967,
+          6.135150909423828,
+          -0.99994957447052
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 4D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.9790657162666321,
+          1.3590080738067627,
+          -0.9790199995040894,
+          7.839725494384766,
+          -0.9987577199935913,
+          0.5456406474113464,
+          5.776711463928223,
+          7.263273239135742,
+          -0.999400794506073,
+          5.665064334869385,
+          -0.9987848997116089,
+          -0.9643816947937012,
+          -0.7019122838973999,
+          7.255547046661377,
+          8.903468132019043,
+          -0.982044517993927,
+          7.114678382873535,
+          -0.10607059299945831,
+          -0.9749990105628967,
+          6.135150909423828,
+          -0.99994957447052
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 5D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 3, 4],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.9790657162666321,
+          1.3590080738067627,
+          -0.9790199995040894,
+          7.839725494384766,
+          -0.9987577199935913,
+          0.5456406474113464,
+          5.776711463928223,
+          7.263273239135742,
+          -0.999400794506073,
+          5.665064334869385,
+          -0.9987848997116089,
+          -0.9643816947937012,
+          -0.7019122838973999,
+          7.255547046661377,
+          8.903468132019043,
+          -0.982044517993927,
+          7.114678382873535,
+          -0.10607059299945831,
+          -0.9749990105628967,
+          6.135150909423828,
+          -0.99994957447052
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 4D tensor positive options.alpha",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
+            7.839725573639406,
+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "alpha": 0.3607245505146506
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          -0.35317301750183105,
+          1.3590080738067627,
+          -0.35315653681755066,
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+          -0.36050841212272644,
+          5.665064334869385,
+          -0.3602862060070038,
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+          -0.0382622666656971,
+          -0.3517060875892639,
+          6.135150909423828,
+          -0.3607063591480255
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "elu float32 4D tensor negative options.alpha",
+        "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
+            4.721739616402454,
+            0.37687805459885837,
+            1.4189998297338988,
+            -3.866366516102673,
+            1.3590080831697868,
+            -3.8641844556612392,
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+            -6.690801377003339,
+            0.545640671378024,
+            5.776711453839759,
+            7.263273186498619,
+            -7.419948093040434,
+            5.665064356187175,
+            -6.712906923265587,
+            -3.3348948531721945,
+            -1.2103675328053143,
+            7.255546982014842,
+            8.903468527480992,
+            -4.019860311974934,
+            7.114678383091487,
+            -0.11212847159184136,
+            -3.688840965850466,
+            6.135151096361078,
+            -9.895182558358613
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "alpha": -3.468180406374035
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "data": [
+          4.721739768981934,
+          0.3768780529499054,
+          1.4189997911453247,
+          3.3955764770507812,
+          1.3590080738067627,
+          3.3954179286956787,
+          7.839725494384766,
+          3.463871955871582,
+          0.5456406474113464,
+          5.776711463928223,
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+          3.466102361679077,
+          5.665064334869385,
+          3.463966131210327,
+          3.34464955329895,
+          2.434358596801758,
+          7.255547046661377,
+          8.903468132019043,
+          3.40590763092041,
+          7.114678382873535,
+          0.3678719699382782,
+          3.381472587585449,
+          6.135150909423828,
+          3.468005657196045
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/exp.json b/testing/web-platform/tests/webnn/resources/test_data/exp.json
new file mode 100644
index 0000000000..886729f2e8
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/exp.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
+    {
+      "name": "exp float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            1.5401084737753479,
+            12.774433809954473,
+            61.46073034406041,
+            30.371593690722648,
+            -23.07019138708837,
+            6.286732075092644,
+            24.049592392056553,
+            59.17023846672603,
+            -72.39779325866608,
+            76.17325870390891,
+            42.745124211838345,
+            31.50150770254453,
+            15.485609808293518,
+            -11.397760090390022,
+            50.36123123038939,
+            -83.05469409695672,
+            24.110038122659418,
+            -28.330545051670825,
+            -53.749036944957986,
+            -78.11921866998134,
+            -83.41683875349166,
+            -89.72063026731117,
+            -68.90046001676907,
+            -71.89803038543928
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          4.665096282958984,
+          353074.40625,
+          4.92103607186909e+26,
+          15495851933696,
+          9.566272773930962e-11,
+          537.3943481445312,
+          27835916288,
+          4.980902673917305e+25,
+          3.614401801447914e-32,
+          1.2067705660062333e+33,
+          3664138167604216000,
+          47965678862336,
+          5312696,
+          0.000011220586202398408,
+          7.440557948065475e+21,
+          8.507544403157469e-37,
+          29570371584,
+          4.968216051233487e-13,
+          4.54034731570652e-24,
+          1.1837368161912076e-34,
+          5.922797145303594e-37,
+          1.0834951830036632e-39,
+          1.1937427251244527e-30,
+          5.957731569649706e-32
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "exp float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            1.5401084737753479,
+            12.774433809954473,
+            61.46073034406041,
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+            24.110038122659418,
+            -28.330545051670825,
+            -53.749036944957986,
+            -78.11921866998134,
+            -83.41683875349166,
+            -89.72063026731117,
+            -68.90046001676907,
+            -71.89803038543928
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          4.665096282958984,
+          353074.40625,
+          4.92103607186909e+26,
+          15495851933696,
+          9.566272773930962e-11,
+          537.3943481445312,
+          27835916288,
+          4.980902673917305e+25,
+          3.614401801447914e-32,
+          1.2067705660062333e+33,
+          3664138167604216000,
+          47965678862336,
+          5312696,
+          0.000011220586202398408,
+          7.440557948065475e+21,
+          8.507544403157469e-37,
+          29570371584,
+          4.968216051233487e-13,
+          4.54034731570652e-24,
+          1.1837368161912076e-34,
+          5.922797145303594e-37,
+          1.0834951830036632e-39,
+          1.1937427251244527e-30,
+          5.957731569649706e-32
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "exp float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            1.5401084737753479,
+            12.774433809954473,
+            61.46073034406041,
+            30.371593690722648,
+            -23.07019138708837,
+            6.286732075092644,
+            24.049592392056553,
+            59.17023846672603,
+            -72.39779325866608,
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+            42.745124211838345,
+            31.50150770254453,
+            15.485609808293518,
+            -11.397760090390022,
+            50.36123123038939,
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+            -28.330545051670825,
+            -53.749036944957986,
+            -78.11921866998134,
+            -83.41683875349166,
+            -89.72063026731117,
+            -68.90046001676907,
+            -71.89803038543928
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          4.665096282958984,
+          353074.40625,
+          4.92103607186909e+26,
+          15495851933696,
+          9.566272773930962e-11,
+          537.3943481445312,
+          27835916288,
+          4.980902673917305e+25,
+          3.614401801447914e-32,
+          1.2067705660062333e+33,
+          3664138167604216000,
+          47965678862336,
+          5312696,
+          0.000011220586202398408,
+          7.440557948065475e+21,
+          8.507544403157469e-37,
+          29570371584,
+          4.968216051233487e-13,
+          4.54034731570652e-24,
+          1.1837368161912076e-34,
+          5.922797145303594e-37,
+          1.0834951830036632e-39,
+          1.1937427251244527e-30,
+          5.957731569649706e-32
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "exp float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            1.5401084737753479,
+            12.774433809954473,
+            61.46073034406041,
+            30.371593690722648,
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+            24.049592392056553,
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+            31.50150770254453,
+            15.485609808293518,
+            -11.397760090390022,
+            50.36123123038939,
+            -83.05469409695672,
+            24.110038122659418,
+            -28.330545051670825,
+            -53.749036944957986,
+            -78.11921866998134,
+            -83.41683875349166,
+            -89.72063026731117,
+            -68.90046001676907,
+            -71.89803038543928
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          4.665096282958984,
+          353074.40625,
+          4.92103607186909e+26,
+          15495851933696,
+          9.566272773930962e-11,
+          537.3943481445312,
+          27835916288,
+          4.980902673917305e+25,
+          3.614401801447914e-32,
+          1.2067705660062333e+33,
+          3664138167604216000,
+          47965678862336,
+          5312696,
+          0.000011220586202398408,
+          7.440557948065475e+21,
+          8.507544403157469e-37,
+          29570371584,
+          4.968216051233487e-13,
+          4.54034731570652e-24,
+          1.1837368161912076e-34,
+          5.922797145303594e-37,
+          1.0834951830036632e-39,
+          1.1937427251244527e-30,
+          5.957731569649706e-32
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "exp float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            1.5401084737753479,
+            12.774433809954473,
+            61.46073034406041,
+            30.371593690722648,
+            -23.07019138708837,
+            6.286732075092644,
+            24.049592392056553,
+            59.17023846672603,
+            -72.39779325866608,
+            76.17325870390891,
+            42.745124211838345,
+            31.50150770254453,
+            15.485609808293518,
+            -11.397760090390022,
+            50.36123123038939,
+            -83.05469409695672,
+            24.110038122659418,
+            -28.330545051670825,
+            -53.749036944957986,
+            -78.11921866998134,
+            -83.41683875349166,
+            -89.72063026731117,
+            -68.90046001676907,
+            -71.89803038543928
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          4.665096282958984,
+          353074.40625,
+          4.92103607186909e+26,
+          15495851933696,
+          9.566272773930962e-11,
+          537.3943481445312,
+          27835916288,
+          4.980902673917305e+25,
+          3.614401801447914e-32,
+          1.2067705660062333e+33,
+          3664138167604216000,
+          47965678862336,
+          5312696,
+          0.000011220586202398408,
+          7.440557948065475e+21,
+          8.507544403157469e-37,
+          29570371584,
+          4.968216051233487e-13,
+          4.54034731570652e-24,
+          1.1837368161912076e-34,
+          5.922797145303594e-37,
+          1.0834951830036632e-39,
+          1.1937427251244527e-30,
+          5.957731569649706e-32
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/floor.json b/testing/web-platform/tests/webnn/resources/test_data/floor.json
new file mode 100644
index 0000000000..f2fa797d41
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/floor.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
+    {
+      "name": "floor float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            89.69458425635187,
+            -79.6715006046712,
+            -66.80949305244779,
+            -71.88439187517632,
+            86.33935218844132,
+            6.823808491438228,
+            24.908446694609452,
+            0.9734055387608578,
+            19.94818517399692,
+            0.8437776596471878,
+            -24.75293941821147,
+            77.76482131339927,
+            -33.64446543048625,
+            80.77624589277926,
+            44.47844134603099,
+            -37.65005913863395,
+            -83.78780150071003,
+            65.84009074464839,
+            -39.83677499773579,
+            32.52575852910243,
+            -21.21354337121204,
+            -80.30910898865443,
+            16.674850201817335,
+            -72.88893024677465
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          89,
+          -80,
+          -67,
+          -72,
+          86,
+          6,
+          24,
+          0,
+          19,
+          0,
+          -25,
+          77,
+          -34,
+          80,
+          44,
+          -38,
+          -84,
+          65,
+          -40,
+          32,
+          -22,
+          -81,
+          16,
+          -73
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "floor float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            89.69458425635187,
+            -79.6715006046712,
+            -66.80949305244779,
+            -71.88439187517632,
+            86.33935218844132,
+            6.823808491438228,
+            24.908446694609452,
+            0.9734055387608578,
+            19.94818517399692,
+            0.8437776596471878,
+            -24.75293941821147,
+            77.76482131339927,
+            -33.64446543048625,
+            80.77624589277926,
+            44.47844134603099,
+            -37.65005913863395,
+            -83.78780150071003,
+            65.84009074464839,
+            -39.83677499773579,
+            32.52575852910243,
+            -21.21354337121204,
+            -80.30910898865443,
+            16.674850201817335,
+            -72.88893024677465
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          89,
+          -80,
+          -67,
+          -72,
+          86,
+          6,
+          24,
+          0,
+          19,
+          0,
+          -25,
+          77,
+          -34,
+          80,
+          44,
+          -38,
+          -84,
+          65,
+          -40,
+          32,
+          -22,
+          -81,
+          16,
+          -73
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "floor float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            89.69458425635187,
+            -79.6715006046712,
+            -66.80949305244779,
+            -71.88439187517632,
+            86.33935218844132,
+            6.823808491438228,
+            24.908446694609452,
+            0.9734055387608578,
+            19.94818517399692,
+            0.8437776596471878,
+            -24.75293941821147,
+            77.76482131339927,
+            -33.64446543048625,
+            80.77624589277926,
+            44.47844134603099,
+            -37.65005913863395,
+            -83.78780150071003,
+            65.84009074464839,
+            -39.83677499773579,
+            32.52575852910243,
+            -21.21354337121204,
+            -80.30910898865443,
+            16.674850201817335,
+            -72.88893024677465
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          89,
+          -80,
+          -67,
+          -72,
+          86,
+          6,
+          24,
+          0,
+          19,
+          0,
+          -25,
+          77,
+          -34,
+          80,
+          44,
+          -38,
+          -84,
+          65,
+          -40,
+          32,
+          -22,
+          -81,
+          16,
+          -73
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "floor float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            89.69458425635187,
+            -79.6715006046712,
+            -66.80949305244779,
+            -71.88439187517632,
+            86.33935218844132,
+            6.823808491438228,
+            24.908446694609452,
+            0.9734055387608578,
+            19.94818517399692,
+            0.8437776596471878,
+            -24.75293941821147,
+            77.76482131339927,
+            -33.64446543048625,
+            80.77624589277926,
+            44.47844134603099,
+            -37.65005913863395,
+            -83.78780150071003,
+            65.84009074464839,
+            -39.83677499773579,
+            32.52575852910243,
+            -21.21354337121204,
+            -80.30910898865443,
+            16.674850201817335,
+            -72.88893024677465
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          89,
+          -80,
+          -67,
+          -72,
+          86,
+          6,
+          24,
+          0,
+          19,
+          0,
+          -25,
+          77,
+          -34,
+          80,
+          44,
+          -38,
+          -84,
+          65,
+          -40,
+          32,
+          -22,
+          -81,
+          16,
+          -73
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "floor float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            89.69458425635187,
+            -79.6715006046712,
+            -66.80949305244779,
+            -71.88439187517632,
+            86.33935218844132,
+            6.823808491438228,
+            24.908446694609452,
+            0.9734055387608578,
+            19.94818517399692,
+            0.8437776596471878,
+            -24.75293941821147,
+            77.76482131339927,
+            -33.64446543048625,
+            80.77624589277926,
+            44.47844134603099,
+            -37.65005913863395,
+            -83.78780150071003,
+            65.84009074464839,
+            -39.83677499773579,
+            32.52575852910243,
+            -21.21354337121204,
+            -80.30910898865443,
+            16.674850201817335,
+            -72.88893024677465
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          89,
+          -80,
+          -67,
+          -72,
+          86,
+          6,
+          24,
+          0,
+          19,
+          0,
+          -25,
+          77,
+          -34,
+          80,
+          44,
+          -38,
+          -84,
+          65,
+          -40,
+          32,
+          -22,
+          -81,
+          16,
+          -73
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/gemm.json b/testing/web-platform/tests/webnn/resources/test_data/gemm.json
