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Merge pull request #284 from bbernhar/super_resolution
Add SuperResolution example and test
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‎examples/SuperResolution/SuperResolution.cpp‎

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// Copyright 2022 The WebNN-native Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "examples/SuperResolution/SuperResolution.h"
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SuperResolution::SuperResolution() : ExampleBase() {
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}
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const wnn::Operand SuperResolution::BuildConstantFromNpy(const wnn::GraphBuilder& builder,
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const std::string& path) {
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const cnpy::NpyArray data = cnpy::npy_load(path);
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mConstants.push_back(data.data_holder);
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return utils::BuildConstant(builder, data.shape, data.data<float>(), data.num_bytes());
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}
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const wnn::Operand SuperResolution::BuildConv(const wnn::GraphBuilder& builder,
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const wnn::Operand& input,
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int32_t convIndex,
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bool relu,
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utils::Conv2dOptions* options,
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const std::string& biasName) {
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std::string prefix = mLayout == "nchw" ? mWeightsPath + "conv" : mWeightsPath + "Const_";
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std::string suffix = mLayout == "nchw" ? "_weight.npy" : ".npy";
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const std::string weightsPath = prefix + std::to_string(convIndex) + suffix;
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const wnn::Operand convWeights = BuildConstantFromNpy(builder, weightsPath);
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// TODO: Figure out correct "channels last" path suffix.
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prefix = mLayout == "nchw" ? mWeightsPath + "conv" : mWeightsPath + "super_resolution_";
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if (mLayout == "nchw") {
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prefix.append(std::to_string(convIndex));
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}
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const std::string biasPath = prefix + biasName + "_bias.npy";
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const wnn::Operand convBias = BuildConstantFromNpy(builder, biasPath);
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const wnn::Conv2dOptions* conv2dOptions = options != nullptr ? options->AsPtr() : nullptr;
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const wnn::Operand conv2d = builder.Conv2d(input, convWeights, conv2dOptions);
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if (!mFused) {
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if (relu) {
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return builder.Relu(conv2d);
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}
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return conv2d;
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}
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// Fused
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utils::Conv2dOptions fusedOptions;
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if (options != nullptr) {
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fusedOptions = *options;
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}
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fusedOptions.bias = convBias;
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if (relu) {
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fusedOptions.activation = builder.ReluOperator();
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}
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return builder.Conv2d(input, convWeights, fusedOptions.AsPtr());
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}
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const wnn::Operand SuperResolution::LoadNchw(const wnn::GraphBuilder& builder, bool softmax) {
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const wnn::Operand input = utils::BuildInput(builder, "input", {1, 1, 224, 224});
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utils::Conv2dOptions conv1Options;
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conv1Options.strides = {1, 1};
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conv1Options.padding = {2, 2, 2, 2};
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conv1Options.dilations = {1, 1};
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const wnn::Operand conv1 =
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BuildConv(builder, input, /*convIndex*/ 1, /*relu*/ true, &conv1Options);
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utils::Conv2dOptions conv2Options;
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conv2Options.strides = {1, 1};
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conv2Options.padding = {1, 1, 1, 1};
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conv2Options.dilations = {1, 1};
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const wnn::Operand conv2 =
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BuildConv(builder, conv1, /*convIndex*/ 2, /*relu*/ true, &conv2Options);
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utils::Conv2dOptions conv3Options;
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conv3Options.strides = {1, 1};
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conv3Options.padding = {1, 1, 1, 1};
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conv3Options.dilations = {1, 1};
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const wnn::Operand conv3 =
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BuildConv(builder, conv2, /*convIndex*/ 3, /*relu*/ true, &conv3Options);
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utils::Conv2dOptions conv4Options;
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conv4Options.strides = {1, 1};
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conv4Options.padding = {1, 1, 1, 1};
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conv4Options.dilations = {1, 1};
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const wnn::Operand conv4 =
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BuildConv(builder, conv3, /*convIndex*/ 4, /*relu*/ false, &conv4Options);
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const std::vector<int32_t> newShape1 = {-1, 1, 3, 3, 224, 224};
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const wnn::Operand reshape1 = builder.Reshape(conv4, newShape1.data(), newShape1.size());
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wnn::TransposeOptions transpose1Options;
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std::vector<int32_t> permutation = {0, 1, 4, 2, 5, 3};
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transpose1Options.permutation = permutation.data();
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transpose1Options.permutationCount = permutation.size();
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const wnn::Operand transpose1 = builder.Transpose(reshape1, &transpose1Options);
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const std::vector<int32_t> newShape2 = {-1, 1, 672, 672};
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return builder.Reshape(transpose1, newShape2.data(), newShape2.size());
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}

