webnn: emulate dequantizeLinear on coreml

Add emulation code for when input is not constant, or blockwise, or
type is (u)int32 for `dequantizeLinear` on CoreML.

Bug: 338529226
Change-Id: I70994755baf1f34600d0cb5079698250ef5821e9
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/6389321
Reviewed-by: Reilly Grant <reillyg@chromium.org>
Commit-Queue: Phillis Tang <phillis@chromium.org>
Cr-Commit-Position: refs/heads/main@{#1438377}

services/webnn/coreml/graph_builder_coreml.cc

@@ -1136,6 +1136,9 @@ ContextProperties GraphBuilderCoreml::GetContextProperties() {
   static constexpr SupportedDataTypes kGatherIndicesSupportedDataTypes{
       OperandDataType::kInt32, OperandDataType::kInt8, OperandDataType::kUint8};
 
+  static constexpr SupportedDataTypes kInts8Ints32{
+      OperandDataType::kInt8, OperandDataType::kUint8, OperandDataType::kInt32,
+      OperandDataType::kUint32};
   SupportedDataTypes arg_min_max_input_supported_data_types = kFloatsAndInt32;
   // crbug.com/388117627: On Intel devices, passing float input containing NaNs
   // sometimes triggers a crash in Core ML.
@@ -1195,11 +1198,11 @@ ContextProperties GraphBuilderCoreml::GetContextProperties() {
        // input.
        // TODO(crbug.com/361603703): Support constant (u)int4 inputs via
        // https://apple.github.io/coremltools/source/coremltools.converters.mil.mil.ops.defs.html#coremltools.converters.mil.mil.ops.defs.iOS18.compression.constexpr_blockwise_shift_scale
-       /*dequantize_linear_input=*/{DataTypeConstraint::kInts8, kMaxRank},
+       /*dequantize_linear_input=*/{kInts8Ints32, kMaxRank},
        /*dequantize_linear_scale=*/
-       {DataTypeConstraint::kFloat16To32, SupportedRanks::UpTo(1)},
+       {DataTypeConstraint::kFloat16To32, kMaxRank},
        /*dequantize_linear_zero_point=*/
-       {DataTypeConstraint::kInts8, SupportedRanks::UpTo(1)},
+       {kInts8Ints32, kMaxRank},
        /*add_input=*/{kFloatsAndInt32, kMaxRank},
        /*sub_input=*/{kFloatsAndInt32, kMaxRank},
        /*mul_input=*/{kFloatsAndInt32, kMaxRank},
@@ -1392,12 +1395,10 @@ ContextProperties GraphBuilderCoreml::GetContextProperties() {
        /*where_value=*/{kFloatsAndInt32, kMaxRank}});
 
   if (__builtin_available(macOS 15, *)) {
-    properties.data_type_limits.dequantize_linear_scale.ranks = kMaxRank;
-    properties.data_type_limits.dequantize_linear_zero_point.ranks = kMaxRank;
     properties.data_type_limits.dequantize_linear_input.data_types =
-        DataTypeConstraint::kInts4ToInts8;
+        DataTypeConstraint::kInts4Ints8Ints32;
     properties.data_type_limits.dequantize_linear_zero_point.data_types =
-        DataTypeConstraint::kInts4ToInts8;
+        DataTypeConstraint::kInts4Ints8Ints32;
   }
   return properties;
 }
@@ -2354,16 +2355,14 @@ GraphBuilderCoreml::AddOperationForDequantizeLinear(
   CHECK(context_properties_.data_type_limits.dequantize_linear_zero_point
             .data_types.Has(zero_point_operand_data_type));
 
-  // TODO(crbug.com/338529226): These params must all be constant tensors.
-  if (!constant_operands_->contains(operation.zero_point_operand_id)) {
-    return NewNotSupportedError(
-        "Unsupported options to dequantizeLinear. 'zero_point' must be "
-        "constant.");
+  if (input_operand_data_type == OperandDataType::kInt32 ||
+      input_operand_data_type == OperandDataType::kUint32) {
+    return AddOperationForDequantizeLinearEmulate(operation, block);
   }
 
-  if (!constant_operands_->contains(operation.scale_operand_id)) {
-    return NewNotSupportedError(
-        "Unsupported options to dequantizeLinear. 'scale' must be constant.");
+  if (!constant_operands_->contains(operation.zero_point_operand_id) ||
+      !constant_operands_->contains(operation.scale_operand_id)) {
+    return AddOperationForDequantizeLinearEmulate(operation, block);
   }
 