new file mode 100644
index 0000000000..3738e19f7c
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/gemm.json
@@ -0,0 +1,1856 @@
+{
+  "tests": [
+    {
+      "name": "gemm two float32 2D tensors (b is non-constant) default options",
+      "inputs": {
+        "a": {
+          "shape": [3, 4],
+          "data": [
+            82.98884511142329,
+            90.51641254722982,
+            59.6385201162642,
+            36.27187180381433,
+            18.96485038946509,
+            43.89479290862091,
+            98.89487912764056,
+            91.46013741088626,
+            50.51683887619669,
+            40.45679629199866,
+            50.76741460760452,
+            9.336554329198155
+          ],
+          "type": "float32"
+        },
+        "b": {
+          "shape": [4, 5],
+          "data": [
+            25.14739246484985,
+            66.69238549579231,
+            63.29909902139696,
+            10.629964783998469,
+            61.32737573972831,
+            0.003725653326558387,
+            16.499146388625483,
+            3.0366680571384252,
+            93.14021782678614,
+            70.08265680040718,
+            75.74880854000601,
+            96.6068806977233,
+            99.10042039275365,
+            23.243775283337477,
+            86.1185682132947,
+            42.90679144336773,
+            34.08055187293266,
+            87.37654561544477,
+            92.34209530787089,
+            60.32208994273669
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 5],
+        "data": [
+          8161.14697265625,
+          14025.82421875,
+          14607.5009765625,
+          14048.5322265625,
+          18757.09765625,
+          11892.5107421875,
+          14659.9755859375,
+          19125.74609375,
+          15034.27734375,
+          18273.080078125,
+          5516.6904296875,
+          9259.267578125,
+          9167.3916015625,
+          6347.330078125,
+          10868.6025390625
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "gemm two float32 2D tensors default options",
+      "inputs": {
+        "a": {
+          "shape": [3, 4],
+          "data": [
+            82.98884511142329,
+            90.51641254722982,
+            59.6385201162642,
+            36.27187180381433,
+            18.96485038946509,
+            43.89479290862091,
+            98.89487912764056,
+            91.46013741088626,
+            50.51683887619669,
+            40.45679629199866,
+            50.76741460760452,
+            9.336554329198155
+          ],
+          "type": "float32"
+        },
+        "b": {
+          "shape": [4, 5],
+          "data": [
+            25.14739246484985,
+            66.69238549579231,
+            63.29909902139696,
+            10.629964783998469,
+            61.32737573972831,
+            0.003725653326558387,
+            16.499146388625483,
+            3.0366680571384252,
+            93.14021782678614,
+            70.08265680040718,
+            75.74880854000601,
+            96.6068806977233,
+            99.10042039275365,
+            23.243775283337477,
+            86.1185682132947,
+            42.90679144336773,
+            34.08055187293266,
+            87.37654561544477,
+            92.34209530787089,
+            60.32208994273669
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 5],
+        "data": [
+          8161.14697265625,
+          14025.82421875,
+          14607.5009765625,
+          14048.5322265625,
+          18757.09765625,
+          11892.5107421875,
+          14659.9755859375,
+          19125.74609375,
+          15034.27734375,
+          18273.080078125,
+          5516.6904296875,
+          9259.267578125,
+          9167.3916015625,
+          6347.330078125,
+          10868.6025390625
+        ],
+        "type": "float32"
+      }
+    },
+    // options.c
+    {
+      "name": "gemm two float32 2D tensors options.c",
+      "inputs": {
+        "a": {
+          "shape": [3, 4],
+          "data": [
+            82.98884511142329,
+            90.51641254722982,
+            59.6385201162642,
+            36.27187180381433,
+            18.96485038946509,
+            43.89479290862091,
+            98.89487912764056,
+            91.46013741088626,
+            50.51683887619669,
+            40.45679629199866,
+            50.76741460760452,
+            9.336554329198155
+          ],
+          "type": "float32"
+        },
+        "b": {
+          "shape": [4, 5],
+          "data": [
+            25.14739246484985,
+            66.69238549579231,
+            63.29909902139696,
+            10.629964783998469,
+            61.32737573972831,
+            0.003725653326558387,
+            16.499146388625483,
+            3.0366680571384252,
+            93.14021782678614,
+            70.08265680040718,
+            75.74880854000601,
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+    {
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+      "inputs": {
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+          "data": [
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+          "type": "float32",
+          "constant": true
+        }
+      },
+      "options": {
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+          ],
+          "type": "float32"
+        },
+        "alpha": -22.611149749186296,
+        "beta": -11.68521964935509
+      },
+      "expected": {
+        "name": "output",
+        "shape": [3, 5],
+        "data": [
+          -185500.109375,
+          -318207.84375,
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "gemm both negative options.alpha and 3rd float32 input tensor (options.c)",
+      "inputs": {
+        "a": {
+          "shape": [3, 4],
+          "data": [
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+          "type": "float32"
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+        "alpha": -22.611149749186296
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+      "expected": {
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+        "shape": [3, 5],
+        "data": [
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+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/hard_sigmoid.json b/testing/web-platform/tests/webnn/resources/test_data/hard_sigmoid.json
new file mode 100644
index 0000000000..22fe7c6da0
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/hard_sigmoid.json
@@ -0,0 +1,890 @@
+{ // hardSigmoid: Calculate the non-smooth function used in place of a sigmoid function on the input tensor.
+  "tests": [
+    {
+      "name": "hardSigmoid float32 positive 1D tensor default options", // default options: {alpha: 0.2, beta: 0.5}
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
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+            0.7311381962152534,
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+            0.7766845231174959,
+            0.8455570201933926,
+            0.5553020911955322,
+            0.5603444395469193
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          0.5118141174316406,
+          0.6415218114852905,
+          0.6045681238174438,
+          0.5846202969551086,
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+          0.5218378305435181,
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+          0.6064510345458984,
+          0.6368615627288818,
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+          0.5609799027442932,
+          0.6605174541473389,
+          0.5497192740440369,
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+          0.6109522581100464,
+          0.6108517050743103,
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+          0.6553369164466858,
+          0.669111430644989,
+          0.6110604405403137,
+          0.6120688915252686
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "hardSigmoid float32 positive 2D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
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+            0.8455570201933926,
+            0.5553020911955322,
+            0.5603444395469193
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
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+          0.6415218114852905,
+          0.6045681238174438,
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+          0.669111430644989,
+          0.6110604405403137,
+          0.6120688915252686
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "hardSigmoid float32 positive 3D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            0.05907066981577147,
+            0.7076089198897,
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+            0.8025872652109942,
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+            0.6636898942337357,
+            0.554761182646025,
+            0.5542584257213008,
+            0.7311381962152534,
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+            0.5553020911955322,
+            0.5603444395469193
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "hardSigmoid float32 positive 4D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
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+            0.5553020911955322,
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "data": [
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "hardSigmoid float32 positive 5D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
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+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 3, 4],
+        "data": [
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "hardSigmoid float32 positive 4D tensor specified positive options.alpha default options.beta",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
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+            0.7076089198897,
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+      "options": {
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+      "options": {
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+      "expected": {
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+        "data": [
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/hard_swish.json b/testing/web-platform/tests/webnn/resources/test_data/hard_swish.json
new file mode 100644
index 0000000000..8d7812d21e
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/hard_swish.json
@@ -0,0 +1,334 @@
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+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          0.4569105803966522,
+          9.11885929107666,
+          3.545238494873047,
+          2.4567370414733887,
+          0,
+          -0.3693843185901642,
+          5.52318000793457,
+          0,
+          0,
+          6.420943737030029,
+          0,
+          0.7011276483535767,
+          0,
+          -0.3240821659564972,
+          0,
+          3.1852290630340576,
+          0,
+          4.174602508544922,
+          3.7802627086639404,
+          0,
+          0,
+          0,
+          0,
+          8.083491325378418
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/leaky_relu.json b/testing/web-platform/tests/webnn/resources/test_data/leaky_relu.json
new file mode 100644
index 0000000000..a95a9a0cfc
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/leaky_relu.json
@@ -0,0 +1,542 @@
+{
+  "tests": [
+    {
+      "name": "leakyRelu float32 1D tensor default options", // default options.alpha=0.01
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -0.19053640961647034,
+          50.77590560913086,
+          -0.695496678352356,
+          -0.8057432770729065,
+          -0.9040110111236572,
+          76.02884674072266,
+          66.33873748779297,
+          -0.8410186767578125,
+          -0.1719101369380951,
+          -0.8747624158859253,
+          -0.0341646634042263,
+          -0.2277235984802246,
+          -0.02509489096701145,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -0.33178603649139404,
+          -0.4603901207447052,
+          -0.6147925853729248,
+          64.26514434814453,
+          21.469341278076172,
+          -0.31514689326286316,
+          -0.4127694368362427,
+          -0.6559529304504395
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 2D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -0.19053640961647034,
+          50.77590560913086,
+          -0.695496678352356,
+          -0.8057432770729065,
+          -0.9040110111236572,
+          76.02884674072266,
+          66.33873748779297,
+          -0.8410186767578125,
+          -0.1719101369380951,
+          -0.8747624158859253,
+          -0.0341646634042263,
+          -0.2277235984802246,
+          -0.02509489096701145,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -0.33178603649139404,
+          -0.4603901207447052,
+          -0.6147925853729248,
+          64.26514434814453,
+          21.469341278076172,
+          -0.31514689326286316,
+          -0.4127694368362427,
+          -0.6559529304504395
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 3D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          -0.19053640961647034,
+          50.77590560913086,
+          -0.695496678352356,
+          -0.8057432770729065,
+          -0.9040110111236572,
+          76.02884674072266,
+          66.33873748779297,
+          -0.8410186767578125,
+          -0.1719101369380951,
+          -0.8747624158859253,
+          -0.0341646634042263,
+          -0.2277235984802246,
+          -0.02509489096701145,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -0.33178603649139404,
+          -0.4603901207447052,
+          -0.6147925853729248,
+          64.26514434814453,
+          21.469341278076172,
+          -0.31514689326286316,
+          -0.4127694368362427,
+          -0.6559529304504395
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 4D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "data": [
+          -0.19053640961647034,
+          50.77590560913086,
+          -0.695496678352356,
+          -0.8057432770729065,
+          -0.9040110111236572,
+          76.02884674072266,
+          66.33873748779297,
+          -0.8410186767578125,
+          -0.1719101369380951,
+          -0.8747624158859253,
+          -0.0341646634042263,
+          -0.2277235984802246,
+          -0.02509489096701145,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -0.33178603649139404,
+          -0.4603901207447052,
+          -0.6147925853729248,
+          64.26514434814453,
+          21.469341278076172,
+          -0.31514689326286316,
+          -0.4127694368362427,
+          -0.6559529304504395
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 5D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
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+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 3, 4],
+        "data": [
+          -0.19053640961647034,
+          50.77590560913086,
+          -0.695496678352356,
+          -0.8057432770729065,
+          -0.9040110111236572,
+          76.02884674072266,
+          66.33873748779297,
+          -0.8410186767578125,
+          -0.1719101369380951,
+          -0.8747624158859253,
+          -0.0341646634042263,
+          -0.2277235984802246,
+          -0.02509489096701145,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -0.33178603649139404,
+          -0.4603901207447052,
+          -0.6147925853729248,
+          64.26514434814453,
+          21.469341278076172,
+          -0.31514689326286316,
+          -0.4127694368362427,
+          -0.6559529304504395
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 1D tensor negative options.alpha",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "alpha": -97.70109193608776
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          1861.5615234375,
+          50.77590560913086,
+          6795.07861328125,
+          7872.19970703125,
+          8832.2861328125,
+          76.02884674072266,
+          66.33873748779297,
+          8216.8447265625,
+          1679.580810546875,
+          8546.5244140625,
+          333.7925109863281,
+          2224.884521484375,
+          245.17982482910156,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          3241.5859375,
+          4498.06201171875,
+          6006.5908203125,
+          64.26514434814453,
+          21.469341278076172,
+          3079.019775390625,
+          4032.802490234375,
+          6408.73193359375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 2D tensor positive options.alpha",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "alpha": 35.799162942273234
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          -682.1043701171875,
+          50.77590560913086,
+          -2489.81982421875,
+          -2884.493408203125,
+          -3236.28369140625,
+          76.02884674072266,
+          66.33873748779297,
+          -3010.776611328125,
+          -615.4238891601562,
+          -3131.576416015625,
+          -122.306640625,
+          -815.2314453125,
+          -89.83760833740234,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          -1187.7662353515625,
+          -1648.158203125,
+          -2200.906005859375,
+          64.26514434814453,
+          21.469341278076172,
+          -1128.1995849609375,
+          -1477.6800537109375,
+          -2348.256591796875
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "leakyRelu float32 5D tensor options.alpha=0.0", // relu
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
+            -19.053641157857015,
+            50.77590443347373,
+            -69.54966768567536,
+            -80.57432185346957,
+            -90.40109641580112,
+            76.02884674163622,
+            66.33873525494391,
+            -84.10186452043264,
+            -17.19101282693427,
+            -87.47624329964907,
+            -3.4164664941905585,
+            -22.7723589638245,
+            -2.509489125727569,
+            18.933284857582677,
+            98.61402761165104,
+            55.33923216295767,
+            -33.178605382176,
+            -46.03901297809681,
+            -61.47925538549912,
+            64.26514742116822,
+            21.46934200700099,
+            -31.51468946013378,
+            -41.27694294131783,
+            -65.59528852425132
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "alpha": 0.0
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 3, 4],
+        "data": [
+          0,
+          50.77590560913086,
+          0,
+          0,
+          0,
+          76.02884674072266,
+          66.33873748779297,
+          0,
+          0,
+          0,
+          0,
+          0,
+          0,
+          18.933284759521484,
+          98.61402893066406,
+          55.3392333984375,
+          0,
+          0,
+          0,
+          64.26514434814453,
+          21.469341278076172,
+          0,
+          0,
+          0
+        ],
+        "type": "float32"
+      },
+      "type": "float32"
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/linear.json b/testing/web-platform/tests/webnn/resources/test_data/linear.json
new file mode 100644
index 0000000000..ded1d2d7e3
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/linear.json
@@ -0,0 +1,751 @@
+{ // linear: Calculate a linear function y = alpha * x + beta on the input tensor.
