Merging upstream version 127.0.

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

16 files changed, 206 insertions, 582 deletions

diff --git a/testing/web-platform/tests/webnn/resources/test_data/arg_max.json b/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
index d2fe9e62ca..348a54dc24 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/arg_max.json
@@ -460,7 +460,7 @@
         }
       },
       "options": {
-        "keepDimensions": true
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
diff --git a/testing/web-platform/tests/webnn/resources/test_data/arg_min.json b/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
index 132a2dc3e8..330afbc710 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/arg_min.json
@@ -460,7 +460,7 @@
         }
       },
       "options": {
-        "keepDimensions": true
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
diff --git a/testing/web-platform/tests/webnn/resources/test_data/matmul.json b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
index f3a03e442e..cc1789ee25 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/matmul.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/matmul.json
@@ -1,332 +1,6 @@
 {
   "tests": [
     {
-      "name": "matmul float32 constant 1D and 1D tensors all positive produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32",
-          "constant": true
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32",
-          "constant": true
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 7458.89013671875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 1D tensors all positive produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 7458.89013671875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 1D tensors all negative produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            -86.60583871803968,
-            -94.74202421330796,
-            -86.16720380573273,
-            -76.0215630990851
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            -21.22328469397374,
-            -56.66441199254357,
-            -77.66753889428908,
-            -56.55797454862353
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": 18198.58203125,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 positive 1D and negative 1D tensors produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            -21.22328469397374,
-            -56.66441199254357,
-            -77.66753889428908,
-            -56.55797454862353
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": -7069.85546875,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 negative 1D and positive 1D tensors produces a scalar",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            -86.60583871803968,
-            -94.74202421330796,
-            -86.16720380573273,
-            -76.0215630990851
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            27.829805134194842,
-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "data": -19578.140625,
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 2D tensors",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
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-          "data": [
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-            78.40126706348094,
-            14.819002753540623,
-            3.692303791736573,
-            45.9064286713635,
-            43.08391896733015,
-            47.19946845924572,
-            60.925216107016425,
-            8.162760351602216,
-            20.33326305093228,
-            20.438397895943282,
-            27.01940859922867,
-            15.601424432184263,
-            87.46969388883927,
-            65.79554455585657,
-            69.31696864490797,
-            31.984439910782992,
-            12.291812891860388,
-            13.304834654547172,
-            85.26705387930089
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 5],
-        "data": [
-          8602.796875,
-          7075.7802734375,
-          3083.654052734375,
-          3881.228271484375,
-          8131.462890625
-        ],
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 1D and 4D tensors",
-      "inputs": {
-        "a": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [2, 2, 4, 2],
-          "data": [
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-            78.61926127874348,
-            2.246814764541316,
-            12.044773359659434,
-            1.8342867333124069,
-            82.09732511549477,
-            43.884761946067094,
-            5.616231825100204,
-            34.67424097413332,
-            49.152710076333506,
-            75.34904358690912,
-            84.74523302920429,
-            36.56497325521975,
-            22.89479672718755,
-            15.02636975800511,
-            66.49530785246675,
-            65.81345056776044,
-            26.749681209347376,
-            19.415639234175774,
-            98.60692665127114,
-            65.39448996549784,
-            56.47023672202065,
-            80.64523905250766,
-            82.20401464839868,
-            70.84606482516416,
-            50.27994995977012,
-            67.39406108056262,
-            75.35806805146241,
-            2.7487208784167327,
-            68.0645872775828,
-            70.73791158057968,
-            46.26436742398676
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [2, 2, 1, 2],
-        "data": [
-          5293.36376953125,
-          7255.7626953125,
-          5224.80322265625,
-          7556.21142578125,
-          8926.5361328125,
-          8476.359375,
-          7713.62158203125,
-          8234.0224609375
-        ],
-        "type": "float32"
-      }
-    },
-    {
-      "name": "matmul float32 2D and 1D tensors",
-      "inputs": {
-        "a": {
-          "shape": [5, 4],
-          "data": [
-            88.17004408170853,
-            43.08391896733015,
-            20.438397895943282,
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-            78.40126706348094,
-            47.19946845924572,
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-            31.984439910782992,
-            14.819002753540623,
-            60.925216107016425,
-            15.601424432184263,
-            12.291812891860388,
-            3.692303791736573,
-            8.162760351602216,
-            87.46969388883927,
-            13.304834654547172,
