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[clang-tidy] Exclude cppcoreguidelines-avoid-magic-numbers (#57841)
Summary: Add cppcoreguidelines-avoid-magic-numbers exclusion to clang-tidy Remove existing nolint warnings using following script: ``` for file in `git ls-files | grep -v \.py`; do gsed '/^ *\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)/d' -i $file; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/57841 Reviewed By: samestep Differential Revision: D28295045 Pulled By: malfet fbshipit-source-id: 7c6e8d1213c9593f169ed3df6a916498f1a97163
This commit is contained in:
Nikita Shulga
committed by
Facebook GitHub Bot
Facebook GitHub Bot
parent
bc2540f0be
commit
3a66a1cb99
@ -33,7 +33,6 @@ TEST_F(ModuleTest, CanEnableAndDisableTrainingMode) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST_F(ModuleTest, ZeroGrad) {
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Linear module(3, 4);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto weight = torch::ones({8, 3}, torch::requires_grad());
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auto loss = module(weight).sum();
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loss.backward();
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@ -56,9 +55,7 @@ TEST_F(ModuleTest, ZeroGrad) {
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TEST_F(ModuleTest, ZeroGradWithUndefined) {
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struct TestModule : torch::nn::Module {
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TestModule() {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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x = register_parameter("x", torch::ones(5, torch::requires_grad()));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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y = register_parameter("y", torch::ones(5, torch::requires_grad()));
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}
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torch::Tensor x, y;
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@ -117,7 +114,6 @@ TEST_F(ModuleTest, ReplaceModule) {
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}
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};
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auto model = std::make_shared<TestModel>();
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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model->l1 = model->replace_module("l1", torch::nn::Linear(5, 6));
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ASSERT_EQ(model->named_parameters()["l1.weight"].size(0), 6);
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ASSERT_EQ(model->l1.get(), model->named_modules()["l1"]->as<Linear>());
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@ -150,7 +146,6 @@ TEST_F(ModuleTest, RegisterParameterThrowsForEmptyOrDottedName) {
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TEST_F(ModuleTest, RegisterParameterThrowsForDuplicateModuleName) {
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struct TestModel : public torch::nn::Module {};
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TestModel model;
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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model.register_parameter("p", torch::ones(5));
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ASSERT_THROWS_WITH(
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model.register_parameter("p", torch::ones(5)),
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@ -196,7 +191,6 @@ TEST_F(ModuleTest, RegisterBufferThrowsForEmptyOrDottedName) {
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TEST_F(ModuleTest, RegisterBufferThrowsForDuplicateModuleName) {
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struct TestModel : public torch::nn::Module {};
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TestModel model;
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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model.register_buffer("p", torch::ones(5));
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ASSERT_THROWS_WITH(
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model.register_buffer("p", torch::ones(5)), "Buffer 'p' already defined");
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@ -247,7 +241,6 @@ void test_DeviceOrDtypeConversionSkipsUndefinedTensor(
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torch::Device to_device, torch::Dtype to_dtype) {
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{
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// Case 1: Undefined tensors as parameters
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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Linear module(LinearOptions(10, 20).bias(false));
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ASSERT_TRUE(module->weight.defined());
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ASSERT_FALSE(module->bias.defined());
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@ -264,7 +257,6 @@ void test_DeviceOrDtypeConversionSkipsUndefinedTensor(
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}
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{
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// Case 2: Undefined tensors as buffers
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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BatchNorm1d module(BatchNorm1dOptions(5).track_running_stats(false).affine(true));
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ASSERT_TRUE(module->weight.defined());
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ASSERT_FALSE(module->running_mean.defined());
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@ -294,7 +286,6 @@ TEST_F(ModuleTest, DeviceOrDtypeConversionSkipsUndefinedTensor_CUDA) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST_F(ModuleTest, ParametersAndBuffersAccessorSkipsUndefinedTensor) {
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{
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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Linear module(LinearOptions(10, 20).bias(false));
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auto params = module->parameters();
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@ -306,7 +297,6 @@ TEST_F(ModuleTest, ParametersAndBuffersAccessorSkipsUndefinedTensor) {
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ASSERT_TRUE(pointer_equal(named_params["weight"], module->weight));
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}
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{
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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BatchNorm1d module(BatchNorm1dOptions(5).track_running_stats(false).affine(false));
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auto buffers = module->buffers();