   CHECK_EQ(input_operand_info.mil_data_type,
@@ -2386,17 +2385,32 @@ GraphBuilderCoreml::AddOperationForDequantizeLinear(
     }
   }
 
-  if (scale_operand_info.dimensions.size() == 1 &&
-      scale_operand_info.dimensions[0] !=
-          input_operand_info
-              .dimensions[input_operand_info.dimensions.size() - 1]) {
-    return NewNotSupportedError(
-        "Unsupported options to dequantizeLinear. The size of 'scale' must be "
-        "equal to the size of the input's last dimension.");
+  // CoreML `dequantize` and `constexpr_affine_dequantize` only support scalar
+  // or vector scale whose size matches with one axis of input.
+  base::span<const uint32_t> scale_dimensions = scale_operand_info.dimensions;
+  base::span<const uint32_t> input_dimensions = input_operand_info.dimensions;
+  CHECK_LE(scale_dimensions.size(), input_dimensions.size());
+  uint32_t scale_vector_size = 0;
+  size_t axis = 0;
+  bool has_matching_dimension = false;
+  for (size_t i = 0; i < scale_dimensions.size(); ++i) {
+    size_t current_axis = input_dimensions.size() + i - scale_dimensions.size();
+    if (scale_dimensions[i] != 1) {
+      // Only allow at most one matching dimension, otherwise emulate.
+      if (scale_dimensions[i] != input_dimensions[current_axis] ||
+          has_matching_dimension) {
+        return AddOperationForDequantizeLinearEmulate(operation, block);
+      } else {
+        axis = current_axis;
+        scale_vector_size = scale_dimensions[i];
+        has_matching_dimension = true;
+      }
+    }
   }
 
   if (is_constant_input) {
-    return AddOperationForDequantizeLinearConst(operation, block);
+    return AddOperationForDequantizeLinearConst(operation, axis,
+                                                scale_vector_size <= 1, block);
   }
 
   uint64_t input_operand_id = operation.input_operand_id;
@@ -2415,17 +2429,23 @@ GraphBuilderCoreml::AddOperationForDequantizeLinear(
   RETURN_IF_ERROR(SetInputFromOperand(*op->mutable_inputs(), kParamInput,
                                       input_operand_id));
 
-  RETURN_IF_ERROR(SetInputFromOperand(*op->mutable_inputs(), kOpParamZeroPoint,
-                                      operation.zero_point_operand_id));
+  // If scale shape is [1], pass as scalar instead because CoreML only allows
+  // scalar or vector with size matching input dimension.
+  RETURN_IF_ERROR(SetInputFromConstantOperand(
+      *op->mutable_inputs(), kOpParamZeroPoint, operation.zero_point_operand_id,
+      scale_vector_size > 1 ? base::span<const uint32_t>{scale_vector_size}
+                            : base::span<const uint32_t>{}));
 
-  RETURN_IF_ERROR(SetInputFromOperand(*op->mutable_inputs(), kOpParamScale,
-                                      operation.scale_operand_id));
+  RETURN_IF_ERROR(SetInputFromConstantOperand(
+      *op->mutable_inputs(), kOpParamScale, operation.scale_operand_id,
+      scale_vector_size > 1 ? base::span<const uint32_t>{scale_vector_size}
+                            : base::span<const uint32_t>{}));
 
   // An "axis" must be specified if "scale" is a vector.
-  if (!scale_operand_info.dimensions.empty()) {
-    SetInputWithValue(*op->mutable_inputs(), kOpParamAxis,
-                      CreateScalarImmediateValue(base::checked_cast<int32_t>(
-                          input_operand_info.dimensions.size() - 1)));
+  if (!scale_dimensions.empty()) {
+    SetInputWithValue(
+        *op->mutable_inputs(), kOpParamAxis,
+        CreateScalarImmediateValue(base::checked_cast<int32_t>(axis)));
   }
 
   if (input_operand_id != operation.input_operand_id) {
@@ -2446,11 +2466,11 @@ GraphBuilderCoreml::AddOperationForDequantizeLinear(
 [[nodiscard]] base::expected<void, mojom::ErrorPtr>
 GraphBuilderCoreml::AddOperationForDequantizeLinearConst(
     const mojom::DequantizeLinear& operation,
+    size_t axis,
+    bool is_scalar_scale,
     CoreML::Specification::MILSpec::Block& block) {
   const OperandInfo& input_operand_info =
       GetOperandInfo(operation.input_operand_id);
-  const OperandInfo& scale_operand_info =
-      GetOperandInfo(operation.scale_operand_id);
 