-            45.9064286713635,
-            20.33326305093228,
-            65.79554455585657,
-            85.26705387930089
-          ],
-          "type": "float32"
-        },
-        "b": {
-          "shape": [4],
-          "data": [
-            50.10142534731317,
-            22.2193058046253,
-            34.65448469299386,
-            36.35148095671881
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [5, 1],
-        "data": [
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-          7075.7802734375,
-          3083.654052734375,
-          3881.228271484375,
-          8131.462890625
-        ],
-        "type": "float32"
-      }
-    },
-    {
       "name": "matmul float32 2D and 2D tensors",
       "inputs": {
         "a": {
@@ -750,64 +424,6 @@
       }
     },
     {
-      "name": "matmul float32 3D and 1D tensors",
-      "inputs": {
-        "a": {
-          "shape": [2, 3, 4],
-          "data": [
-            56.46701250066562,
-            99.86045478237251,
-            71.05493372292567,
-            32.45438455331333,
-            17.310747999630017,
-            2.586275053048559,
-            92.31499166302054,
-            96.9758519231732,
-            26.4721315276526,
-            77.67031776320978,
-            29.278788710989147,
-            82.12142428847062,
-            89.89308471484885,
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-            64.36866008901963,
-            23.75928513568486,
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-            57.45134849716054,
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-            85.0296980735713,
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-            83.14548502311283,
-            34.4128942110155,
-            83.20379675185079
-          ],
-          "type": "float32"
-        }
-      },
-      "expected": {
-        "name": "output",
-        "shape": [2, 3, 1],
-        "data": [
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-          11942.376953125,
-          15035.0322265625,
-          13553.013671875,
-          12302.328125,
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-        ],
-        "type": "float32"
-      }
-    },
-    {
       "name": "matmul float32 4D and 4D (broadcast) tensors",
       "inputs": {
         "a": {
diff --git a/testing/web-platform/tests/webnn/resources/test_data/prelu.json b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
index cf79bee7a9..14a7c412dd 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/prelu.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/prelu.json
@@ -1,6 +1,34 @@
 {
   "tests": [
     {
+      "name": "prelu float32 0D scalar",
+      "inputs": {
+        "x": {
+          "shape": [],
+          "data": [
+            -4.794857500523286
+          ],
+          "type": "float32"
+        },
+        "slope": {
+          "shape": [],
+          "data": [
+            1.1202747481570352
+          ],
+          "type": "float32",
+          "constant": true
+        }
+      },
+      "expected": {
+        "name": "output",
+        "shape": [],
+        "data": [
+          -5.371557712554932
+        ],
+        "type": "float32"
+      }
+    },
+    {
       "name": "prelu float32 1D constant tensors",
       "inputs": {
         "x": {
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
index 7cbc442511..c3f2b618e9 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l1.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           108.43173217773438,
           315.6007995605469,
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
index 7e59a45d5e..d83eea9dfb 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_l2.json
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           138.580078125,
           166.67791748046875,
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
index 250398d227..061e12ad51 100644
--- 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
@@ -596,7 +596,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -645,11 +646,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           5.7273993492126465,
           5.64375114440918,
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
index b7f39abd52..3577d6aa9e 100644
--- 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
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           8.563796997070312,
           5.500619411468506,
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
index 967aea8bf4..11ed0ed919 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_max.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           90.42288208007812,
           94.99645233154297,
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
index 5a48952c06..8c26d0a562 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_mean.json
@@ -670,7 +670,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "shape": [2, 2],
@@ -718,10 +719,11 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           52.287559509277344,
           45.10261917114258,
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
index 92de75e92a..6c26df5db1 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_min.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           -87.9623031616211,
           -53.747413635253906,
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
index 691bf4da9b..d58af30ec1 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_product.json
@@ -556,7 +556,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -605,11 +606,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           -3638925568,
           6523364352,
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
index df47a1a2b2..7027d38b67 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/reduce_sum.json
@@ -670,7 +670,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "shape": [2, 2],
@@ -718,10 +719,11 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           355.21942138671875,
           185.98255920410156,
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
index 8ac373e4b3..bd2ebb341a 100644
--- 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
@@ -676,7 +676,8 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": false
       },
       "expected": {
         "name": "output",
@@ -725,11 +726,12 @@
         }
       },
       "options": {
-        "axes": [1, 3]