+  "tests": [
+    {
+      "name": "linear float32 1D tensor default options", // default options: {alpha: 1, beta: 0}
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            -1.1225161816883542,
+            -6.605223195131225,
+            -1.9555539248683687,
+            -4.598548331438281,
+            4.234208072658522,
+            3.097542121236385,
+            3.7465923873418348,
+            -4.487029772637743,
+            6.407402114982858,
+            -4.354544013606705,
+            -5.8190925441357955,
+            3.7214346452179328,
+            -6.330114110872294,
+            8.580595073862398,
+            -6.764922344398516,
+            6.433565829855674,
+            -9.708685944356201,
+            2.6431380232113746,
+            5.214088864824586,
+            9.658617012096975,
+            -8.72174939837989,
+            -0.4533396492565025,
+            9.992619953447026,
+            -6.469674921617137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          -1.12251615524292,
+          -6.605223178863525,
+          -1.9555538892745972,
+          -4.598548412322998,
+          4.234208106994629,
+          3.0975420475006104,
+          3.7465922832489014,
+          -4.487029552459717,
+          6.407402038574219,
+          -4.354544162750244,
+          -5.819092750549316,
+          3.7214345932006836,
+          -6.330113887786865,
+          8.580595016479492,
+          -6.764922142028809,
+          6.433565616607666,
+          -9.708685874938965,
+          2.6431379318237305,
+          5.2140889167785645,
+          9.65861701965332,
+          -8.721749305725098,
+          -0.4533396363258362,
+          9.992619514465332,
+          -6.469675064086914
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "linear float32 2D tensor default options",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            -1.1225161816883542,
+            -6.605223195131225,
+            -1.9555539248683687,
+            -4.598548331438281,
+            4.234208072658522,
+            3.097542121236385,
+            3.7465923873418348,
+            -4.487029772637743,
+            6.407402114982858,
+            -4.354544013606705,
+            -5.8190925441357955,
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+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/log.json b/testing/web-platform/tests/webnn/resources/test_data/log.json
new file mode 100644
index 0000000000..c48406e707
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/log.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
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+      "inputs": {
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+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/matmul.json b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
new file mode 100644
index 0000000000..6e0423a68d
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
@@ -0,0 +1,1289 @@
+{
+  "tests": [
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diff --git a/testing/web-platform/tests/webnn/resources/test_data/max.json b/testing/web-platform/tests/webnn/resources/test_data/max.json
new file mode 100644
index 0000000000..27a258248f
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/max.json
@@ -0,0 +1,784 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json b/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json
new file mode 100644
index 0000000000..cf426620e5
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/max_pool2d.json
@@ -0,0 +1,1368 @@
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/min.json b/testing/web-platform/tests/webnn/resources/test_data/min.json
new file mode 100644
index 0000000000..f5ea4779f4
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/min.json
@@ -0,0 +1,784 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/mul.json b/testing/web-platform/tests/webnn/resources/test_data/mul.json
new file mode 100644
index 0000000000..e6487cfc59
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/mul.json
@@ -0,0 +1,784 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/neg.json b/testing/web-platform/tests/webnn/resources/test_data/neg.json
new file mode 100644
index 0000000000..8a1eea34f9
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/neg.json
@@ -0,0 +1,334 @@
+{
+  "tests": [
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/pad.json b/testing/web-platform/tests/webnn/resources/test_data/pad.json
new file mode 100644
index 0000000000..ac4834d7f0
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/pad.json
@@ -0,0 +1,757 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/pow.json b/testing/web-platform/tests/webnn/resources/test_data/pow.json
new file mode 100644
index 0000000000..d6c9f592df
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/pow.json
@@ -0,0 +1,1072 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/prelu.json b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
new file mode 100644
index 0000000000..e45e12cd4b
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
@@ -0,0 +1,868 @@
+{
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+          "type": "float32"
+        },
+        "slope": {
+          "shape": [2, 3], // broadcast [2, 3] --> [2, 2, 2, 3]
+          "data": [
+            4.8742760041637645,
+            -8.50163357869285,
+            1.1819270477816914,
+            -9.985190366937573,
+            -4.424202960837338,
+            -6.654683521499036
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "ouput",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          -12.425349235534668,
+          40.764122009277344,
+          8.413617134094238,
+          6.108623504638672,
+          37.571624755859375,
+          3.3143365383148193,
+          1.1687211990356445,
+          1.2052156925201416,
+          -7.936229228973389,
+          5.787421703338623,
+          16.615657806396484,
+          32.5965461730957,
+          7.3295159339904785,
+          33.61741256713867,
+          7.067296981811523,
+          9.439736366271973,
+          11.31790828704834,
+          57.621803283691406,
+          8.47507381439209,
+          4.551425457000732,
+          -10.953948020935059,
+          2.617891550064087,
+          1.3258955478668213,
+          49.366512298583984
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "prelu float32 broadcast 4D x 3D slope",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -2.5491681672317235,
+            -4.794857500523286,
+            8.413617520687886,
+            6.108623511441287,
+            -8.492292847462334,
+            3.3143364551069876,
+            1.1687212422078108,
+            -0.1417628422981423,
+            -6.714651930677875,
+            5.787421746282195,
+            -3.7556274239369847,
+            -4.898286418001732,
+            7.329515995865023,
+            -3.9542297833176665,
+            7.067297201348715,
+            9.439736453375971,
+            -2.5581801134299775,
+            -8.658834185932482,
+            8.475073893236225,
+            4.551425642121982,
+            -9.267870491380243,
+            -0.26217744010265776,
+            1.325895534951659,
+            -7.418311114031475
+          ],
+          "type": "float32"
+        },
+        "slope": {
+          "shape": [1, 1, 3], // broadcast [1, 1, 3] --> [2, 2, 2, 3]
+          "data": [
+            5.073923296191488,
+            0.48077445494619653,
+            -7.091750168010829
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "ouput",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          -12.934283256530762,
+          -2.3052449226379395,
+          8.413617134094238,
+          6.108623504638672,
+          -4.082877159118652,
+          3.3143365383148193,
+          1.1687211990356445,
+          -0.06815595179796219,
+          47.61863327026367,
+          5.787421703338623,
+          -1.8056097030639648,
+          34.737422943115234,
+          7.3295159339904785,
+          -1.901092767715454,
+          7.067296981811523,
+          9.439736366271973,
+          -1.2299076318740845,
+          61.40629196166992,
+          8.47507381439209,
+          4.551425457000732,
+          65.72542572021484,
+          -1.330268144607544,
+          1.3258955478668213,
+          52.60881042480469
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "prelu float32 broadcast 4D x 4D slope",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -2.5491681672317235,
+            -4.794857500523286,
+            8.413617520687886,
+            6.108623511441287,
+            -8.492292847462334,
+            3.3143364551069876,
+            1.1687212422078108,
+            -0.1417628422981423,
+            -6.714651930677875,
+            5.787421746282195,
+            -3.7556274239369847,
+            -4.898286418001732,
+            7.329515995865023,
+            -3.9542297833176665,
+            7.067297201348715,
+            9.439736453375971,
+            -2.5581801134299775,
+            -8.658834185932482,
+            8.475073893236225,
+            4.551425642121982,
+            -9.267870491380243,
+            -0.26217744010265776,
+            1.325895534951659,
+            -7.418311114031475
+          ],
+          "type": "float32"
+        },
+        "slope": {
+          "shape": [1, 1, 1, 1], // broadcast [1, 1, 1, 1] --> [2, 2, 2, 3]
+          "data": [
+            5.0114545056636395
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "ouput",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          -12.775040626525879,
+          -24.029211044311523,
+          8.413617134094238,
+          6.108623504638672,
+          -42.558738708496094,
+          3.3143365383148193,
+          1.1687211990356445,
+          -0.7104380130767822,
+          -33.65017318725586,
+          5.787421703338623,
+          -18.821155548095703,
+          -24.54753875732422,
+          7.3295159339904785,
+          -19.816442489624023,
+          7.067296981811523,
+          9.439736366271973,
+          -12.82020378112793,
+          -43.39335632324219,
+          8.47507381439209,
+          4.551425457000732,
+          -46.44551467895508,
+          -1.3138903379440308,
+          1.3258955478668213,
+          -37.17652893066406
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
new file mode 100644
index 0000000000..aa169299c7
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
@@ -0,0 +1,702 @@
+{
+  "tests": [
+    {
+      "name": "reduceL1 float32 1D tensor all positive default options", // default options: {axes: null, keepDimensions: false}
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -98.83928567774318,
+            -57.66743928106195,
+            -57.101201850012814,
+            -6.693042101576822,
+            -45.305847421047595,
+            -86.68338950685379,
+            -74.71875033016443,
+            -76.46740234611214,
+            -75.37676973458242,
+            -18.22093937407911,
+            -54.64426752595342,
+            -36.45240031615904,
+            -18.322682023656796,
+            -47.94379514838312,
+            -40.1997828250384,
+            -15.830483512310494,
+            -48.88335705253115,
+            -41.60024225085446,
+            -20.65563368305152,
+            -92.29933856234294,
+            -46.288581883419646,
+            -80.57185804741187,
+            -25.494730168492268,
+            -48.96730121051369
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1215.228515625,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            18,
+            29,
+            35,
+            36,
+            4,
+            76,
+            41,
+            18,
+            53,
+            29,
+            25,
+            94,
+            26,
+            1,
+            3,
+            68,
+            39,
+            25,
+            87,
+            30,
+            39,
+            75,
+            76,
+            66
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 993,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -92,
+            -52,
+            -88,
+            -78,
+            -20,
+            -73,
+            -42,
+            -57,
+            -39,
+            -75,
+            -17,
+            -36,
+            -81,
+            -24,
+            -88,
+            -91,
+            -76,
+            -5,
+            -44,
+            -66,
+            -96,
+            -8,
+            -69,
+            -27
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1344,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          142.01541137695312,
+          106.62430572509766,
+          175.39280700683594,
+          286.7269592285156,
+          169.36322021484375,
+          212.59750366210938
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          258.57110595703125,
+          174.42807006835938,
+          102.19830322265625,
+          134.52191162109375,
+          207.92910766601562,
+          215.07168579101562
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          1092.72021484375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 1092.72021484375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          1092.72021484375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          108.43173217773438,
+          315.6007995605469,
+          359.5506591796875,
+          309.13702392578125
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL1 float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            5.508826448139126,
+            50.61575563515446,
+            1.6773050539454992,
+            84.21352292914005,
+            15.664374631289203,
+            52.89714899357876,
+            9.12515782683123,
+            28.93762412170997,
+            12.567061064158146,
+            11.399989904078245,
+            86.91246376729916,
+            64.51329469980782,
+            71.28342153263038,
+            76.34410635436484,
+            41.53409150301335,
+            97.56533284219819,
+            31.803831597266385,
+            6.0897547388209405,
+            61.70843555684953,
+            69.76119433406723,
+            38.91940474525253,
+            52.28833355637117,
+            22.31783714884341,
+            99.0719229634137
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          108.43173217773438,
+          315.6007995605469,
+          359.5506591796875,
+          309.13702392578125
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
new file mode 100644
index 0000000000..73397cbb7a
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
@@ -0,0 +1,702 @@
+{
+  "tests": [
+    {
+      "name": "reduceL2 float32 1D tensor all positive default options", // default options: {axes: null, keepDimensions: false}
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -66.80042739154972,
+            -53.00005108985402,
+            -59.58587770117833,
+            -46.14393008028177,
+            -49.60613922872308,
+            -12.832738832929593,
+            -88.05061277508285,
+            -75.56246522621561,
+            -50.767774970060664,
+            -36.96630141451547,
+            -26.34404432713906,
+            -58.905464928590476,
+            -94.28752832403735,
+            -22.780279721601616,
+            -84.34877530084705,
+            -60.477345782692815,
+            -41.45580712299912,
+            -92.84781353832356,
+            -85.0544854150549,
+            -30.23526041853337,
+            -47.33807956591096,
+            -25.26842900087003,
+            -78.1195878278582,
+            -28.3309437256642
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 292.57574462890625,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            4,
+            29,
+            8,
+            56,
+            42,
+            78,
+            89,
+            64,
+            56,
+            81,
+            85,
+            18,
+            6,
+            39,
+            35,
+            63,
+            87,
+            50,
+            81,
+            89,
+            5,
+            8,
+            37,
+            37
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 274.4029846191406,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -70,
+            -78,
+            -65,
+            -77,
+            -25,
+            -47,
+            -63,
+            -67,
+            -66,
+            -15,
+            -28,
+            -75,
+            -88,
+            -54,
+            -13,
+            -27,
+            -5,
+            -18,
+            -68,
+            -71,
+            -50,
+            -56,
+            -99,
+            -99
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 300.3830871582031,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
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+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
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+            6.855991445231058,
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+            41.888577644260664,
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+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          122.352783203125,
+          124.8213119506836,
+          128.20062255859375,
+          128.14801025390625,
+          87.18083953857422,
+          55.043975830078125
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          114.44775390625,
+          110.26422882080078,
+          133.47344970703125,
+          64.96752166748047,
+          128.0914764404297,
+          101.677734375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
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+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
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+            43.65894603418228,
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+            33.504704671527506
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+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
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+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          272.0996398925781
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
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+            41.888577644260664,
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+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 272.0996398925781,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          272.0996398925781
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          138.580078125,
+          166.67791748046875,
+          149.91552734375,
+          67.6578598022461
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceL2 float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            4.860227954324237,
+            88.23184532015614,
+            54.489688892595865,
+            64.75027573238448,
+            6.855991445231058,
+            91.3987084155092,
+            41.888577644260664,
+            73.65445188651776,
+            35.31573479319383,
+            48.345430062443896,
+            82.3919051922353,
+            77.86200561022456,
+            93.31141688733462,
+            62.486883544675194,
+            60.292898644959706,
+            13.23059966965019,
+            20.535988317971942,
+            53.451616950541414,
+            11.32008585820996,
+            64.75763553379184,
+            43.65894603418228,
+            0.8374307376408652,
+            0.6848266407317727,
+            33.504704671527506
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          138.580078125,
+          166.67791748046875,
+          149.91552734375,
+          67.6578598022461
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json
new file mode 100644
index 0000000000..2e1fee804f
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum.json
@@ -0,0 +1,622 @@
+{
+  "tests": [
+    {
+      "name": "reduceLogSum float32 1D tensor all non-negative default options", // default options: {axes: null, keepDimensions: false}
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 1D tensor all non-negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            63,
+            82,
+            49,
+            23,
+            98,
+            67,
+            15,
+            9,
+            89,
+            7,
+            69,
+            61,
+            47,
+            50,
+            41,
+            39,
+            58,
+            52,
+            35,
+            83,
+            81,
+            7,
+            34,
+            9
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.063048362731934,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
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+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
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+            43.791352286892106,
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+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          5.593751907348633,
+          4.773046016693115,
+          5.3115739822387695,
+          5.2497639656066895,
+          4.973392486572266,
+          5.373587131500244
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
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+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          5.410027980804443,
+          5.367736339569092,
+          5.399682998657227,
+          4.652334213256836,
+          4.744638442993164,
+          5.565346717834473
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
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+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
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+            64.91234005889837,
+            71.54029915166349,
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+            43.791352286892106,
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+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          7.039101600646973
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+          "type": "float32"
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+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 7.039101600646973,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
+            50.394988743199434,
+            14.578406888832252,
+            20.86681803845336,
+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
+            0.8337112078307563,
+            69.23145833259072,
+            3.8541642374881446,
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+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          7.039101600646973
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            97.87423374006126,
+            26.529027351852186,
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+            32.43873432263156,
+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
+            43.791352286892106,