‎examples/SuperResolution/SuperResolution.h‎

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// Copyright 2022 The WebNN-native Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <webnn/webnn.h>
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#include <webnn/webnn_cpp.h>
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#include "examples/SampleUtils.h"
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class SuperResolution : public ExampleBase {
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public:
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SuperResolution();
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~SuperResolution() override = default;
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const wnn::Operand LoadNchw(const wnn::GraphBuilder& builder, bool softmax);
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private:
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const wnn::Operand BuildConstantFromNpy(const wnn::GraphBuilder& builder,
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const std::string& path);
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const wnn::Operand BuildConv(const wnn::GraphBuilder& builder,
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const wnn::Operand& input,
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int32_t convIndex,
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bool relu6,
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utils::Conv2dOptions* options,
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const std::string& biasName = "");
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std::vector<SHARED_DATA_TYPE> mConstants;
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};

‎src/webnn/native/dmlx/GraphDMLX.cpp‎

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DAWN_ASSERT(mExpression.find(inputOperand) != mExpression.end());
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::dml::Expression input = mExpression.at(inputOperand);
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auto newShape = reshape->GetNewShape();
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if (newShape.size() > DML_TENSOR_DIMENSION_COUNT_MAX) {
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if (newShape.size() > DML_TENSOR_DIMENSION_COUNT_MAX1) {
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return DAWN_INTERNAL_ERROR("The size of new shape is not supported by DML.");
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}
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::dml::TensorDimensions newSizes(newShape.size());
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DAWN_ASSERT(mExpression.find(inputOperand) != mExpression.end());
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::dml::Expression input = mExpression.at(inputOperand);
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std::vector<int32_t> permutation = transpose->GetPermutation();
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if (permutation.size() > DML_TENSOR_DIMENSION_COUNT_MAX) {
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if (permutation.size() > DML_TENSOR_DIMENSION_COUNT_MAX1) {
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return DAWN_INTERNAL_ERROR("The size of permutation is not supported by DML.");
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}
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‎src/webnn/tests/BUILD.gn‎

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"${webnn_root}/src/webnn:cpp",
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"${webnn_root}/src/webnn:webnn_proc",
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"${webnn_root}/src/webnn/common",
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"${webnn_root}/src/webnn/native:webnn_native",
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"${webnn_root}/src/webnn/native:sources",
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"${webnn_root}/src/webnn/native:webnn_native",
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"${webnn_root}/src/webnn/utils:webnn_utils",
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]
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"${webnn_root}/examples/ResNet/ResNet.h",
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"${webnn_root}/examples/SqueezeNet/SqueezeNet.cpp",
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"${webnn_root}/examples/SqueezeNet/SqueezeNet.h",
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"${webnn_root}/examples/SuperResolution/SuperResolution.cpp",
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"${webnn_root}/examples/SuperResolution/SuperResolution.h",
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"WebnnTest.cpp",
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"WebnnTest.h",
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"end2end/AddTests.cpp",
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"end2end/models/ResNetNhwc.cpp",
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"end2end/models/SqueezeNetNchw.cpp",
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"end2end/models/SqueezeNetNhwc.cpp",
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"end2end/models/SuperResolutionNchw.cpp",
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]
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# Validation tests that need OS windows live in end2end tests.

‎src/webnn/tests/end2end/models/SuperResolutionNchw.cpp‎

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// Copyright 2022 The WebNN-native Authors
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "examples/SuperResolution/SuperResolution.h"
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#include "webnn/tests/WebnnTest.h"
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static const std::string kModelPath = WEBNN_END2END_TEST_MODEL_PATH;
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class SuperResolutionNchwTests : public WebnnTest {
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public:
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void TestSuperResolutionNchw(const std::string& inputFile,
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const std::string& expectedFile,
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bool fused = true) {
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SuperResolution superresolution;
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superresolution.mFused = true;
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const std::string nchwPath = kModelPath + "/super_resolution_nchw/";
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superresolution.mWeightsPath = nchwPath + "weights/";
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const wnn::GraphBuilder builder = wnn::CreateGraphBuilder(GetContext());
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wnn::Operand output = superresolution.LoadNchw(builder, false);
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wnn::Graph graph = utils::Build(builder, {{"output", output}});
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const cnpy::NpyArray inputNpy = cnpy::npy_load(nchwPath + "test_data_set/" + inputFile);
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const std::vector<float> inputData = inputNpy.as_vec<float>();
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std::vector<float> result(utils::SizeOfShape({/*TODO: batchSize?*/ 1, 1, 672, 672}));
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utils::Compute(graph, {{"input", inputData}}, {{"output", result}});
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const cnpy::NpyArray outputNpy = cnpy::npy_load(nchwPath + "test_data_set/" + expectedFile);
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EXPECT_TRUE(utils::CheckValue(result, outputNpy.as_vec<float>()));
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}
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};
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TEST_F(SuperResolutionNchwTests, NchwTest0) {
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TestSuperResolutionNchw("0/input_0.npy", "0/output_0.npy", false);
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}

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