+        "axes": [1, 3],
+        "keepDimensions": true
       },
       "expected": {
         "name": "output",
-        "shape": [1, 2, 2, 1],
+        "shape": [2, 1, 2, 1],
         "data": [
           12302.474609375,
           22772.77734375,
diff --git a/testing/web-platform/tests/webnn/resources/test_data/softplus.json b/testing/web-platform/tests/webnn/resources/test_data/softplus.json
index eb05b7b281..373612d5ca 100644
--- a/testing/web-platform/tests/webnn/resources/test_data/softplus.json
+++ b/testing/web-platform/tests/webnn/resources/test_data/softplus.json
@@ -1,7 +1,7 @@
-{ // softplus: The calculation follows the expression ln(1 + exp(steepness * x)) / steepness.
+{ // softplus: The calculation follows the expression ln(1 + exp(x)).
   "tests": [
     {
-      "name": "softplus float32 1D constant tensor default options", // default options: {steepness: 1}
+      "name": "softplus float32 1D constant tensor",
       "inputs": {
         "x": {
           "shape": [24],
@@ -68,7 +68,7 @@
      }
     },
     {
-      "name": "softplus float32 1D tensor default options", // default options: {steepness: 1}
+      "name": "softplus float32 1D tensor",
       "inputs": {
         "x": {
           "shape": [24],
@@ -134,7 +134,7 @@
      }
     },
     {
-      "name": "softplus float32 2D tensor default options",
+      "name": "softplus float32 2D tensor",
       "inputs": {
         "x": {
           "shape": [4, 6],
@@ -200,7 +200,7 @@
      }
     },
     {
-      "name": "softplus float32 3D tensor default options",
+      "name": "softplus float32 3D tensor",
       "inputs": {
         "x": {
           "shape": [2, 3, 4],
@@ -266,7 +266,7 @@
      }
     },
     {
-      "name": "softplus float32 4D tensor default options",
+      "name": "softplus float32 4D tensor",
       "inputs": {
         "x": {
           "shape": [1, 2, 3, 4],
@@ -332,7 +332,7 @@
      }
     },
     {
-      "name": "softplus float32 5D tensor default options",
+      "name": "softplus float32 5D tensor",
       "inputs": {
         "x": {
           "shape": [1, 2, 1, 3, 4],
@@ -396,144 +396,6 @@
         ],
         "type": "float32"
      }
-    },
-    {
-      "name": "softplus both positive float32 4D tensor and options.steepness",
-      "inputs": {
-        "x": {
-          "shape": [1, 2, 3, 4],
-          "data": [
-            5.626614582460632,
-            5.167487045486892,
-            4.0146356193402655,
-            9.48003299650489,
-            9.989938045769978,
-            7.0654412821434125,
-            2.132681001794825,
-            8.187151346059956,
-            5.169976220175496,
-            2.1044997879382077,
-            3.523329401138895,
-            4.136340646976668,
-            1.7418719794295656,
-            5.145224066290767,
-            5.015515309165462,
-            0.045903935074711466,
-            2.9570898924917377,
-            3.959244712098706,
-            5.517926978255181,
-            7.192322388417094,
-            8.76492480390928,
-            1.3734704039113388,
-            8.930669016709397,
-            8.660283210871246
-          ],
-          "type": "float32"
-        }
-      },
-      "options": {
-        "steepness": 1.5104469060897827
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 2, 3, 4],
-        "data": [
-          5.626749515533447,
-          5.167757034301758,
-          4.016173362731934,
-          9.480032920837402,
-          9.989937782287598,
-          7.065456390380859,
-          2.158585548400879,
-          8.187153816223145,
-          5.170245170593262,
-          2.1315081119537354,
-          3.526555061340332,
-          4.137620449066162,
-          1.7879058122634888,
-          5.145503044128418,
-          5.015854835510254,
-          0.4822517931461334,
-          2.964651584625244,
-          3.960916519165039,
-          5.518085956573486,
-          7.19233512878418,
-          8.764925956726074,
-          1.4518096446990967,
-          8.930669784545898,
-          8.660284042358398
-        ],
-        "type": "float32"
-     }
-    },
-    {
-      "name": "softplus both negative float32 4D tensor and options.steepness",
-      "inputs": {
-        "x": {
-          "shape": [1, 2, 3, 4],
-          "data": [
-            -5.584833476104802,
-            -8.188738740810354,
-            -8.981280004134987,
-            -1.7315531899284586,
-            -0.7266543578958906,
-            -0.0034800119290885334,
-            -7.378389455552106,
-            -8.907525953796949,
-            -6.0483786568116304,
-            -6.328561142365743,
-            -2.6006513567654626,
-            -5.02005264196455,
-            -2.0647716093484414,
-            -1.5499896740695434,
-            -2.221591675966657,
-            -1.1088025713211636,
-            -2.7854626064634385,
-            -2.105037489961294,
-            -5.144277741727352,
-            -5.081219916574497,
-            -7.499426297617635,
-            -2.4305558382286545,
-            -8.390520024268328,
-            -0.07117499202643174
-          ],
-          "type": "float32"
-        }
-      },
-      "options": {
-        "steepness": -1.2985155767552126
-      },
-      "expected": {
-        "name": "output",
-        "shape": [1, 2, 3, 4],
-        "data": [
-          -5.585379123687744,
-          -8.188756942749023,
-          -8.981287002563477,
-          -1.8088372945785522,
-          -0.9798305630683899,
-          -0.5355416536331177,
-          -7.378442287445068,
-          -8.907533645629883,
-          -6.048677444458008,
-          -6.328769207000732,
-          -2.626511573791504,
-          -5.021188259124756,
-          -2.1157851219177246,
-          -1.6465802192687988,
-          -2.2634570598602295,
-          -1.2725814580917358,
-          -2.805877923965454,
-          -2.1535322666168213,
-          -5.145244121551514,
-          -5.082269191741943,
-          -7.499471664428711,
-          -2.4626762866973877,
-          -8.390534400939941,
-          -0.5702091455459595
-        ],
-        "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
index d1dc0675a7..e5b80ae9f7 100644
--- a/testing/web-platform/tests/webnn/resources/utils.js
+++ b/testing/web-platform/tests/webnn/resources/utils.js
@@ -13,6 +13,15 @@ const TypedArrayDict = {
   int64: BigInt64Array,
 };
 