+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
+            8.568099335705881,
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+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          5.7273993492126465,
+          5.64375114440918,
+          5.453810214996338,
+          5.758983135223389
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSum float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            64.54826901463852,
+            97.87423374006126,
+            26.529027351852186,
+            79.79046651888517,
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+            64.91234005889837,
+            71.54029915166349,
+            11.13706890220647,
+            55.07930697185586,
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+            13.831947671728972,
+            97.39019470916091,
+            35.50775651228035,
+            52.275862097336166,
+            82.838655037009,
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+            69.23145833259072,
+            3.8541642374881446,
+            70.55673656397397,
+            71.99264788951747
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          5.7273993492126465,
+          5.64375114440918,
+          5.453810214996338,
+          5.758983135223389
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json
new file mode 100644
index 0000000000..00c55ded51
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_log_sum_exp.json
@@ -0,0 +1,702 @@
+{
+  "tests": [
+    {
+      "name": "reduceLogSumExp float32 1D tensor all positive default options", // default options: {axes: null, keepDimensions: false}
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            66.1870735698,
+            68.69164623929768,
+            15.529598361334717,
+            65.62419160755422,
+            86.18090584091544,
+            7.382064010955736,
+            1.6365860724411263,
+            90.55726458445135,
+            86.69934561770543,
+            75.7165191675748,
+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
+            73.63322249161153,
+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -38.42346567796924,
+            -16.384904409140333,
+            -46.629634356968474,
+            -45.81843819006337,
+            -95.61458783306942,
+            -90.64578309257007,
+            -6.279945972307587,
+            -24.546370226192565,
+            -82.15882762280646,
+            -76.8746037170462,
+            -44.181029848800904,
+            -97.35032678020788,
+            -75.52388056554437,
+            -97.984203822517,
+            -97.46591756173142,
+            -85.89237745468532,
+            -27.34196668605746,
+            -76.80293743058324,
+            -93.91905595799426,
+            -25.62251637659385,
+            -36.49762778486478,
+            -96.2163796024006,
+            -33.56049055386055,
+            -94.06451375473459
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -6.279904842376709,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            34,
+            45,
+            5,
+            45,
+            97,
+            11,
+            83,
+            84,
+            17,
+            17,
+            11,
+            20,
+            59,
+            97,
+            44,
+            90,
+            80,
+            59,
+            86,
+            91,
+            33,
+            84,
+            27,
+            27
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 97.69485473632812,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -91,
+            -77,
+            -2,
+            -34,
+            -77,
+            -38,
+            -92,
+            -45,
+            -54,
+            -11,
+            -64,
+            -76,
+            -53,
+            -19,
+            -41,
+            -83,
+            -21,
+            -34,
+            -73,
+            -33,
+            -10,
+            -71,
+            -82,
+            -26
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -1.999541163444519,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            66.1870735698,
+            68.69164623929768,
+            15.529598361334717,
+            65.62419160755422,
+            86.18090584091544,
+            7.382064010955736,
+            1.6365860724411263,
+            90.55726458445135,
+            86.69934561770543,
+            75.7165191675748,
+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
+            73.63322249161153,
+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            66.1870735698,
+            68.69164623929768,
+            15.529598361334717,
+            65.62419160755422,
+            86.18090584091544,
+            7.382064010955736,
+            1.6365860724411263,
+            90.55726458445135,
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+            75.7165191675748,
+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
+            73.63322249161153,
+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            68.69164623929768,
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+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
+            73.63322249161153,
+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            66.1870735698,
+            68.69164623929768,
+            15.529598361334717,
+            65.62419160755422,
+            86.18090584091544,
+            7.382064010955736,
+            1.6365860724411263,
+            90.55726458445135,
+            86.69934561770543,
+            75.7165191675748,
+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
+            73.63322249161153,
+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            68.69164623929768,
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+            75.7165191675748,
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+            25.779723516449636,
+            60.15386290165083,
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+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          68.81230926513672,
+          90.56975555419922,
+          86.6993637084961,
+          81.53412628173828,
+          64.85645294189453,
+          82.32090759277344
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            66.1870735698,
+            68.69164623929768,
+            15.529598361334717,
+            65.62419160755422,
+            86.18090584091544,
+            7.382064010955736,
+            1.6365860724411263,
+            90.55726458445135,
+            86.69934561770543,
+            75.7165191675748,
+            67.0074429215978,
+            9.943717120210827,
+            25.779723516449636,
+            60.15386290165083,
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+            81.53375339603328,
+            64.85643136289283,
+            54.04977784193004,
+            33.380943217138224,
+            32.50357565109678,
+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
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+          86.180908203125,
+          73.63322448730469,
+          75.71652221679688,
+          90.55726623535156,
+          86.7118148803711
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+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            68.69164623929768,
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+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
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+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          90.59076690673828
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 90.59076690673828,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
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+          "data": [
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+            33.380943217138224,
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+            61.30902295453489,
+            56.95015629977242,
+            35.37182024244998,
+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          90.59076690673828
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            82.32090594141081
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          90.57815551757812,
+          86.18093872070312,
+          73.63323211669922,
+          82.69600677490234
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceLogSumExp float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+          "type": "float32"
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+      },
+      "options": {
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+      "expected": {
+        "name": "output",
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+          86.18093872070312,
+          73.63323211669922,
+          82.69600677490234
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
new file mode 100644
index 0000000000..4dd7098d03
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
@@ -0,0 +1,582 @@
+{
+  "tests": [
+    {
+      "name": "reduceMax float32 1D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
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+          "type": "float32"
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+      "expected": {
+        "name": "output",
+        "data": 99.77313232421875,
+        "type": "float32"
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+    },
+    {
+      "name": "reduceMax float32 2D tensor default options",
+      "inputs": {
+        "input": {
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+    {
+      "name": "reduceMax float32 3D tensor default options",
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+    {
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+      "inputs": {
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+      "expected": {
+        "name": "output",
+        "data": 99.77313232421875,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
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+      "expected": {
+        "name": "output",
+        "data": 99.77313232421875,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            32.166585683408215,
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+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
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+          20.253753662109375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            32.166585683408215,
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+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
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+        "data": [
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+          37.28493118286133
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+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            -51.287275192229046,
+            -42.588327517032454
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+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 99.77313232421875,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          99.77313232421875
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            -46.03200926418318,
+            20.253753500247612,
+            -21.55738542170144,
+            -51.287275192229046,
+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 99.77313232421875,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            90.42288038051404,
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+            20.253753500247612,
+            -21.55738542170144,
+            -51.287275192229046,
+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          99.77313232421875
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            -46.03200926418318,
+            20.253753500247612,
+            -21.55738542170144,
+            -51.287275192229046,
+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          90.42288208007812,
+          94.99645233154297,
+          96.55397033691406,
+          99.77313232421875
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMax float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            32.166585683408215,
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+            99.77313292829271,
+            -72.86485546227293,
+            -46.03200926418318,
+            20.253753500247612,
+            -21.55738542170144,
+            -51.287275192229046,
+            -42.588327517032454
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          90.42288208007812,
+          94.99645233154297,
+          96.55397033691406,
+          99.77313232421875
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
new file mode 100644
index 0000000000..db20b17a83
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
@@ -0,0 +1,694 @@
+{
+  "tests": [
+    {
+      "name": "reduceMean float32 1D tensor all positive default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
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+            13.784331379836544,
+            20.006068194857885,
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+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
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+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -37.14687069315612,
+            -44.50042209159177,
+            -6.126548413219496,
+            -6.321792976064302,
+            -76.5389783512652,
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+            -20.763563935321017,
+            -38.74917461116718,
+            -36.81039848179957,
+            -26.274377028592966,
+            -12.56681966278282,
+            -55.28200785289164,
+            -20.697565065775606,
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+            -45.36002983401583,
+            -34.996193368480235,
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+            -0.7434244205683882,
+            -21.981258134364538,
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+            -58.59896180690518,
+            -76.02979877636918,
+            -23.917405754606236,
+            -22.941872716763513
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -34.74319839477539,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            42,
+            24,
+            44,
+            38,
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+            18,
+            3,
+            77,
+            60,
+            19,
+            66,
+            8,
+            21,
+            19,
+            62,
+            71
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 48.41666793823242,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -73,
+            -8,
+            -55,
+            -73,
+            -61,
+            -54,
+            -5,
+            -39,
+            -66,
+            -53,
+            -57,
+            -39,
+            -62,
+            -98,
+            -36,
+            -1,
+            -75,
+            -8,
+            -71,
+            -72,
+            -67,
+            -16,
+            -21,
+            -31
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -47.54166793823242,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "shape": [2, 3],
+        "data": [
+          45.46687316894531,
+          49.670711517333984,
+          50.94768142700195,
+          44.734745025634766,
+          27.777833938598633,
+          23.264999389648438
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "shape": [2, 3],
+        "data": [
+          54.82453536987305,
+          40.251548767089844,
+          22.060470581054688,
+          48.58541488647461,
+          51.343353271484375,
+          24.797523498535156
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "shape": [1, 1, 1],
+        "data": [
+          40.31047439575195
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "data": 40.31047439575195,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "shape": [1, 1, 1, 1],
+        "data": [
+          40.31047439575195
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "shape": [2, 2],
+        "data": [
+          52.287559509277344,
+          45.10261917114258,
+          47.640018463134766,
+          16.211700439453125
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMean float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            95.84498772347054,
+            75.69370054099012,
+            1.5417720846181426,
+            8.787033906673592,
+            70.08280339173061,
+            13.784331379836544,
+            20.006068194857885,
+            94.80963809344851,
+            25.829190184293417,
+            94.13260521032214,
+            67.72958187044576,
+            16.099351117563778,
+            92.19433555001908,
+            11.567352371276595,
+            52.705496151946285,
+            22.471793133903972,
+            3.6623324286590764,
+            20.2102781903039,
+            58.56523137489753,
+            28.673493080608758,
+            42.134198143189195,
+            21.637750690378144,
+            14.160698325191756,
+            15.127351396412191
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "shape": [1, 2, 2, 1],
+        "data": [
+          52.287559509277344,
+          45.10261917114258,
+          47.640018463134766,
+          16.211700439453125
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
new file mode 100644
index 0000000000..db6c0e2269
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
@@ -0,0 +1,582 @@
+{
+  "tests": [
+    {
+      "name": "reduceMin float32 1D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -58.76195671214997,
+            -87.962299829198,
+            -70.13690195964651,
+            -53.61766646981643,
+            -39.50931280469092,
+            76.48815138549966,
+            -18.705087479309455,
+            44.78261924634546,
+            30.70233967738929,
+            61.463613873181146,
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+            99.01705821629525,
+            73.39929943432298,
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+            -84.40769111096932,
+            75.88834177123843,
+            96.02651672898816,
+            -55.976554418350545,
+            -1.791101785391234
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -87.9623031616211,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMin float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            -58.76195671214997,
+            -87.962299829198,
+            -70.13690195964651,
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+            30.70233967738929,
+            61.463613873181146,
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+            -53.747413472322414,
+            -31.713543832764827,
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+            77.93652481771113,
+            99.01705821629525,
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+            75.88834177123843,
+            96.02651672898816,
+            -55.976554418350545,
+            -1.791101785391234
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -87.9623031616211,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMin float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            -58.76195671214997,
+            -87.962299829198,
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+            99.01705821629525,
+            73.39929943432298,
+            92.08459468237234,
+            -59.40851905900759,
+            -84.40769111096932,
+            75.88834177123843,
+            96.02651672898816,
+            -55.976554418350545,
+            -1.791101785391234
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -87.9623031616211,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceMin float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -58.76195671214997,
+            -87.962299829198,
+            -70.13690195964651,
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
new file mode 100644
index 0000000000..60484300bc
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
@@ -0,0 +1,582 @@
+{
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+      "name": "reduceProduct float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
+            -22.69974404385384,
+            79.97555172142995,
+            14.46502415218545,
+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
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+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          4227263.5,
+          -446960.5625,
+          3811296.75,
+          1280298.5,
+          -1343475.375,
+          1280118.75
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
+            -22.69974404385384,
+            79.97555172142995,
+            14.46502415218545,
+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
+            26.780734701055266,
+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 1.5855958784642327e+37,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
+            -22.69974404385384,
+            79.97555172142995,
+            14.46502415218545,
+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
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+            -97.97651593223856,
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+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          1.5855958784642327e+37
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
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+            -44.23515424391753,
+            -22.69974404385384,
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+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
+            26.780734701055266,
+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 1.5855958784642327e+37,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
+            -22.69974404385384,
+            79.97555172142995,
+            14.46502415218545,
+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
+            26.780734701055266,
+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          1.5855958784642327e+37
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
+            -22.69974404385384,
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+            14.46502415218545,
+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
+            -20.15709647137976,
+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
+            26.780734701055266,
+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          -3638925568,
+          6523364352,
+          -414643360,
+          1610916352
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceProduct float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            -68.75911760233478,
+            99.4496130391401,
+            24.860555622046746,
+            -44.23515424391753,
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+            49.231095225588376,
+            30.058706923717068,