   CHECK(constant_operands_->contains(operation.input_operand_id));
   CHECK(constant_operands_->contains(operation.zero_point_operand_id));
@@ -2460,20 +2480,15 @@ GraphBuilderCoreml::AddOperationForDequantizeLinearConst(
   op->set_type(kOpDequantizeLinearConstTypeName);
 
   static constexpr char kParamInput[] = "quantized_data";
-  bool input_needs_reshape = input_operand_info.dimensions.empty();
+  std::vector<uint32_t> input_dimensions = input_operand_info.dimensions.empty()
+                                               ? std::vector<uint32_t>{1}
+                                               : input_operand_info.dimensions;
   CoreML::Specification::MILSpec::Value value;
-  if (input_needs_reshape) {
-    ASSIGN_OR_RETURN(value,
-                     weights_file_handle_->Write(
-                         operation.input_operand_id,
-                         *constant_operands_->at(operation.input_operand_id),
-                         std::array<uint32_t, 1>{1}));
-  } else {
-    ASSIGN_OR_RETURN(value,
-                     weights_file_handle_->Write(
-                         operation.input_operand_id,
-                         *constant_operands_->at(operation.input_operand_id)));
-  }
+  ASSIGN_OR_RETURN(value,
+                   weights_file_handle_->Write(
+                       operation.input_operand_id,
+                       *constant_operands_->at(operation.input_operand_id),
+                       input_dimensions));
   // This op requires all parameters passed as attributes instead of inputs.
   (*op->mutable_attributes())[kParamInput] = std::move(value);
 
@@ -2481,21 +2496,22 @@ GraphBuilderCoreml::AddOperationForDequantizeLinearConst(
       (*op->mutable_attributes())[kOpParamZeroPoint],
       weights_file_handle_->Write(
           operation.zero_point_operand_id,
-          *constant_operands_->at(operation.zero_point_operand_id)))
+          *constant_operands_->at(operation.zero_point_operand_id),
+          is_scalar_scale ? base::span<const uint32_t>{}
+                          : base::span<const uint32_t>{input_dimensions[axis]}))
 
-  ASSIGN_OR_RETURN((*op->mutable_attributes())[kOpParamScale],
-                   weights_file_handle_->Write(
-                       operation.scale_operand_id,
-                       *constant_operands_->at(operation.scale_operand_id)))
+  ASSIGN_OR_RETURN(
+      (*op->mutable_attributes())[kOpParamScale],
+      weights_file_handle_->Write(
+          operation.scale_operand_id,
+          *constant_operands_->at(operation.scale_operand_id),
+          is_scalar_scale ? base::span<const uint32_t>{}
+                          : base::span<const uint32_t>{input_dimensions[axis]}))
 
-  int32_t axis = 0;
-  if (!scale_operand_info.dimensions.empty()) {
-    axis =
-        base::checked_cast<int32_t>(input_operand_info.dimensions.size() - 1);
-  }
-  (*op->mutable_attributes())[kOpParamAxis] = CreateScalarImmediateValue(axis);
+  (*op->mutable_attributes())[kOpParamAxis] =
+      CreateScalarImmediateValue(base::checked_cast<int32_t>(axis));
 
-  if (input_needs_reshape) {
+  if (input_operand_info.dimensions.empty()) {
     ASSIGN_OR_RETURN(
         uint64_t output_operand_id,
         GenerateInternalOperandInfo(
@@ -2574,6 +2590,128 @@ GraphBuilderCoreml::AddOperationForDequantizeLinearConstBlockwise(
   return base::ok();
 }
 