+const kContextOptionsForVariant = {
+  cpu: {
+    deviceType: 'cpu',
+  },
+  gpu: {
+    deviceType: 'gpu',
+  }
+};
+
 // The maximum index to validate for the output's expected value.
 const kMaximumIndexToValidate = 1000;
 
@@ -867,17 +876,15 @@ const run = async (operationName, context, builder, resources, buildFunc) => {
   checkResults(operationName, namedOutputOperands, result.outputs, resources);
 };
 
+const variant = location.search.substring(1);
+const contextOptions = kContextOptionsForVariant[variant];
+
 /**
  * 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
- * @param {String} deviceType - The execution device type for this test
  */
-const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
-  test(() => assert_not_equals(navigator.ml, undefined, "ml property is defined on navigator"));
-  if (navigator.ml === undefined) {
-    return;
-  }
+const testWebNNOperation = (operationName, buildFunc) => {
   let operationNameArray;
   if (typeof operationName === 'string') {
     operationNameArray = [operationName];
@@ -890,7 +897,14 @@ const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
   operationNameArray.forEach((subOperationName) => {
     const tests = loadTests(subOperationName);
     promise_setup(async () => {
-      context = await navigator.ml.createContext({deviceType});
+      let supported = false;
+      try {
+        context = await navigator.ml.createContext(contextOptions);
+        supported = true;
+      } catch (e) {
+      }
+      assert_implements(
+          supported, `Unable to create context for ${variant} variant`);
       builder = new MLGraphBuilder(context);
     });
     for (const subTest of tests) {
@@ -901,6 +915,65 @@ const testWebNNOperation = (operationName, buildFunc, deviceType = 'cpu') => {
   });
 };
 