+            69.45106401985521,
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+            -58.02551401530734,
+            51.89660954258355,
+            -2.020799112914105,
+            39.392973241316554,
+            26.780734701055266,
+            -97.97651593223856,
+            48.66154478867011,
+            -85.19523905815305,
+            -18.169861657911653,
+            64.83759066937682,
+            -14.958838503675935,
+            -74.50931980014732,
+            -11.319679210869765
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          -3638925568,
+          6523364352,
+          -414643360,
+          1610916352
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
new file mode 100644
index 0000000000..6da78ae804
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
@@ -0,0 +1,694 @@
+{
+  "tests": [
+    {
+      "name": "reduceSum float32 1D tensor all positive default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
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+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
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+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
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+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -51.77016701194195,
+            -34.46467785404002,
+            -40.983506494422414,
+            -83.34922667410298,
+            -67.67525749941849,
+            -18.703119061215574,
+            -20.281060841405974,
+            -20.123054810748656,
+            -83.63451764199297,
+            -23.651085471445683,
+            -10.20843911447325,
+            -36.212902987180804,
+            -76.26201536868358,
+            -9.094745329540757,
+            -53.88933855716023,
+            -67.52341028201596,
+            -71.14580362299527,
+            -82.04484921713924,
+            -96.29924980334548,
+            -68.46700365583722,
+            -26.107193300700942,
+            -68.01821308673175,
+            -4.833076925370335,
+            -48.90069809349882
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -1163.642578125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            56,
+            90,
+            67,
+            33,
+            20,
+            58,
+            22,
+            15,
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+            95,
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+            11,
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+            50,
+            57,
+            77,
+            89,
+            10,
+            2
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1307,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -55,
+            -36,
+            -74,
+            -17,
+            -67,
+            -95,
+            -3,
+            -67,
+            -95,
+            -13,
+            -45,
+            -9,
+            -33,
+            -98,
+            -86,
+            -11,
+            -70,
+            -44,
+            -31,
+            -68,
+            -79,
+            -24,
+            -60,
+            -36
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": -1216,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
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+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            99.1748548274599,
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+            60.17613590317996
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
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+            42.856416416096344,
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+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+            99.1748548274599,
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+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "shape": [2, 3],
+        "data": [
+          210.44241333007812,
+          104.54179382324219,
+          226.2177734375,
+          239.025390625,
+          260.405029296875,
+          273.2470397949219
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "shape": [2, 3],
+        "data": [
+          179.63900756835938,
+          260.37457275390625,
+          219.3611297607422,
+          246.83712768554688,
+          157.4895782470703,
+          250.1780242919922
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "shape": [1, 1, 1],
+        "data": [
+          1313.87939453125
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "data": 1313.87939453125,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "shape": [1, 1, 1, 1],
+        "data": [
+          1313.87939453125
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "shape": [2, 2],
+        "data": [
+          355.21942138671875,
+          185.98255920410156,
+          362.3598937988281,
+          410.3175354003906
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSum float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            69.6038605453285,
+            99.1748548274599,
+            32.782341359545676,
+            8.881362932730319,
+            16.094296257493014,
+            11.806894918510213,
+            32.64223805640243,
+            43.998363476438975,
+            77.01777099153088,
+            79.79425759062173,
+            45.007949804090174,
+            24.39779644056914,
+            57.50268541631618,
+            57.60172895173401,
+            80.26985885745457,
+            43.65110628848945,
+            87.50368667545843,
+            94.50203768533922,
+            35.54289690580114,
+            42.856416416096344,
+            88.58631651618441,
+            98.85772999308332,
+            25.62685451963782,
+            60.17613590317996
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "shape": [1, 2, 2, 1],
+        "data": [
+          355.21942138671875,
+          185.98255920410156,
+          362.3598937988281,
+          410.3175354003906
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json
new file mode 100644
index 0000000000..cf6bbb65d4
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum_square.json
@@ -0,0 +1,702 @@
+{
+  "tests": [
+    {
+      "name": "reduceSumSquare float32 1D tensor all positive default options", // default options: {axes: null, keepDimensions: false}
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 1D tensor all negative default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -21.452013864072896,
+            -57.30725907408611,
+            -72.83901116638569,
+            -0.059761520988928396,
+            -71.73678939977705,
+            -44.61909261218302,
+            -43.120022676836946,
+            -91.33738230600645,
+            -33.172438449832086,
+            -48.55593151678299,
+            -95.62864137865712,
+            -20.876631045259614,
+            -16.69083735987158,
+            -39.52110386011864,
+            -7.51078560359592,
+            -90.59026921164444,
+            -42.21683259824742,
+            -76.74274815005997,
+            -98.2242026863753,
+            -60.27295167122231,
+            -74.7320278737084,
+            -8.543684369072977,
+            -59.88873484887647,
+            -17.99894136421551
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 80052.015625,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 1D tensor all positive integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            52,
+            48,
+            2,
+            66,
+            30,
+            39,
+            14,
+            23,
+            81,
+            94,
+            78,
+            64,
+            38,
+            16,
+            63,
+            11,
+            46,
+            95,
+            17,
+            47,
+            40,
+            53,
+            87,
+            43
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 71347,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 1D tensor all negative integers default options", // test with float32 values which are equivalent to integers
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -10,
+            -60,
+            -69,
+            -88,
+            -35,
+            -84,
+            -74,
+            -42,
+            -93,
+            -26,
+            -40,
+            -55,
+            -92,
+            -26,
+            -39,
+            -30,
+            -61,
+            -16,
+            -16,
+            -36,
+            -9,
+            -89,
+            -45,
+            -29
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73634,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 2D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 6],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 3D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 5D tensor default options",
+      "inputs": {
+        "input": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 3D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          9709.013671875,
+          10817.7685546875,
+          14548.470703125,
+          16385.8515625,
+          9287.357421875,
+          12527.3974609375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor options.axes",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [0, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3],
+        "data": [
+          8585.87109375,
+          7700.654296875,
+          19889.1796875,
+          7113.0439453125,
+          16775.708984375,
+          13211.3994140625
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 3D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 3D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
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+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1],
+        "data": [
+          73275.859375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
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+            13.493006439137023,
+            44.15238362662202,
+            86.53118079678906,
+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": false
+      },
+      "expected": {
+        "name": "output",
+        "data": 73275.859375,
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
+            19.177289239472593,
+            13.493006439137023,
+            44.15238362662202,
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+            70.20919468463771,
+            25.67262870756528,
+            79.73770192548034,
+            66.42284577584445,
+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "keepDimensions": true
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 1, 1, 1],
+        "data": [
+          73275.859375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor options.axes with options.keepDimensions=false",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
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+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2],
+        "data": [
+          12302.474609375,
+          22772.77734375,
+          26919.09765625,
+          11281.5068359375
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reduceSumSquare float32 4D tensor options.axes with options.keepDimensions=true",
+      "inputs": {
+        "input": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            52.5615351837915,
+            2.6261063680439234,
+            82.04877759500097,
+            14.401411284784604,
+            33.96051675758925,
+            83.93837980977771,
+            47.44504659398938,
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+            13.493006439137023,
+            44.15238362662202,
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+            70.20919468463771,
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+            70.40363336301188,
+            13.503327808732468,
+            41.22539754662389,
+            6.654552839238637,
+            85.79743668166222,
+            89.91348950671976,
+            53.55647451130674,
+            39.48537158474081,
+            3.9460408540454184
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "axes": [1, 3]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 2, 1],
+        "data": [
+          12302.474609375,
+          22772.77734375,
+          26919.09765625,
+          11281.5068359375
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/relu.json b/testing/web-platform/tests/webnn/resources/test_data/relu.json
new file mode 100644
index 0000000000..b459789147
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/relu.json
@@ -0,0 +1,334 @@
+{
+  "tests": [ // relu input tensor of 1D to 5D with same data values
+    {
+      "name": "relu float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            79.04725231657116,
+            2.2503608756501166,
+            80.73939090529203,
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+            -71.09157819044825,
+            -82.74703468427575,
+            -26.814426600801028,
+            -99.16788836397058,
+            -35.71083406288831,
+            18.36165830990626,
+            -37.36091648205435,
+            -52.8386119809162,
+            -10.408374773008958,
+            60.60291560236189,
+            -13.644198913810342,
+            -76.54250291031946,
+            -8.132338049258351,
+            51.51447452437017,
+            -51.63370281825297,
+            -64.567999424324,
+            -5.093302411117136,
+            15.354103550744384,
+            90.03858807393516
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "data": [
+          79.04724884033203,
+          2.2503609657287598,
+          80.73938751220703,
+          63.9039192199707,
+          77.67340850830078,
+          0,
+          0,
+          0,
+          0,
+          0,
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+          0,
+          0,
+          0,
+          60.6029167175293,
+          0,
+          0,
+          0,
+          51.51447296142578,
+          0,
+          0,
+          0,
+          15.354103088378906,
+          90.03858947753906
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "relu float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            79.04725231657116,
+            2.2503608756501166,
+            80.73939090529203,
+            63.90392076789547,
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+            -5.093302411117136,
+            15.354103550744384,
+            90.03858807393516
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+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
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+          0,
+          0,
+          15.354103088378906,
+          90.03858947753906
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "relu float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            79.04725231657116,
+            2.2503608756501166,
+            80.73939090529203,
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+            -99.16788836397058,
+            -35.71083406288831,
+            18.36165830990626,
+            -37.36091648205435,
+            -52.8386119809162,
+            -10.408374773008958,
+            60.60291560236189,
+            -13.644198913810342,
+            -76.54250291031946,
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+            -51.63370281825297,
+            -64.567999424324,
+            -5.093302411117136,
+            15.354103550744384,
+            90.03858807393516
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "data": [
+          79.04724884033203,
+          2.2503609657287598,
+          80.73938751220703,
+          63.9039192199707,
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+          0,
+          0,
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+          0,
+          0,
+          0,
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+          0,
+          0,
+          0,
+          51.51447296142578,
+          0,
+          0,
+          0,
+          15.354103088378906,
+          90.03858947753906
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "relu float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 2, 2, 3],
+          "data": [
+            79.04725231657116,
+            2.2503608756501166,
+            80.73939090529203,
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+            15.354103550744384,
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+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 2, 2, 3],
+        "data": [
+          79.04724884033203,
+          2.2503609657287598,
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+          0,
+          0,
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+          0,
+          0,
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+          0,
+          0,
+          0,
+          15.354103088378906,
+          90.03858947753906
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "relu float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 1, 4, 1, 3],
+          "data": [
+            79.04725231657116,
+            2.2503608756501166,
+            80.73939090529203,
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+            -82.74703468427575,
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+            -99.16788836397058,
+            -35.71083406288831,
+            18.36165830990626,
+            -37.36091648205435,
+            -52.8386119809162,
+            -10.408374773008958,
+            60.60291560236189,
+            -13.644198913810342,
+            -76.54250291031946,
+            -8.132338049258351,
+            51.51447452437017,
+            -51.63370281825297,
+            -64.567999424324,
+            -5.093302411117136,
+            15.354103550744384,
+            90.03858807393516
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 1, 4, 1, 3],
+        "data": [
+          79.04724884033203,
+          2.2503609657287598,
+          80.73938751220703,
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+          60.6029167175293,
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+          0,
+          15.354103088378906,
+          90.03858947753906
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/reshape.json b/testing/web-platform/tests/webnn/resources/test_data/reshape.json
new file mode 100644
index 0000000000..7d48ed3a18
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/reshape.json
@@ -0,0 +1,406 @@
+{
+  "tests": [
+    {
+      "name": "reshape float32 tensor to a new shape (reorder all dimensions)",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
+            -30.056147250771076,
+            99.5694232746736,
+            88.04620115823073,
+            -91.87507576772606,
+            -23.797235323955633,
+            -91.28665022600151,
+            -63.15204449663816,
+            12.066952464893262,
+            -96.1172904235943,
+            -44.77365489782947,
+            -80.08650883940432,
+            -64.4375694650447,
+            27.641954235862485,
+            -96.86306613475395,
+            83.68347403572196,
+            50.599484132010815,
+            -20.187656772788642,
+            -1.3904608012750117,
+            -96.9360325497362,
+            65.34144119048645,
+            34.835993949837274,
+            62.01485845563673,
+            -2.8698414892852355,
+            27.903749097190158
+          ],
+          "type": "float32"
+        }
+      },
+      "newShape": [4, 2, 3],
+      "expected": {
+        "name": "output",
+        "shape": [4, 2, 3],
+        "data": [
+          -30.0561466217041,
+          99.56941986083984,
+          88.04620361328125,
+          -91.87507629394531,
+          -23.7972354888916,
+          -91.28665161132812,
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+          12.0669527053833,
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+          -44.77365493774414,
+          -80.08650970458984,
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+          27.64195442199707,
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+          62.01485824584961,
+          -2.8698415756225586,
+          27.903749465942383
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "reshape float32 tensor to a new shape (reduce dimensions)",
+      "inputs": {
+        "input": {
+          "shape": [4, 1, 1, 1, 6],
+          "data": [
+            -30.056147250771076,
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+          "type": "float32"
+        }
+      },
+      "newShape": [4, 1, 1, 6],
+      "expected": {
+        "name": "output",
+        "shape": [4, 1, 1, 6],
+        "data": [
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/sigmoid.json b/testing/web-platform/tests/webnn/resources/test_data/sigmoid.json
new file mode 100644
index 0000000000..c233336321
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/sigmoid.json
@@ -0,0 +1,334 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/sin.json b/testing/web-platform/tests/webnn/resources/test_data/sin.json
new file mode 100644
index 0000000000..3cc4771a33
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/sin.json
@@ -0,0 +1,334 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/slice.json b/testing/web-platform/tests/webnn/resources/test_data/slice.json
new file mode 100644
index 0000000000..ed193dd656
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/slice.json
@@ -0,0 +1,254 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/softmax.json b/testing/web-platform/tests/webnn/resources/test_data/softmax.json
new file mode 100644
index 0000000000..52ea57c763
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/softmax.json
@@ -0,0 +1,136 @@
+{
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+            -6.235629579015209
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "data": [
+          0.2546302080154419,
+          0.24781952798366547,
+          0.2307596504688263,
+          0.008623254485428333,
+          0.002599793951958418,
+          0.2555675804615021,
+          0.40352678298950195,
+          0.13637976348400116,
+          0.0009232329903170466,
+          0.20185552537441254,
+          0.23287305235862732,
+          0.024441635236144066,
+          0.0551743283867836,
+          0.3008708655834198,
+          0.0002474947541486472,
+          0.6276082992553711,
+          0.0050902292132377625,
+          0.011008745059370995,
+          0.9090295433998108,
+          0.0388500951230526,
+          0.00041779119055718184,
+          0.039206232875585556,
+          0.0012629841221496463,
+          0.011233373545110226
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/softsign.json b/testing/web-platform/tests/webnn/resources/test_data/softsign.json
new file mode 100644
index 0000000000..e3208b18ad
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/softsign.json
@@ -0,0 +1,400 @@
+{ // softsign: The calculation follows the expression x / (1 + |x|).