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@ -315,7 +305,6 @@ TEST_F(ModuleTest, ParametersAndBuffersAccessorSkipsUndefinedTensor) {
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ASSERT_EQ(named_buffers.size(), 0);
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}
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{
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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BatchNorm1d module(BatchNorm1dOptions(5).track_running_stats(true).affine(false));
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auto buffers = module->buffers();
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@ -334,7 +323,6 @@ TEST_F(ModuleTest, ParametersAndBuffersAccessorSkipsUndefinedTensor) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST_F(ModuleTest, Conversion_MultiCUDA) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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Linear module(128, 64);
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for (auto& parameter : module->parameters()) {
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ASSERT_EQ(parameter.device(), torch::Device(torch::kCPU));
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@ -411,11 +399,8 @@ struct TestDistinctParametersModule
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reset();
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}
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void reset() override {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l1 = register_module("l1", Linear(10, 3));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l2 = register_module("l2", Linear(3, 5));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l3 = register_module("l3", Linear(5, 100));
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buffer = register_buffer("buf", torch::ones({2, 2}));
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}
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@ -557,7 +542,6 @@ TEST_F(ModuleTest, CloneCopiesTheValuesOfVariablesOfSubmodules) {
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{
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torch::NoGradGuard no_grad;
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a->module->weight += 1;
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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a->module->value = 123;
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}
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@ -581,11 +565,8 @@ TEST_F(ModuleTest, CloneToDevicePreservesTheDeviceOfParameters_CUDA) {
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reset();
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}
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void reset() override {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l1 = register_module("l1", Linear(10, 3));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l2 = register_module("l2", Linear(3, 5));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l3 = register_module("l3", Linear(5, 100));
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buffer = register_buffer("buf", torch::ones({2, 2}));
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}
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@ -621,11 +602,8 @@ TEST_F(
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reset();
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}
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void reset() override {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l1 = register_module("l1", Linear(10, 3));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l2 = register_module("l2", Linear(3, 5));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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l3 = register_module("l3", Linear(5, 100));
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buffer = register_buffer("buf", torch::ones({2, 2}));
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}
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@ -701,7 +679,6 @@ TEST_F(ModuleTest, ContainsBuffersWithTheCorrectName) {
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}
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struct AImpl : torch::nn::Module {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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AImpl() : x_(123) {}
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AImpl(int x) : x_(x) {}
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int x_;
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@ -722,7 +699,6 @@ TEST_F(
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TEST_F(
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ModuleTest,
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ValueConstructorOfModuleHolderCallsCorrectConstructorInImpl) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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A a(5);
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ASSERT_TRUE(a);
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ASSERT_FALSE(a.is_empty());
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@ -906,11 +882,8 @@ std::shared_ptr<TestContainer> make_deeply_nested_test_container() {
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{TestContainer(1, {TestContainer(2), TestContainer(3)}),
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TestContainer(4),
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TestContainer(
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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5,
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{TestContainer(6),
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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TestContainer(7, {TestContainer(8), TestContainer(9)})})}));
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}
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@ -921,15 +894,10 @@ make_key_value_pairs_for_deeply_nested_container() {
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{"test_prefix.0.0", 2},
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{"test_prefix.0.1", 3},
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{"test_prefix.1", 4},
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{"test_prefix.2", 5},
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{"test_prefix.2.0", 6},
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{"test_prefix.2.1", 7},
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{"test_prefix.2.1.0", 8},
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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{"test_prefix.2.1.1", 9}};
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}
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