+/**
+ * WebNN parallel compute operation test.
+ */
+const testParallelCompute = () => {
+  let ml_context;
+  let ml_graph;
+
+  promise_setup(async () => {
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
+    // Construct a simple graph: A = B * 2.
+    const builder = new MLGraphBuilder(ml_context);
+    const operandType = {dataType: 'float32', dimensions: [1]};
+    const input_operand = builder.input('input', operandType);
+    const const_operand = builder.constant(operandType, Float32Array.from([2]));
+    const output_operand = builder.mul(input_operand, const_operand);
+    ml_graph = await builder.build({'output': output_operand});
+  });
+
+  promise_test(async () => {
+    const test_inputs = [1, 2, 3, 4];
+
+    const actual_outputs = await Promise.all(test_inputs.map(async (input) => {
+      let inputs = {'input': Float32Array.from([input])};
+      let outputs = {'output': new Float32Array(1)};
+      ({inputs, outputs} = await ml_context.compute(ml_graph, inputs, outputs));
+      return outputs.output[0];
+    }));
+
+    const expected_outputs = [2, 4, 6, 8];
+    assert_array_equals(actual_outputs, expected_outputs);
+  });
+};
+
+/**
+ * Run WebNN conformance tests by specified operation.
+ * @param {(String[]|String)} operationName - An operation name array or an
+ *     operation name
+ * @param {Function} buildFunc - A build function for an operation
+ */
+const runWebNNConformanceTests = (operationName, buildFunc) => {
+  // Link to https://github.com/web-platform-tests/wpt/pull/44883
+  // Check navigator.ml is defined before trying to run WebNN tests
+  if (navigator.ml) {
+    testWebNNOperation(operationName, buildFunc);
+  } else {
+    // Show indication to users why the test failed
+    test(
+        () => assert_not_equals(
+            navigator.ml, undefined, 'ml property is defined on navigator'));
+  }
+};
+
 // ref: http://stackoverflow.com/questions/32633585/how-do-you-convert-to-half-floats-in-javascript
 const toHalf = (value) => {
   let floatView = new Float32Array(1);
@@ -970,13 +1043,19 @@ const createBuffer = (context, bufferSize) => {
 /**
  * WebNN destroy buffer twice test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testDestroyWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testDestroyWebNNBuffer = (testName) => {
   let context;
   let buffer;
   promise_setup(async () => {
-    context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
     buffer = createBuffer(context, 4);
   });
   promise_test(async () => {
@@ -993,12 +1072,19 @@ const testDestroyWebNNBuffer = (testName, deviceType = 'cpu') => {
  * WebNN create buffer test.
  * @param {String} testName - The name of the test operation.
  * @param {Number} bufferSize - Size of the buffer to create, in bytes.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testCreateWebNNBuffer = (testName, bufferSize, deviceType = 'cpu') => {
+const testCreateWebNNBuffer = (testName, bufferSize) => {
   let context;
+
   promise_setup(async () => {
-      context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
   promise_test(async () => {
     createBuffer(context, bufferSize);
@@ -1021,12 +1107,18 @@ const assert_buffer_data_equals = async (ml_context, ml_buffer, expected) => {
 /**
  * WebNN write buffer operation test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testWriteWebNNBuffer = (testName) => {
   let ml_context;
   promise_setup(async () => {
-    ml_context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
 
   promise_test(async () => {
@@ -1117,7 +1209,7 @@ const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
       return;
     }
 
-    let another_ml_context = await navigator.ml.createContext({deviceType});
+    let another_ml_context = await navigator.ml.createContext(contextOptions);
     let another_ml_buffer = createBuffer(another_ml_context, ml_buffer.size);
 
     let input_data = new Uint8Array(ml_buffer.size).fill(0xAA);
@@ -1131,12 +1223,18 @@ const testWriteWebNNBuffer = (testName, deviceType = 'cpu') => {
 /**
  * WebNN read buffer operation test.
  * @param {String} testName - The name of the test operation.
- * @param {String} deviceType - The execution device type for this test.
  */
-const testReadWebNNBuffer = (testName, deviceType = 'cpu') => {
+const testReadWebNNBuffer = (testName) => {
   let ml_context;
   promise_setup(async () => {
-    ml_context = await navigator.ml.createContext({deviceType});
+    let supported = false;
+    try {
+      ml_context = await navigator.ml.createContext(contextOptions);
+      supported = true;
+    } catch (e) {
+    }
+    assert_implements(
+        supported, `Unable to create context for ${variant} variant`);
   });
 
   promise_test(async t => {
@@ -1277,7 +1375,7 @@ const testReadWebNNBuffer = (testName, deviceType = 'cpu') => {
       return;
     }
 
-    let another_ml_context = await navigator.ml.createContext({deviceType});
+    let another_ml_context = await navigator.ml.createContext(contextOptions);
     let another_ml_buffer = createBuffer(another_ml_context, ml_buffer.size);
 
     await promise_rejects_js(