+[[nodiscard]] base::expected<void, mojom::ErrorPtr>
+GraphBuilderCoreml::AddOperationForDequantizeLinearEmulate(
+    const mojom::DequantizeLinear& operation,
+    CoreML::Specification::MILSpec::Block& block) {
+  const OperandInfo& input_operand_info =
+      GetOperandInfo(operation.input_operand_id);
+  const OperandInfo& scale_operand_info =
+      GetOperandInfo(operation.scale_operand_id);
+  const OperandInfo& zero_point_operand_info =
+      GetOperandInfo(operation.zero_point_operand_id);
+
+  // cast(zero_point, scale_type)
+  base::span<const uint32_t> scale_dimensions = scale_operand_info.dimensions;
+  base::span<const uint32_t> input_dimensions = input_operand_info.dimensions;
+  uint64_t scale_operand_id = operation.scale_operand_id;
+  uint64_t zero_point_operand_id = operation.zero_point_operand_id;
+  ASSIGN_OR_RETURN(
+      zero_point_operand_id,
+      GenerateInternalOperandInfo(scale_operand_info.mil_data_type,
+                                  zero_point_operand_info.dimensions));
+  RETURN_IF_ERROR(AddOperationForCast(operation.zero_point_operand_id,
+                                      zero_point_operand_id, block));
+
+  // When zero_point and scale on a dimension is not
+  // input_dimension or 1, this is a blockwise dequantization, the zero_point
+  // and scale need to be expanded.
+  for (size_t i = 0; i < scale_dimensions.size(); ++i) {
+    uint32_t scale_vector_size = scale_dimensions[i];
+    size_t current_axis = input_dimensions.size() + i - scale_dimensions.size();
+    if (scale_vector_size != 1 &&
+        scale_vector_size != input_dimensions[current_axis]) {
+      // For blockwise dequantization we need to expand the shape by 1 during
+      // `ExpandForBlockwise`, so the original shape needs to be <=4.
+      if (scale_dimensions.size() > 4) {
+        return NewNotSupportedError(
+            "Unsupported rank for dequantizeLinear argument scale. It should "
+            "be between 0 and 4 for blockwise dequantization.");
+      }
+      CHECK_EQ(input_dimensions[current_axis] % scale_vector_size, 0u);
+      const int32_t repetitions =
+          input_dimensions[current_axis] / scale_vector_size;
+      uint64_t prev_scale = scale_operand_id;
+      ASSIGN_OR_RETURN(scale_operand_id,
+                       ExpandForBlockwise(prev_scale, i, repetitions, block));
+      uint64_t prev_zero_point = zero_point_operand_id;
+      ASSIGN_OR_RETURN(
+          zero_point_operand_id,
+          ExpandForBlockwise(prev_zero_point, i, repetitions, block));
+    }
+  }
+
+  // `output = (input - zeroPoint) * scale`.
+  ASSIGN_OR_RETURN(uint64_t casted_input,
+                   GenerateInternalOperandInfo(scale_operand_info.mil_data_type,
+                                               input_operand_info.dimensions));
+  RETURN_IF_ERROR(
+      AddOperationForCast(operation.input_operand_id, casted_input, block));
+
+  ASSIGN_OR_RETURN(uint64_t minus_zero_point,
+                   GenerateInternalOperandInfo(scale_operand_info.mil_data_type,
+                                               input_operand_info.dimensions));
+  RETURN_IF_ERROR(AddOperationForElementwiseBinary(
+      casted_input, zero_point_operand_id, minus_zero_point,
+      mojom::ElementWiseBinary::Kind::kSub, block));
+
+  RETURN_IF_ERROR(AddOperationForElementwiseBinary(
+      minus_zero_point, scale_operand_id, operation.output_operand_id,
+      mojom::ElementWiseBinary::Kind::kMul, block));
+  return base::ok();
+}
+
+[[nodiscard]] base::expected<uint64_t, mojom::ErrorPtr>
+GraphBuilderCoreml::ExpandForBlockwise(
+    uint64_t input_operand_id,
+    size_t repetition_axis,
+    int32_t repetitions,
+    CoreML::Specification::MILSpec::Block& block) {
+  const OperandInfo& input_operand_info = GetOperandInfo(input_operand_id);
+  base::span<const uint32_t> dimensions = input_operand_info.dimensions;
+  base::FixedArray<uint32_t> reshaped_dimensions(dimensions.size() + 1);
+
+  // `tile` repeats values for the whole dimension, but we want repetitions for
+  // each individual value, this is achieved by inserting dimension of 1 to be
+  // tiled, then reshape back.
+  auto [reshaped_dimensions_first, reshaped_dimensions_last] =
+      base::span(reshaped_dimensions).split_at(repetition_axis + 1);
+  auto [dimensions_first, dimensions_last] =
+      dimensions.split_at(repetition_axis + 1);
+  reshaped_dimensions_first.copy_from(dimensions_first);
+  reshaped_dimensions_last[0] = 1;
+  reshaped_dimensions_last.subspan(1u).copy_from(dimensions_last);
+
+  uint64_t prev_operand = input_operand_id;
+  ASSIGN_OR_RETURN(input_operand_id,
+                   GenerateInternalOperandInfo(input_operand_info.mil_data_type,
+                                               reshaped_dimensions));
+  RETURN_IF_ERROR(
+      AddOperationForReshape(prev_operand, input_operand_id, block));
+
+  base::FixedArray<uint32_t> tile_dimensions = reshaped_dimensions;
+  tile_dimensions[repetition_axis + 1] = repetitions;
+  prev_operand = input_operand_id;
+  ASSIGN_OR_RETURN(input_operand_id,
+                   GenerateInternalOperandInfo(input_operand_info.mil_data_type,
+                                               tile_dimensions));
+
+  base::FixedArray<int32_t> repetitions_for_tile(reshaped_dimensions.size(), 1);
+  repetitions_for_tile[repetition_axis + 1] = repetitions;
+  RETURN_IF_ERROR(AddOperationForTile(prev_operand, input_operand_id,
+                                      repetitions_for_tile, block));
+  std::vector<uint32_t> output_dimensions(input_operand_info.dimensions);
+  output_dimensions[repetition_axis] =
+      dimensions[repetition_axis] * repetitions;
+  ASSIGN_OR_RETURN(uint64_t output_operand_id,
+                   GenerateInternalOperandInfo(input_operand_info.mil_data_type,
+                                               output_dimensions));
+
+  RETURN_IF_ERROR(
+      AddOperationForReshape(input_operand_id, output_operand_id, block));
+  return output_operand_id;
+}
+
 base::expected<void, mojom::ErrorPtr>
 GraphBuilderCoreml::AddOperationForElementwiseBinary(
     std::variant<uint64_t, CoreML::Specification::MILSpec::Value> lhs_operand,
@@ -5127,27 +5265,35 @@ GraphBuilderCoreml::AddOperationForSplit(
 
