webnn: replace DataError with TypeError

webnn/validation_tests/lstm.https.any.js

@@ -113,23 +113,23 @@ const tests = [
     ]
   },
   {
-    name: '[lstm] DataError is expected if hiddenSize equals to zero',
+    name: '[lstm] TypeError is expected if hiddenSize equals to zero',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
     steps: steps,
     hiddenSize: 0
   },
   {
-    name: '[lstm] DataError is expected if hiddenSize is too large',
+    name: '[lstm] TypeError is expected if hiddenSize is too large',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
     steps: steps,
     hiddenSize: 4294967295,
   },
   {
-    name: '[lstm] DataError is expected if steps equals to zero',
+    name: '[lstm] TypeError is expected if steps equals to zero',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
@@ -138,7 +138,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the data type is not one of the floating point types',
+        '[lstm] TypeError is expected if the data type is not one of the floating point types',
     input: {dataType: 'uint32', dimensions: kValidInputDimensions},
     weight: {dataType: 'uint32', dimensions: kValidWeightDimensions},
     recurrentWeight:
@@ -147,7 +147,7 @@ const tests = [
     hiddenSize: hiddenSize
   },
   {
-    name: '[lstm] DataError is expected if the rank of input is not 3',
+    name: '[lstm] TypeError is expected if the rank of input is not 3',
     input: {dataType: 'float32', dimensions: [steps, batchSize]},
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
@@ -156,15 +156,15 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if input.dimensions[0] is not equal to steps',
+        '[lstm] TypeError is expected if input.dimensions[0] is not equal to steps',
     input: {dataType: 'float32', dimensions: [1000, batchSize, inputSize]},
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
     steps: steps,
     hiddenSize: hiddenSize
   },
   {
-    name: '[lstm] DataError is expected if the shape of weight is incorrect',
+    name: '[lstm] TypeError is expected if the shape of weight is incorrect',
     input: kExampleInputDescriptor,
     weight: {
       dataType: 'float32',
@@ -176,7 +176,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the rank of recurrentWeight is not 3',
+        '[lstm] TypeError is expected if the rank of recurrentWeight is not 3',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight:
@@ -186,7 +186,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the size of options.activations is not 3',
+        '[lstm] TypeError is expected if the size of options.activations is not 3',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
@@ -195,7 +195,7 @@ const tests = [
     options: {activations: ['sigmoid', 'tanh']}
   },
   {
-    name: '[lstm] DataError is expected if the rank of options.bias is not 2',
+    name: '[lstm] TypeError is expected if the rank of options.bias is not 2',
     input: {dataType: 'float16', dimensions: kValidInputDimensions},
     weight: {dataType: 'float16', dimensions: kValidWeightDimensions},
     recurrentWeight:
@@ -206,7 +206,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the shape of options.recurrentBias.dimensions is incorrect',
+        '[lstm] TypeError is expected if the shape of options.recurrentBias.dimensions is incorrect',
     input: {dataType: 'float16', dimensions: kValidInputDimensions},
     weight: {dataType: 'float16', dimensions: kValidWeightDimensions},
     recurrentWeight:
@@ -219,7 +219,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the dataType of options.peepholeWeight is incorrect',
+        '[lstm] TypeError is expected if the dataType of options.peepholeWeight is incorrect',
     input: {dataType: 'float16', dimensions: kValidInputDimensions},
     weight: {dataType: 'float16', dimensions: kValidWeightDimensions},
     recurrentWeight:
@@ -233,7 +233,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the dataType of options.initialHiddenState is incorrect',
+        '[lstm] TypeError is expected if the dataType of options.initialHiddenState is incorrect',
     input: {dataType: 'float16', dimensions: kValidInputDimensions},
     weight: {dataType: 'float16', dimensions: kValidWeightDimensions},
     recurrentWeight:
@@ -249,7 +249,7 @@ const tests = [
   },
   {
     name:
-        '[lstm] DataError is expected if the shape of options.initialCellState is incorrect',
+        '[lstm] TypeError is expected if the shape of options.initialCellState is incorrect',
     input: kExampleInputDescriptor,
     weight: kExampleWeightDescriptor,
     recurrentWeight: kExampleRecurrentWeightDescriptor,
@@ -333,8 +333,8 @@ tests.forEach(
           assert_array_equals(outputs[i].shape(), test.outputs[i].dimensions);
         }
       } else {
-        assert_throws_dom(
-            'DataError',
+        assert_throws_js(
+            TypeError,
             () => builder.lstm(
                 input, weight, recurrentWeight, test.steps, test.hiddenSize,
                 options));

webnn/validation_tests/triangular.https.any.js

@@ -12,6 +12,6 @@ promise_test(async t => {
       assert_throws_js(TypeError, () => builder.triangular(input));
     }
   }
-}, "[triangular] DataError is expected if input's rank is less than 2");
+}, "[triangular] TypeError is expected if input's rank is less than 2");
 
 validateInputFromAnotherBuilder('triangular');