+  "tests": [
+    {
+      "name": "softsign positive float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            1.5834133593790956,
+            4.0787189411490115,
+            8.883356617490337,
+            8.070860233252166,
+            8.211773633019915,
+            2.4554003891197818,
+            0.653374178120758,
+            7.866281154604682,
+            3.1239552336192666,
+            8.013792390668268,
+            3.9409862749371283,
+            1.8131727337833081,
+            2.390676102273188,
+            1.3359680092645565,
+            9.416410839467265,
+            0.44325690899325254,
+            5.236662013213598,
+            9.424242359034539,
+            7.816190418459348,
+            5.849185795081855,
+            8.780370640491928,
+            5.1205157788312246,
+            7.1172223514005095,
+            4.59910661262345
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "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
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softsign negative float32 1D tensor",
+      "inputs": {
+        "x": {
+          "shape": [24],
+          "data": [
+            -2.5978440095516913,
+            -0.4449555447737712,
+            -9.095475232407683,
+            -3.7480076975512873,
+            -1.3867289790255697,
+            -8.220328902868987,
+            -3.538342320320556,
+            -9.364588742025619,
+            -6.283252341501335,
+            -5.0020120266550006,
+            -8.245729151019969,
+            -3.775470497728266,
+            -4.087254829132392,
+            -7.3816760861585795,
+            -5.882921529710956,
+            -8.338910337100263,
+            -6.6015492897072185,
+            -4.491942000901396,
+            -3.524778486355298,
+            -4.439912258765581,
+            -5.2342625634221225,
+            -1.5911732471016933,
+            -9.106277545690418,
+            -8.523774275382141
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [24],
+        "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
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softsign float32 2D tensor",
+      "inputs": {
+        "x": {
+          "shape": [4, 6],
+          "data": [
+            -8.343496173533422,
+            -6.92015211612679,
+            2.699638761922575,
+            -8.663104577031863,
+            -3.190534368785616,
+            7.657887080586452,
+            6.650215091182602,
+            6.058011004380681,
+            0.6634320403254037,
+            5.805803683155526,
+            -0.32821124531446344,
+            1.270430403469046,
+            -9.946119978610852,
+            6.905375202832072,
+            -0.031071535439890496,
+            -3.9696409293645862,
+            6.270823207970878,
+            -2.6392608577007914,
+            3.051350503137261,
+            7.42647683445869,
+            -8.454667518154086,
+            7.135868292466057,
+            -4.9860941550065885,
+            -7.859615086397076
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [4, 6],
+        "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
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softsign float32 3D tensor",
+      "inputs": {
+        "x": {
+          "shape": [2, 3, 4],
+          "data": [
+            -8.343496173533422,
+            -6.92015211612679,
+            2.699638761922575,
+            -8.663104577031863,
+            -3.190534368785616,
+            7.657887080586452,
+            6.650215091182602,
+            6.058011004380681,
+            0.6634320403254037,
+            5.805803683155526,
+            -0.32821124531446344,
+            1.270430403469046,
+            -9.946119978610852,
+            6.905375202832072,
+            -0.031071535439890496,
+            -3.9696409293645862,
+            6.270823207970878,
+            -2.6392608577007914,
+            3.051350503137261,
+            7.42647683445869,
+            -8.454667518154086,
+            7.135868292466057,
+            -4.9860941550065885,
+            -7.859615086397076
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 4],
+        "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
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softsign float32 4D tensor",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 3, 4],
+          "data": [
+            -8.343496173533422,
+            -6.92015211612679,
+            2.699638761922575,
+            -8.663104577031863,
+            -3.190534368785616,
+            7.657887080586452,
+            6.650215091182602,
+            6.058011004380681,
+            0.6634320403254037,
+            5.805803683155526,
+            -0.32821124531446344,
+            1.270430403469046,
+            -9.946119978610852,
+            6.905375202832072,
+            -0.031071535439890496,
+            -3.9696409293645862,
+            6.270823207970878,
+            -2.6392608577007914,
+            3.051350503137261,
+            7.42647683445869,
+            -8.454667518154086,
+            7.135868292466057,
+            -4.9860941550065885,
+            -7.859615086397076
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 3, 4],
+        "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
+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "softsign float32 5D tensor",
+      "inputs": {
+        "x": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
+            -8.343496173533422,
+            -6.92015211612679,
+            2.699638761922575,
+            -8.663104577031863,
+            -3.190534368785616,
+            7.657887080586452,
+            6.650215091182602,
+            6.058011004380681,
+            0.6634320403254037,
+            5.805803683155526,
+            -0.32821124531446344,
+            1.270430403469046,
+            -9.946119978610852,
+            6.905375202832072,
+            -0.031071535439890496,
+            -3.9696409293645862,
+            6.270823207970878,
+            -2.6392608577007914,
+            3.051350503137261,
+            7.42647683445869,
+            -8.454667518154086,
+            7.135868292466057,
+            -4.9860941550065885,
+            -7.859615086397076
+          ],
+          "type": "float32"
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [1, 2, 1, 3, 4],
+        "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
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/split.json b/testing/web-platform/tests/webnn/resources/test_data/split.json
new file mode 100644
index 0000000000..e4216003c0
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/split.json
@@ -0,0 +1,660 @@
+{
+  "tests": [
+    {
+      "name": "split float32 1D tensor number splits default options",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
+            -64.52057192772567,
+            -84.60513454654502,
+            -67.9928282139549,
+            -23.446074622313745,
+            -85.64383132426956,
+            46.877522730892906,
+            -68.11224159891194,
+            75.99607609082298,
+            -61.05668616435924,
+            -90.92643605408041,
+            53.916621140775476,
+            84.16269171442175,
+            -95.57494716023527,
+            -52.40757884637803,
+            -29.007187148127983,
+            71.65495730084652,
+            50.663572707062656,
+            21.364581604631596,
+            -27.127241457105228,
+            65.1489516233315,
+            -30.406812651567833,
+            -6.818390152438795,
+            46.67362179020569,
+            -21.12453802903387
+          ],
+          "type": "float32"
+        }
+      },
+      "splits": 3,
+      "expected": [
+        {
+          "name": "output1",
+          "shape": [8],
+          "data": [
+            -64.52056884765625,
+            -84.60513305664062,
+            -67.99282836914062,
+            -23.446075439453125,
+            -85.64382934570312,
+            46.87752151489258,
+            -68.11224365234375,
+            75.99607849121094
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "output2",
+          "shape": [8],
+          "data": [
+            -61.05668640136719,
+            -90.92643737792969,
+            53.916622161865234,
+            84.16268920898438,
+            -95.57494354248047,
+            -52.40757751464844,
+            -29.007186889648438,
+            71.65496063232422
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "output3",
+          "shape": [8],
+          "data": [
+            50.66357421875,
+            21.364582061767578,
+            -27.127241134643555,
+            65.1489486694336,
+            -30.40681266784668,
+            -6.818390369415283,
+            46.673622131347656,
+            -21.12453842163086
+          ],
+          "type": "float32"
+        }
+      ]
+    },
+    {
+      "name": "split float32 2D tensor number splits default options",
+      "inputs": {
+        "input": {
+          "shape": [8, 3],
+          "data": [
+            -64.52057192772567,
+            -84.60513454654502,
+            -67.9928282139549,
+            -23.446074622313745,
+            -85.64383132426956,
+            46.877522730892906,
+            -68.11224159891194,
+            75.99607609082298,
+            -61.05668616435924,
+            -90.92643605408041,
+            53.916621140775476,
+            84.16269171442175,
+            -95.57494716023527,
+            -52.40757884637803,
+            -29.007187148127983,
+            71.65495730084652,
+            50.663572707062656,
+            21.364581604631596,
+            -27.127241457105228,
+            65.1489516233315,
+            -30.406812651567833,
+            -6.818390152438795,
+            46.67362179020569,
+            -21.12453802903387
+          ],
+          "type": "float32"
+        }
+      },
+      "splits": 2,
+      "expected": [
+        {
+          "name": "output1",
+          "shape": [4, 3],
+          "data": [
+            -64.52056884765625,
+            -84.60513305664062,
+            -67.99282836914062,
+            -23.446075439453125,
+            -85.64382934570312,
+            46.87752151489258,
+            -68.11224365234375,
+            75.99607849121094,
+            -61.05668640136719,
+            -90.92643737792969,
+            53.916622161865234,
+            84.16268920898438
+          ],
+          "type": "float32"
+        },
+        {
+          "name": "output2",
+          "shape": [4, 3],
+          "data": [
+            -95.57494354248047,
+            -52.40757751464844,
+            -29.007186889648438,
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+            50.66357421875,
+            21.364582061767578,
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+            -6.818390369415283,
+            46.673622131347656,
+            -21.12453842163086
+          ],
+          "type": "float32"
+        }
+      ]
+    },
+    {
+      "name": "split float32 3D tensor number splits default options",
+      "inputs": {
+        "input": {
+          "shape": [4, 3, 2],
+          "data": [
+            -64.52057192772567,
+            -84.60513454654502,
+            -67.9928282139549,
+            -23.446074622313745,
+            -85.64383132426956,
+            46.877522730892906,
+            -68.11224159891194,
+            75.99607609082298,
+            -61.05668616435924,
+            -90.92643605408041,
+            53.916621140775476,
+            84.16269171442175,
+            -95.57494716023527,
+            -52.40757884637803,
+            -29.007187148127983,
+            71.65495730084652,
+            50.663572707062656,
+            21.364581604631596,
+            -27.127241457105228,
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+            -30.406812651567833,
+            -6.818390152438795,
+            46.67362179020569,
+            -21.12453802903387
+          ],
+          "type": "float32"
+        }
+      },
+      "splits": 2,
+      "expected": [
+        {
+          "name": "output1",
+          "shape": [2, 3, 2],
+          "data": [
+            -64.52056884765625,
+            -84.60513305664062,
+            -67.99282836914062,
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+            -85.64382934570312,
+            46.87752151489258,
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/squeeze.json b/testing/web-platform/tests/webnn/resources/test_data/squeeze.json
new file mode 100644
index 0000000000..88890fe870
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/squeeze.json
@@ -0,0 +1,696 @@
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/sub.json b/testing/web-platform/tests/webnn/resources/test_data/sub.json
new file mode 100644
index 0000000000..4a3096313e
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/sub.json
@@ -0,0 +1,784 @@
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/tan.json b/testing/web-platform/tests/webnn/resources/test_data/tan.json
new file mode 100644
index 0000000000..857e2b6505
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/tan.json
@@ -0,0 +1,334 @@
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\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/tanh.json b/testing/web-platform/tests/webnn/resources/test_data/tanh.json
new file mode 100644
index 0000000000..9e13b62472
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/tanh.json
@@ -0,0 +1,334 @@
+{
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+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/test_data/transpose.json b/testing/web-platform/tests/webnn/resources/test_data/transpose.json
new file mode 100644
index 0000000000..03092031d9
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/test_data/transpose.json
@@ -0,0 +1,679 @@
+{
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+      "inputs": {
+        "input": {
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+    },
+    {
+      "name": "transpose float32 3D tensor default options",
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+      "name": "transpose float32 4D tensor default options",
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+    },
+    {
+      "name": "transpose float32 5D tensor default options",
+      "inputs": {
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "transpose float32 1D tensor options.permutation",
+      "inputs": {
+        "input": {
+          "shape": [24],
+          "data": [
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+        "shape": [24],
+        "data": [
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+      }
+    },
+    {
+      "name": "transpose float32 2D tensor options.permutation",
+      "inputs": {
+        "input": {
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+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "permutation": [1, 0]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [6, 4],
+        "data": [
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+        ],
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+      }
+    },
+    {
+      "name": "transpose float32 3D tensor options.permutation",
+      "inputs": {
+        "input": {
+          "shape": [2, 3, 4],
+          "data": [
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+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "permutation": [2, 0, 1]
+      },
+      "expected": {
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+        "shape": [4, 2, 3],
+        "data": [
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+        ],
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+      }
+    },
+    {
+      "name": "transpose float32 4D tensor options.permutation",
+      "inputs": {
+        "input": {
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+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "permutation": [2, 3, 0, 1]
+      },
+      "expected": {
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+        "shape": [3, 4, 1, 2],
+        "data": [
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+        ],
+        "type": "float32"
+      }
+    },
+    {
+      "name": "transpose float32 5D tensor options.permutation",
+      "inputs": {
+        "input": {
+          "shape": [1, 2, 1, 3, 4],
+          "data": [
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+            2.1999381880991393
+          ],
+          "type": "float32"
+        }
+      },
+      "options": {
+        "permutation": [1, 3, 0, 4, 2]
+      },
+      "expected": {
+        "name": "output",
+        "shape": [2, 3, 1, 4, 1],
+        "data": [
+          -45.67443084716797,
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+          38.466827392578125,
+          2.1999382972717285
+        ],
+        "type": "float32"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/testing/web-platform/tests/webnn/resources/utils.js b/testing/web-platform/tests/webnn/resources/utils.js
new file mode 100644
index 0000000000..37748fd57a
--- /dev/null
+++ b/testing/web-platform/tests/webnn/resources/utils.js
@@ -0,0 +1,664 @@
+'use strict';
+
+const ExecutionArray = ['sync', 'async'];
+
+// https://webmachinelearning.github.io/webnn/#enumdef-mloperandtype
+const TypedArrayDict = {
+  float32: Float32Array,
+  int32: Int32Array,
+  uint32: Uint32Array,
+  int8: Int8Array,
+  uint8: Uint8Array,
+};
+
+const sizeOfShape = (array) => {
+  return array.reduce((accumulator, currentValue) => accumulator * currentValue, 1);
+};
+
+/**
+ * Get tests resources from test data JSON file of specified operation name.