 [[nodiscard]] base::expected<void, mojom::ErrorPtr>
 GraphBuilderCoreml::AddOperationForTile(
-    const mojom::Tile& operation,
+    uint64_t input_operand_id,
+    uint64_t output_operand_id,
+    base::span<const int32_t> repetitions,
     CoreML::Specification::MILSpec::Block& block) {
-  const OperandInfo& input_operand_info =
-      GetOperandInfo(operation.input_operand_id);
+  const OperandInfo& input_operand_info = GetOperandInfo(input_operand_id);
   CHECK(context_properties_.data_type_limits.tile_input.data_types.Has(
       MILDataTypeToOperandType(input_operand_info.mil_data_type)));
 
   CoreML::Specification::MILSpec::Operation* op = block.add_operations();
   op->set_type(kOpTileTypeName);
-  RETURN_IF_ERROR(SetInputFromOperand(*op->mutable_inputs(), kOpParamX,
-                                      operation.input_operand_id));
+  RETURN_IF_ERROR(
+      SetInputFromOperand(*op->mutable_inputs(), kOpParamX, input_operand_id));
 
-  // CoreML expects repetitions to be vector of int32_t.
-  SetInputWithValue(
-      *op->mutable_inputs(), kOpParamReps,
-      Create1DTensorImmediateValue<int32_t>(Ui32ToI32(operation.repetitions)));
+  SetInputWithValue(*op->mutable_inputs(), kOpParamReps,
+                    Create1DTensorImmediateValue<int32_t>(repetitions));
 
-  PopulateNamedValueType(operation.output_operand_id, *op->add_outputs());
+  PopulateNamedValueType(output_operand_id, *op->add_outputs());
   return base::ok();
 }
 
