webnn: refactor WebNN API conformance tests infrastructure

This CL is to refactor WebNN API conformance tests infrastructure by optimizing utils.js helper and moving tests from JSON files into each test file. It also removes tests of dropped `constant(fillSequence)` op of WebNN API changes [1]. [1] [Remove sequential filling overload of constant()](webmachinelearning/webnn#656) Bug: 331692961 Change-Id: Ie57095d76ed1a87bcbd93dbade8962a1d4461627 Cq-Include-Trybots: luci.chromium.try:win11-blink-rel,mac14-blink-rel,mac14.arm64-blink-rel Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/5668527 Auto-Submit: Feng Dai <feng.dai@intel.com> Commit-Queue: Feng Dai <feng.dai@intel.com> Reviewed-by: ningxin hu <ningxin.hu@intel.com> Reviewed-by: David Baron <dbaron@chromium.org> Reviewed-by: Austin Sullivan <asully@chromium.org> Cr-Commit-Position: refs/heads/main@{#1332944}
web-platform-tests · Jul 25, 2024 · 723e52f · 723e52f
1 parent d5d125a
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diff --git a/webnn/META.yml b/webnn/META.yml
@@ -1,4 +1,4 @@
-spec: https://webmachinelearning.github.io/webnn/
+spec: https://www.w3.org/TR/webnn/
 suggested_reviewers:
   - dontcallmedom
   - Honry
diff --git a/webnn/conformance_tests/abs.https.any.js b/webnn/conformance_tests/abs.https.any.js
@@ -0,0 +1,320 @@
+// META: title=test WebNN API element-wise abs operation
+// META: global=window,dedicatedworker
+// META: variant=?cpu
+// META: variant=?gpu
+// META: variant=?npu
+// META: script=../resources/utils.js
+// META: timeout=long
+
+'use strict';
+
+// https://www.w3.org/TR/webnn/#api-mlgraphbuilder-unary
+// Compute the absolute value of the input tensor, element-wise.
+//
+// MLOperand abs(MLOperand input);
+
+
+const getAbsPrecisionTolerance = (graphResources) => {
+  const toleranceValueDict = {float32: 0, float16: 0};
+  const expectedDataType =
+      getExpectedDataTypeOfSingleOutput(graphResources.expectedOutputs);
+  return {metricType: 'ULP', value: toleranceValueDict[expectedDataType]};
+};
+
+const absTests = [
+  // abs tests
+  {
+    'name': 'abs float32 positive 0D scalar',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [49.837242126464844],
+          'descriptor': {'dimensions': [], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [49.837242126464844],
+          'descriptor': {'dimensions': [], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 negative 0D scalar',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [-91.03521728515625],
+          'descriptor': {'dimensions': [], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [91.03521728515625],
+          'descriptor': {'dimensions': [], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 1D constant tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [24], 'dataType': 'float32'},
+          'constant': true
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [24], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 1D tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [24], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [24], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 2D tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [4, 6], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [4, 6], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 3D tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 3, 4], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 3, 4], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 4D tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 2, 2, 3], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 2, 2, 3], 'dataType': 'float32'}
+        }
+      }
+    }
+  },
+  {
+    'name': 'abs float32 5D tensor',
+    'graph': {
+      'inputs': {
+        'absInput': {
+          'data': [
+            49.837242126464844,  82.09291076660156,  3.1989054679870605,
+            85.20904541015625,   88.94609069824219,  -91.03521728515625,
+            31.4484920501709,    -29.31110954284668, -92.4477310180664,
+            -15.520709991455078, 80.91279602050781,  -38.2097053527832,
+            53.064762115478516,  99.6537094116211,   -21.285049438476562,
+            90.01982879638672,   18.32451820373535,  -33.06915283203125,
+            30.097660064697266,  -74.21503448486328, 95.60974884033203,
+            6.614287376403809,   31.2832088470459,   -53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 1, 4, 1, 3], 'dataType': 'float32'}
+        }
+      },
+      'operators': [{
+        'name': 'abs',
+        'arguments': [{'input': 'absInput'}],
+        'outputs': 'absOutput'
+      }],
+      'expectedOutputs': {
+        'absOutput': {
+          'data': [
+            49.837242126464844, 82.09291076660156, 3.1989054679870605,
+            85.20904541015625,  88.94609069824219, 91.03521728515625,
+            31.4484920501709,   29.31110954284668, 92.4477310180664,
+            15.520709991455078, 80.91279602050781, 38.2097053527832,
+            53.064762115478516, 99.6537094116211,  21.285049438476562,
+            90.01982879638672,  18.32451820373535, 33.06915283203125,
+            30.097660064697266, 74.21503448486328, 95.60974884033203,
+            6.614287376403809,  31.2832088470459,  53.206058502197266
+          ],
+          'descriptor': {'dimensions': [2, 1, 4, 1, 3], 'dataType': 'float32'}
+        }
+      }
+    }
+  }
+];
+
+if (navigator.ml) {
+  absTests.forEach((test) => {
+    webnn_conformance_test(
+        buildGraphAndCompute, getAbsPrecisionTolerance, test);
+  });
+} else {
+  test(() => assert_implements(navigator.ml, 'missing navigator.ml'));
+}