+ * @param {String} operationName - An operation name
+ * @returns {Object} Tests resources
+ */
+const loadTests = (operationName) => {
+  const loadJSON = (file) => {
+    let xmlhttp = new XMLHttpRequest();
+    xmlhttp.open("GET", file, false);
+    xmlhttp.overrideMimeType("application/json");
+    xmlhttp.send();
+    if (xmlhttp.status == 200 && xmlhttp.readyState == 4) {
+      return xmlhttp.responseText;
+    } else {
+      throw new Error(`Failed to load ${file}`);
+    }
+  };
+
+  const capitalLetterMatches = operationName.match(/[A-Z]/g);
+  if (capitalLetterMatches !== null) {
+    // for example: the test data JSON file for leakyRelu is leaky_relu.json and for reduceLogSum is reduce_log_sum.json
+    capitalLetterMatches.forEach(
+      capitalLetter => operationName = operationName.replace(capitalLetter, `_${capitalLetter.toLowerCase()}`)
+    )
+  }
+  const json = loadJSON(`/webnn/resources/test_data/${operationName}.json`);
+  const resources = JSON.parse(json.replace(/\\"|"(?:\\"|[^"])*"|(\/\/.*|\/\*[\s\S]*?\*\/)/g, (m, g) => g ? "" : m));
+  return resources.tests;
+};
+
+/**
+ * Get exptected data and data type from given resources with output name.
+ * @param {Array} resources - An array of expected resources
+ * @param {String} outputName - An output name
+ * @returns {Array.<[Number[], String]>} An array of expected data array and data type
+ */
+const getExpectedDataAndType = (resources, outputName) => {
+  let ret;
+  for (let subResources of resources) {
+    if (subResources.name === outputName) {
+      ret = [subResources.data, subResources.type];
+      break;
+    }
+  }
+  if (ret === undefined) {
+    throw new Error(`Failed to get expected data sources and type by ${outputName}`);
+  }
+  return ret;
+};
+
+/**
+ * Get ULP tolerance of conv2d/convTranspose2d operation.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getConv2dPrecisionTolerance = (resources, operationName) => {
+  // number of reduced input elements multiplied by filter and summed (a sliding dot product like pooling)
+  const inputNameArray = Object.keys(resources.inputs);
+  const inputShape = resources.inputs[inputNameArray[0]].shape;
+  const filterShape = resources.inputs[inputNameArray[1]].shape;
+  const options = resources.options;
+  let groups = 1;
+  let inputChannels = inputShape[1]; // default nchw inputLayout
+  // default oihw filterLayout for conv2d or default iohw filterLayout for convTranspose2d
+  let filterWidth = filterShape[3];
+  let filterHeight = filterShape[2];
+  if (options) {
+    if (options.groups) {
+      groups = options.groups;
+    }
+    if (options.inputLayout) {
+      if (!['nchw', 'nhwc'].includes(options.inputLayout)) {
+        throw new Error(`Unsupported inputLayout ${options.inputLayout}`);
+      }
+      inputChannels = options.inputLayout === 'nchw' ? inputChannels : inputShape[3];
+    }
+    if (options.filterLayout) {
+      let filterLayouts = ['oihw', 'hwio', 'ohwi', 'ihwo']; // default for conv2d
+      if (operationName === 'convTranspose2d') {
+        filterLayouts = ['iohw', 'hwoi', 'ohwi'];
+      }
+      if (!filterLayouts.includes(options.filterLayout)) {
+        throw new Error(`Unsupported filterLayout ${options.filterLayout}`);
+      }
+      switch (options.filterLayout) {
+        case 'oihw':
+        case 'iohw':
+          // Just use the existing filterWidth and filterHeight above.
+          break;
+        case 'hwio':
+        case 'hwoi':
+          filterWidth = filterShape[1];
+          filterHeight = filterShape[0];
+          break;
+        case 'ohwi':
+        case 'ihwo':
+          filterWidth = filterShape[2];
+          filterHeight = filterShape[1];
+          break;
+        default:
+          break;
+      }
+    }
+  }
+  const tolerance = filterWidth * filterHeight * (inputChannels / groups) * 2;
+  return tolerance;
+};
+
+/**
+ * Get ULP tolerance of gemm operation.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getGemmPrecisionTolerance = (resources, operationName) => {
+  // GEMM : alpha * (A x B) + beta * C
+  // An upper bound for the worst serial ordering is bounded by
+  // the number of lossy operations, where matrix multiplication
+  // is a dot product (mul and add times the number of elements)
+  // plus bias operations.
+  const shapeA = resources.inputs[Object.keys(resources.inputs)[0]].shape;
+  const options = {...resources.options};
+  const width = options.aTranspose ? shapeA[0] : shapeA[1];
+  let tolerance = width * 2;
+  // default options.alpha is 1.0
+  if (options.alpha !== undefined && options.alpha !== 1.0) {
+    tolerance++;
+  }
+  if (options.c && options.beta !== 0.0) {
+    // default options.beta is 1.0
+    if (options.beta !== undefined && options.beta !== 1.0) {
+      tolerance++;
+    }
+    tolerance++;
+  }
+  return tolerance;
+};
+
+/**
+ * Get ULP tolerance of matmul operation.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getMatmulPrecisionTolerance = (resources, operationName) => {
+  // Matmul : Compute the matrix product of two input tensors.
+  // If a is 1-D, WebNN converts it to a 2-D tensor by prepending a 1 to its dimensions, [n] -> [1, n].
+  // So we can just always check the last dimension here.
+  const shapeA = resources.inputs[Object.keys(resources.inputs)[0]].shape;
+  const tolerance = shapeA[shapeA.length - 1] * 2;
+  return tolerance;
+};
+
+/**
+ * Get ULP tolerance of averagePool2d operation.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getAveragePool2dPrecisionTolerance = (resources, operationName) => {
+  const inputShape = resources.inputs[Object.keys(resources.inputs)[0]].shape;
+  let height;
+  let width;
+  const options = {...resources.options};
+  if (options.windowDimensions) {
+    height = options.windowDimensions[0];
+    width = options.windowDimensions[1];
+  } else {
+    // If not present, the window dimensions are assumed to be the height and width dimensions of the input shape
+    if (options.layout && options.layout === 'nhwc') {
+      height = inputShape[1];
+      width = inputShape[2];
+    } else {
+      // nhwc layout of input
+      height = inputShape[2];
+      width = inputShape[3];
+    }
+  }
+
+  const tolerance = height * width + 2;
+  return tolerance;
+};
+
+/**
+ * Get ULP tolerance of softmax operation.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getSoftmaxPrecisionTolerance = (resources, operationName) => {
+  // Compute the softmax values of the 2-D input tensor along axis 1.
+  const inputShape = resources.inputs[Object.keys(resources.inputs)[0]].shape;
+  const tolerance = inputShape[1] * 3 + 3;
+  return tolerance;
+};
+
+/**
+ * Get ULP tolerance of reduction operations.
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} operationName - An operation name
+ * @returns {Number} A tolerance number
+ */
+const getReductionPrecisionTolerance = (resources, operationName) => {
+  const inputShape = resources.inputs[Object.keys(resources.inputs)[0]].shape;
+  const rank = inputShape.length;
+  const options = {...resources.options};
+  let sizes;
+  if (options && options.axes) {
+    sizes = options.axes.map(
+                (axis) => axis < 0 ? inputShape[axis + rank] : inputShape[axis]
+    );
+  } else {
+    sizes = inputShape;
+  }
+  const reducedElementCount = sizes.reduce(
+                                  (accumulator, currentValue) => accumulator * currentValue
+  );
+  let tolerance;
+  switch (operationName) {
+    case 'reduceL1':
+    case 'reduceProduct':
+    case 'reduceSum':
+      tolerance = reducedElementCount;
+      break;
+    case 'reduceL2':
+      tolerance = reducedElementCount * 2 + 1;
+      break;
+    case 'reduceMean':
+      tolerance = reducedElementCount + 2;
+      break;
+    case 'reduceLogSum':
+      tolerance = reducedElementCount + 18;
+      break;
+    case 'reduceLogSumExp':
+      tolerance = reducedElementCount * 2 + 18;
+      break;
+    case 'reduceSumSquare':
+      tolerance = reducedElementCount * 2;
+      break;
+    default:
+      break;
+  }
+  return tolerance;
+};
+
+// Refer to precision metrics on https://github.com/webmachinelearning/webnn/issues/265#issuecomment-1256242643
+const PrecisionMetrics = {
+  batchNormalization: {ULP: {float32: 6, float16: 6}},
+  clamp: {ULP: {float32: 0, float16: 0}},
+  concat: {ULP: {float32: 0, float16: 0}},
+  conv2d: {ULP: {float32: getConv2dPrecisionTolerance, float16: getConv2dPrecisionTolerance}},
+  convTranspose2d: {ULP: {float32: getConv2dPrecisionTolerance, float16: getConv2dPrecisionTolerance}},
+  // Begin Element-wise binary operations
+  add: {ULP: {float32: 1, float16: 1}},
+  sub: {ULP: {float32: 1, float16: 1}},
+  mul: {ULP: {float32: 1, float16: 1}},
+  div: {ULP: {float32: 2, float16: 2}},
+  max: {ULP: {float32: 0, float16: 0}},
+  min: {ULP: {float32: 0, float16: 0}},
+  pow: {ULP: {float32: 32, float16: 2}},
+  // End Element-wise binary operations
+  // Begin Element-wise unary operations
+  abs: {ULP: {float32: 0, float16: 0}},
+  ceil: {ULP: {float32: 0, float16: 0}},
+  cos: {ATOL: {float32: 1/1024, float16: 1/512}},
+  exp: {ULP: {float32: 32, float16: 1}},
+  floor: {ULP: {float32: 0, float16: 0}},
+  log: {ATOL: {float32: 1/1024, float16:  1/1024}},
+  neg: {ULP: {float32: 0, float16: 0}},
+  sin: {ATOL: {float32: 1/1024, float16: 1/512}},
+  tan: {ATOL: {float32: 1/1024, float16: 1/512}},
+  // End Element-wise unary operations
+  elu: {ULP: {float32: 18, float16: 18}},
+  gemm: {ULP: {float32: getGemmPrecisionTolerance, float16: getGemmPrecisionTolerance}},
+  hardSigmoid: {ULP: {float32: 2, float16: 2}},
+  hardSwish: {ULP: {float32: 4, float16: 4}},
+  leakyRelu: {ULP: {float32: 1, float16: 1}},
+  linear: {ULP: {float32: 2, float16: 2}},
+  matmul: {ULP: {float32: getMatmulPrecisionTolerance, float16: getMatmulPrecisionTolerance}},
+  pad: {ULP: {float32: 0, float16: 0}},
+  // Begin Pooling operations
+  averagePool2d: {ULP: {float32: getAveragePool2dPrecisionTolerance, float16: getAveragePool2dPrecisionTolerance}},
+  maxPool2d: {ULP: {float32: 0, float16: 0}},
+  // End Pooling operations
+  prelu: {ULP: {float32: 1, float16: 1}},
+  // Begin Reduction operations
+  reduceL1: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceL2: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceLogSum: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceLogSumExp: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceMax: {ULP: {float32: 0, float16: 0}},
+  reduceMean: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceMin: {ULP: {float32: 0, float16: 0}},
+  reduceProduct: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceSum: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  reduceSumSquare: {ULP: {float32: getReductionPrecisionTolerance, float16: getReductionPrecisionTolerance}},
+  // End Reduction operations
+  relu: {ULP: {float32: 0, float16: 0}},
+  reshape: {ULP: {float32: 0, float16: 0}},
+  sigmoid: {ULP: {float32: 32+2, float16: 3}}, // float32 (leaving a few ULP for roundoff)
+  slice: {ULP: {float32: 0, float16: 0}},
+  softmax: {ULP: {float32: getSoftmaxPrecisionTolerance, float16: getSoftmaxPrecisionTolerance}},
+  softsign: {ULP: {float32: 3, float16: 3}},
+  split: {ULP: {float32: 0, float16: 0}},
+  squeeze: {ULP: {float32: 0, float16: 0}},
+  tanh: {ATOL: {float32: 1/1024, float16: 1/512}},
+  transpose: {ULP: {float32: 0, float16: 0}},
+};
+
+/**
+ * Get precison tolerance value.