+[[nodiscard]] base::expected<void, mojom::ErrorPtr>
+GraphBuilderCoreml::AddOperationForTile(
+    const mojom::Tile& operation,
+    CoreML::Specification::MILSpec::Block& block) {
+  return AddOperationForTile(operation.input_operand_id,
+                             operation.output_operand_id,
+                             Ui32ToI32(operation.repetitions), block);
+}
+
 [[nodiscard]] base::expected<void, mojom::ErrorPtr>
 GraphBuilderCoreml::AddOperationForTranspose(
     uint64_t input_operand_id,

services/webnn/coreml/graph_builder_coreml.h

@@ -310,12 +310,25 @@ class GraphBuilderCoreml {
   [[nodiscard]] base::expected<void, mojom::ErrorPtr>
   AddOperationForDequantizeLinearConst(
       const mojom::DequantizeLinear& operation,
+      size_t axis,
+      bool is_scalar_scale,
       CoreML::Specification::MILSpec::Block& block);
   [[nodiscard]] base::expected<void, mojom::ErrorPtr>
   AddOperationForDequantizeLinearConstBlockwise(
       const mojom::DequantizeLinear& operation,
       CoreML::Specification::MILSpec::Block& block);
   [[nodiscard]] base::expected<void, mojom::ErrorPtr>
+  AddOperationForDequantizeLinearEmulate(
+      const mojom::DequantizeLinear& operation,
+      CoreML::Specification::MILSpec::Block& block);
+  // Expand for given `repetition` on `axis` for blockwise (de)quantization.
+  [[nodiscard]] base::expected<uint64_t, mojom::ErrorPtr> ExpandForBlockwise(
+      uint64_t input_operand_id,
+      size_t repetition_axis,
+      int32_t repetitions,
+      CoreML::Specification::MILSpec::Block& block);
+
+  [[nodiscard]] base::expected<void, mojom::ErrorPtr>
   AddOperationForElementwiseBinary(
       std::variant<uint64_t, CoreML::Specification::MILSpec::Value> lhs_operand,
       std::variant<uint64_t, CoreML::Specification::MILSpec::Value> rhs_operand,
@@ -499,6 +512,11 @@ class GraphBuilderCoreml {
   [[nodiscard]] base::expected<void, mojom::ErrorPtr> AddOperationForSplit(
       const mojom::Split& operation,
       CoreML::Specification::MILSpec::Block& block);
+  [[nodiscard]] base::expected<void, mojom::ErrorPtr> AddOperationForTile(
+      uint64_t input_operand_id,
+      uint64_t output_operand_id,
+      base::span<const int32_t> repetitions,
+      CoreML::Specification::MILSpec::Block& block);
   [[nodiscard]] base::expected<void, mojom::ErrorPtr> AddOperationForTile(
       const mojom::Tile& operation,
       CoreML::Specification::MILSpec::Block& block);

third_party/blink/web_tests/external/wpt/webnn/conformance_tests/dequantizeLinear.https.any.js

@@ -619,6 +619,43 @@ const dequantizeLinearTests = [
       }
     }
   },
+  {
+    'name': 'dequantizeLinear int32 1D tensor with float32 scalar scale',
+    'graph': {
+      'inputs': {
+        'dequantizeLinearInput': {
+          'data': [12345, 23946213],
+          'descriptor': {shape: [2], dataType: 'int32'},
+          'constant': false
+        },
+        'dequantizeLinearScale': {
+          'data': [1.1202747821807861, 0.2800687253475189],
+          'descriptor': {shape: [2], dataType: 'float32'},
+          'constant': true
+        },
+        'dequantizeLinearZeroPoint': {
+          'data': [32345, -2445234],
+          'descriptor': {shape: [2], dataType: 'int32'},
+          'constant': true
+        }
+      },
+      'operators': [{
+        'name': 'dequantizeLinear',
+        'arguments': [
+          {'input': 'dequantizeLinearInput'},
+          {'scale': 'dequantizeLinearScale'},
+          {'zeroPoint': 'dequantizeLinearZeroPoint'}
+        ],
+        'outputs': 'dequantizeLinearOutput'
+      }],
+      'expectedOutputs': {
+        'dequantizeLinearOutput': {
+          'data': [-22405.495643615723, 7391418.921366602],
+          'descriptor': {shape: [2], dataType: 'float32'}
+        }
+      }
+    }
+  },
 ];
 
 if (navigator.ml) {

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/dequantizeLinear.https.any_cpu-expected.txt

@@ -1,23 +1,17 @@
 This is a testharness.js-based test.
-[FAIL] dequantizeLinear uint8 1D constant tensor with implicit block_size = 2.
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to dequantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
-[FAIL] dequantizeLinear int8 4D constant tensor broadcasting scale and zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
-[FAIL] dequantizeLinear int8 4D constant tensor with block_size = [3, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
 [FAIL] dequantizeLinear uint4 1D tensor with even input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 1D tensor with odd input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 4D constant tensor broadcasting zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 3D input with block_size = [1, 1, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with even size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with odd size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] per-tensor dequantizeLinear for int4 4D constant
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_cpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_cpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_cpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any_cpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/dequantizeLinear.https.any_npu-expected.txt

@@ -1,23 +1,17 @@
 This is a testharness.js-based test.
-[FAIL] dequantizeLinear uint8 1D constant tensor with implicit block_size = 2.
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to dequantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
-[FAIL] dequantizeLinear int8 4D constant tensor broadcasting scale and zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
-[FAIL] dequantizeLinear int8 4D constant tensor with block_size = [3, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
 [FAIL] dequantizeLinear uint4 1D tensor with even input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 1D tensor with odd input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 4D constant tensor broadcasting zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 3D input with block_size = [1, 1, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with even size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with odd size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] per-tensor dequantizeLinear for int4 4D constant
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_npu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_npu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_npu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any_npu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/dequantizeLinear.https.any_gpu-expected.txt

@@ -1,23 +1,17 @@
 This is a testharness.js-based test.
-[FAIL] dequantizeLinear uint8 1D constant tensor with implicit block_size = 2.
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to dequantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
-[FAIL] dequantizeLinear int8 4D constant tensor broadcasting scale and zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
-[FAIL] dequantizeLinear int8 4D constant tensor with block_size = [3, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported rank 2 for argument zeroPoint (must be at most 1)."
 [FAIL] dequantizeLinear uint4 1D tensor with even input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 1D tensor with odd input size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 4D constant tensor broadcasting zeroPoint
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear uint4 3D input with block_size = [1, 1, 2]
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type uint4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with even size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] dequantizeLinear int4 1D tensor with odd size
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 [FAIL] per-tensor dequantizeLinear for int4 4D constant
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int8, uint8]."
+  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'dequantizeLinear' on 'MLGraphBuilder': Unsupported data type int4 for argument input, must be one of [int32, uint32, int8, uint8]."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_gpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_gpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_gpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac-mac14/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any_gpu-expected.txt

@@ -1,31 +0,0 @@
-This is a testharness.js-based test.
-[FAIL] batchNormalization default + relu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + leakyRelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + sigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + clamp
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + prelu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + elu
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + gelu
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + hardSigmoid
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + hardSwish
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization default + linear
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0 + softplus
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] batchNormalization default + softsign
-  promise_test: Unhandled rejection with value: object "TypeError: Failed to execute 'batchNormalization' on 'MLGraphBuilder': Unsupported rank 2 for argument input (must be at least 3)."
-[FAIL] batchNormalization options.axis=0  + softmax
-  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
-[FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8]."
-Harness: the test ran to completion.
-

third_party/blink/web_tests/platform/mac/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_cpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_cpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_cpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-on-cpu/external/wpt/webnn/conformance_tests/subgraph.https.any_cpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_gpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_gpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_gpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/platform/mac/virtual/webnn-service-with-gpu/external/wpt/webnn/conformance_tests/subgraph.https.any_gpu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.serviceworker_npu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.sharedworker_npu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any.worker_npu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.
 

third_party/blink/web_tests/virtual/webnn-service-on-npu/external/wpt/webnn/conformance_tests/subgraph.https.any_npu-expected.txt

@@ -26,6 +26,6 @@ This is a testharness.js-based test.
 [FAIL] batchNormalization options.axis=0  + softmax
   promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported axis for batchNormalization. It must be the channel dimension."
 [FAIL] quantized conv2d
-  promise_test: Unhandled rejection with value: object "TypeError: Unsupported data type, input 'input' data type int32 must be one of [int8,uint8,int4,uint4]."
+  promise_test: Unhandled rejection with value: object "NotSupportedError: Failed to execute 'build' on 'MLGraphBuilder': Unsupported options to quantizeLinear. The size of 'scale' must be equal to the size of the input's last dimension."
 Harness: the test ran to completion.