+ * @param {String} operationName - An operation name
+ * @param {String} metricType - Value: 'ULP', 'ATOL'
+ * @param {Object} resources - Resources used for building a graph
+ * @returns {Number} A tolerance number
+ */
+const getPrecisonTolerance = (operationName, metricType, resources) => {
+  // the outputs by split or gru is a sequence
+  const precisionType = Array.isArray(resources.expected) ? resources.expected[0].type : resources.expected.type;
+  let tolerance = PrecisionMetrics[operationName][metricType][precisionType];
+  // If the tolerance is dynamic, then evaluate the function to get the value.
+  if (tolerance instanceof Function) {
+    tolerance = tolerance(resources, operationName);
+  }
+  return tolerance;
+};
+
+/**
+ * Get bitwise of the given value.
+ * @param {Number} value
+ * @param {String} dataType - A data type string, like "float32", "float16",
+ *     more types, please see:
+ *     https://webmachinelearning.github.io/webnn/#enumdef-mloperandtype
+ * @return {Number} A 64-bit signed integer.
+ */
+const getBitwise = (value, dataType) => {
+  const buffer = new ArrayBuffer(8);
+  const int64Array = new BigInt64Array(buffer);
+  int64Array[0] = value < 0 ? ~BigInt(0) : BigInt(0);
+  let typedArray;
+  if (dataType === "float32") {
+    typedArray = new Float32Array(buffer);
+  } else {
+    throw new AssertionError(`Data type ${dataType} is not supported`);
+  }
+  typedArray[0] = value;
+  return int64Array[0];
+};
+
+/**
+ * Assert that each array property in ``actual`` is a number being close enough to the corresponding
+ * property in ``expected`` by the acceptable ULP distance ``nulp`` with given ``dataType`` data type.
+ *
+ * @param {Array} actual - Array of test values.
+ * @param {Array} expected - Array of values expected to be close to the values in ``actual``.
+ * @param {Number} nulp - A BigInt value indicates acceptable ULP distance.
+ * @param {String} dataType - A data type string, value: "float32",
+ *     more types, please see:
+ *     https://webmachinelearning.github.io/webnn/#enumdef-mloperandtype
+ * @param {String} description - Description of the condition being tested.
+ */
+const assert_array_approx_equals_ulp = (actual, expected, nulp, dataType, description) => {
+  /*
+    * Test if two primitive arrays are equal within acceptable ULP distance
+    */
+  assert_true(actual.length === expected.length,
+              `assert_array_approx_equals_ulp: ${description} lengths differ, expected ${expected.length} but got ${actual.length}`);
+  let actualBitwise, expectedBitwise, distance;
+  for (let i = 0; i < actual.length; i++) {
+    if (actual[i] === expected[i]) {
+      continue;
+    } else {
+      // measure the ULP distance
+      actualBitwise = getBitwise(actual[i], dataType);
+      expectedBitwise = getBitwise(expected[i], dataType);
+      distance = actualBitwise - expectedBitwise;
+      distance = distance >= 0 ? distance : -distance;
+      assert_true(distance <= nulp,
+                  `assert_array_approx_equals_ulp: ${description} actual ${actual[i]} should be close enough to expected ${expected[i]} by the acceptable ${nulp} ULP distance, but they have ${distance} ULP distance`);
+    }
+  }
+};
+
+/**
+ * Assert actual results with expected results.
+ * @param {String} operationName - An operation name
+ * @param {(Number[]|Number)} actual
+ * @param {(Number[]|Number)} expected
+ * @param {Number} tolerance
+ * @param {String} operandType  - An operand type string, value: "float32",
+ *     more types, please see:
+ *     https://webmachinelearning.github.io/webnn/#enumdef-mloperandtype
+ * @param {String} metricType - Value: 'ULP', 'ATOL'
+ */
+const doAssert = (operationName, actual, expected, tolerance, operandType, metricType) => {
+  const description = `test ${operationName} ${operandType}`;
+  if (typeof expected === 'number') {
+    // for checking a scalar output by matmul 1D x 1D
+    expected = [expected];
+    actual = [actual];
+  }
+  if (metricType === 'ULP') {
+    assert_array_approx_equals_ulp(actual, expected, tolerance, operandType, description);
+  } else if (metricType === 'ATOL') {
+    assert_array_approx_equals(actual, expected, tolerance, description);
+  }
+};
+
+/**
+ * Check computed results with expected data.
+ * @param {String} operationName - An operation name
+ * @param {Object.<String, MLOperand>} namedOutputOperands
+ * @param {Object.<MLNamedArrayBufferViews>} outputs - The resources of required outputs
+ * @param {Object} resources - Resources used for building a graph
+ */
+const checkResults = (operationName, namedOutputOperands, outputs, resources) => {
+  const metricType = Object.keys(PrecisionMetrics[operationName])[0];
+  const expected = resources.expected;
+  let tolerance;
+  let operandType;
+  let outputData;
+  let expectedData;
+  if (Array.isArray(expected)) {
+    // the outputs of split() or gru() is a sequence
+    for (let operandName in namedOutputOperands) {
+      outputData = outputs[operandName];
+      // for some operations which may have multi outputs of different types
+      [expectedData, operandType] = getExpectedDataAndType(expected, operandName);
+      tolerance = getPrecisonTolerance(operationName, metricType, resources);
+      doAssert(operationName, outputData, expectedData, tolerance, operandType, metricType)
+    }
+  } else {
+    outputData = outputs[expected.name];
+    expectedData = expected.data;
+    operandType = expected.type;
+    tolerance = getPrecisonTolerance(operationName, metricType, resources);
+    doAssert(operationName, outputData, expectedData, tolerance, operandType, metricType)
+  }
+};
+
+/**
+ * Create a constant operand
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for constant operand
+ * @returns {MLOperand} A constant operand
+ */
+const createConstantOperand = (builder, resources) => {
+  const bufferView = new TypedArrayDict[resources.type](resources.data);
+  return builder.constant({type: resources.type, dimensions: resources.shape}, bufferView);
+};
+
+/**
+ * Create single input operands for a graph.
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @param {String} [inputOperandName] - An inputOperand name
+ * @returns {MLOperand} An input operand
+ */
+const createSingleInputOperand = (builder, resources, inputOperandName) => {
+  inputOperandName = inputOperandName ? inputOperandName : Object.keys(resources.inputs)[0];
+  const inputResources = resources.inputs[inputOperandName];
+  return builder.input(inputOperandName, {type: inputResources.type, dimensions: inputResources.shape});
+};
+
+/**
+ * Create multi input operands for a graph.
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @returns {MLOperand[]} Input operands array
+ */
+const createMultiInputOperands = (builder, resources) => {
+  let inputOperands = [];
+  const inputOperandNameArray = Object.keys(resources.inputs);
+  inputOperandNameArray.forEach(inputOperandName => {
+    let operand;
+    if (resources.inputs[inputOperandName].hasOwnProperty('constant') && resources.inputs[inputOperandName]['constant']) {
+      operand = createConstantOperand(builder, resources.inputs[inputOperandName]);
+    } else {
+      operand = createSingleInputOperand(builder, resources, inputOperandName);
+    }
+    inputOperands.push(operand);
+  });
+  return inputOperands;
+};
+
+/**
+ * Build an operation which has a single input.
+ * @param {String} operationName - An operation name
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @returns {MLNamedOperands}
+ */
+const buildOperationWithSingleInput = (operationName, builder, resources) => {
+  const namedOutputOperand = {};
+  const inputOperand = createSingleInputOperand(builder, resources);
+  const outputOperand = resources.options ?
+      builder[operationName](inputOperand, resources.options) : builder[operationName](inputOperand);
+  namedOutputOperand[resources.expected.name] = outputOperand;
+  return namedOutputOperand;
+};
+
+/**
+ * Build an operation which has two inputs.
+ * @param {String} operationName - An operation name
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @returns {MLNamedOperands}
+ */
+const buildOperationWithTwoInputs= (operationName, builder, resources) => {
+  // For example: MLOperand matmul(MLOperand a, MLOperand b);
+  const namedOutputOperand = {};
+  const [inputOperandA, inputOperandB] = createMultiInputOperands(builder, resources);
+  const outputOperand = resources.options ?
+      builder[operationName](inputOperandA, inputOperandB, resources.options) : builder[operationName](inputOperandA, inputOperandB);
+  namedOutputOperand[resources.expected.name] = outputOperand;
+  return namedOutputOperand;
+};
+
+/**
+ * Build a graph.
+ * @param {String} operationName - An operation name
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @param {Function} buildFunc - A build function for an operation
+ * @returns [namedOperands, inputs, outputs]
+ */
+const buildGraph = (operationName, builder, resources, buildFunc) => {
+  const namedOperands = buildFunc(operationName, builder, resources);
+  let inputs = {};
+  if (Array.isArray(resources.inputs)) {
+    // the inputs of concat() is a sequence
+    for (let subInput of resources.inputs) {
+      if (!subInput.hasOwnProperty('constant') || !subInput.constant) {
+        inputs[subInput.name] = new TypedArrayDict[subInput.type](subInput.data);
+      }
+    }
+  } else {
+    for (let inputName in resources.inputs) {
+      const subTestByName = resources.inputs[inputName];
+      if (!subTestByName.hasOwnProperty('constant') || !subTestByName.constant) {
+        inputs[inputName] = new TypedArrayDict[subTestByName.type](subTestByName.data);
+      }
+    }
+  }
+  let outputs = {};
+  if (Array.isArray(resources.expected)) {
+    // the outputs of split() or gru() is a sequence
+    for (let i = 0; i < resources.expected.length; i++) {
+      const subExpected = resources.expected[i];
+      outputs[subExpected.name] = new TypedArrayDict[subExpected.type](sizeOfShape(subExpected.shape));
+    }
+  } else {
+    // matmul 1D with 1D produces a scalar which doesn't have its shape
+    const shape = resources.expected.shape ? resources.expected.shape : [1];
+    outputs[resources.expected.name] = new TypedArrayDict[resources.expected.type](sizeOfShape(shape));
+  }
+  return [namedOperands, inputs, outputs];
+};
+
+/**
+ * Build a graph, synchronously compile graph and execute, then check computed results.
+ * @param {String} operationName - An operation name
+ * @param {MLContext} context - A ML context
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @param {Function} buildFunc - A build function for an operation
+ */
+const runSync = (operationName, context, builder, resources, buildFunc) => {
+  // build a graph
+  const [namedOutputOperands, inputs, outputs] = buildGraph(operationName, builder, resources, buildFunc);
+  // synchronously compile the graph up to the output operand
+  const graph = builder.buildSync(namedOutputOperands);
+  // synchronously execute the compiled graph.
+  context.computeSync(graph, inputs, outputs);
+  checkResults(operationName, namedOutputOperands, outputs, resources);
+};
+
+/**
+ * Build a graph, asynchronously compile graph and execute, then check computed results.
+ * @param {String} operationName - An operation name
+ * @param {MLContext} context - A ML context
+ * @param {MLGraphBuilder} builder - A ML graph builder
+ * @param {Object} resources - Resources used for building a graph
+ * @param {Function} buildFunc - A build function for an operation
+ */
+const run = async (operationName, context, builder, resources, buildFunc) => {
+  // build a graph
+  const [namedOutputOperands, inputs, outputs] = buildGraph(operationName, builder, resources, buildFunc);
+  // asynchronously compile the graph up to the output operand
+  const graph = await builder.build(namedOutputOperands);
+  // asynchronously execute the compiled graph
+  const result = await context.compute(graph, inputs, outputs);
+  checkResults(operationName, namedOutputOperands, result.outputs, resources);
+};
+
+/**
+ * Run WebNN operation tests.
+ * @param {(String[]|String)} operationName - An operation name array or an operation name
+ * @param {Function} buildFunc - A build function for an operation
+ */
+const testWebNNOperation = (operationName, buildFunc) => {
+  let operationNameArray;
+  if (typeof operationName === 'string') {
+    operationNameArray = [operationName];
+  } else if (Array.isArray(operationName)) {
+    operationNameArray = operationName;
+  }
+
+  ExecutionArray.forEach(executionType => {
+    const isSync = executionType === 'sync';
+    if (self.GLOBAL.isWindow() && isSync) {
+      return;
+    }
+    let context;
+    let builder;
+    if (isSync) {
+      // test sync
+      operationNameArray.forEach((subOperationName) => {
+        const tests = loadTests(subOperationName);
+        setup(() => {
+          context = navigator.ml.createContextSync();
+          builder = new MLGraphBuilder(context);
+        });
+        for (const subTest of tests) {
+          test(() => {
+            runSync(subOperationName, context, builder, subTest, buildFunc);
+          }, `${subTest.name} / ${executionType}`);
+        }
+      });
+    } else {
+      // test async
+      operationNameArray.forEach((subOperationName) => {
+        const tests = loadTests(subOperationName);
+        promise_setup(async () => {
+          context = await navigator.ml.createContext();
+          builder = new MLGraphBuilder(context);
+        });
+        for (const subTest of tests) {
+          promise_test(async () => {
+            await run(subOperationName, context, builder, subTest, buildFunc);
+          }, `${subTest.name} / ${executionType}`);
+        }
+      });
+    }
+  });
+};
\ No newline at end of file