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Diffstat (limited to 'src/backends/test/JsonPrinterTestImpl.hpp')
| -rw-r--r-- | src/backends/test/JsonPrinterTestImpl.hpp | 354 |
1 files changed, 354 insertions, 0 deletions
diff --git a/src/backends/test/JsonPrinterTestImpl.hpp b/src/backends/test/JsonPrinterTestImpl.hpp new file mode 100644 index 0000000000..47e0ec761b --- /dev/null +++ b/src/backends/test/JsonPrinterTestImpl.hpp @@ -0,0 +1,354 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include <armnn/Descriptors.hpp> +#include <armnn/IRuntime.hpp> +#include <armnn/INetwork.hpp> +#include <armnn/Profiling.hpp> + +#include <boost/test/unit_test.hpp> +#include <boost/algorithm/string.hpp> +#include <boost/lexical_cast.hpp> + +#include <sstream> +#include <stack> +#include <string> +#include <vector> + +inline bool AreMatchingPair(const char opening, const char closing) +{ + return (opening == '{' && closing == '}') || (opening == '[' && closing == ']'); +} + +inline bool AreParenthesesMatching(const std::string& exp) +{ + std::stack<char> expStack; + for (size_t i = 0; i < exp.length(); ++i) + { + if (exp[i] == '{' || exp[i] == '[') + { + expStack.push(exp[i]); + } + else if (exp[i] == '}' || exp[i] == ']') + { + if (expStack.empty() || !AreMatchingPair(expStack.top(), exp[i])) + { + return false; + } + else + { + expStack.pop(); + } + } + } + return expStack.empty(); +} + +inline std::vector<double> ExtractMeasurements(const std::string& exp) +{ + std::vector<double> numbers; + bool inArray = false; + std::string numberString; + for (size_t i = 0; i < exp.size(); ++i) + { + if (exp[i] == '[') + { + inArray = true; + } + else if (exp[i] == ']' && inArray) + { + try + { + boost::trim_if(numberString, boost::is_any_of("\t,\n")); + numbers.push_back(std::stod(numberString)); + } + catch (std::invalid_argument const& e) + { + BOOST_FAIL("Could not convert measurements to double: " + numberString); + } + + numberString.clear(); + inArray = false; + } + else if (exp[i] == ',' && inArray) + { + try + { + boost::trim_if(numberString, boost::is_any_of("\t,\n")); + numbers.push_back(std::stod(numberString)); + } + catch (std::invalid_argument const& e) + { + BOOST_FAIL("Could not convert measurements to double: " + numberString); + } + numberString.clear(); + } + else if (exp[i] != '[' && inArray && exp[i] != ',' && exp[i] != ' ') + { + numberString += exp[i]; + } + } + return numbers; +} + +inline std::vector<std::string> ExtractSections(const std::string& exp) +{ + std::vector<std::string> sections; + + std::stack<size_t> s; + for (size_t i = 0; i < exp.size(); i++) + { + if (exp.at(i) == '{') + { + s.push(i); + } + else if (exp.at(i) == '}') + { + size_t from = s.top(); + s.pop(); + sections.push_back(exp.substr(from, i - from + 1)); + } + } + + return sections; +} + +inline std::string SoftmaxProfilerTestSetupHelper(const std::vector<armnn::BackendId>& backends) +{ + using namespace armnn; + + BOOST_CHECK(!backends.empty()); + + ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance(); + + // Create runtime in which test will run + IRuntime::CreationOptions options; + options.m_EnableGpuProfiling = backends.front() == armnn::Compute::GpuAcc; + IRuntimePtr runtime(IRuntime::Create(options)); + + // build up the structure of the network + INetworkPtr net(INetwork::Create()); + + IConnectableLayer* input = net->AddInputLayer(0, "input"); + IConnectableLayer* softmax = net->AddSoftmaxLayer(SoftmaxDescriptor(), "softmax"); + IConnectableLayer* output = net->AddOutputLayer(0, "output"); + + input->GetOutputSlot(0).Connect(softmax->GetInputSlot(0)); + softmax->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + // set the tensors in the network + TensorInfo inputTensorInfo(TensorShape({1, 5}), DataType::QuantisedAsymm8); + inputTensorInfo.SetQuantizationOffset(100); + inputTensorInfo.SetQuantizationScale(10000.0f); + input->GetOutputSlot(0).SetTensorInfo(inputTensorInfo); + + TensorInfo outputTensorInfo(TensorShape({1, 5}), DataType::QuantisedAsymm8); + outputTensorInfo.SetQuantizationOffset(0); + outputTensorInfo.SetQuantizationScale(1.0f / 256.0f); + softmax->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + // optimize the network + IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec()); + if(!optNet) + { + BOOST_FAIL("Error occurred during Optimization, Optimize() returned nullptr."); + } + // load it into the runtime + NetworkId netId; + auto error = runtime->LoadNetwork(netId, std::move(optNet)); + BOOST_TEST(error == Status::Success); + + // create structures for input & output + std::vector<uint8_t> inputData + { + 1, 10, 3, 200, 5 + // one of inputs is sufficiently larger than the others to saturate softmax + }; + std::vector<uint8_t> outputData(5); + + armnn::InputTensors inputTensors + { + {0, armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())} + }; + armnn::OutputTensors outputTensors + { + {0, armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())} + }; + + runtime->GetProfiler(netId)->EnableProfiling(true); + + // do the inferences + runtime->EnqueueWorkload(netId, inputTensors, outputTensors); + runtime->EnqueueWorkload(netId, inputTensors, outputTensors); + runtime->EnqueueWorkload(netId, inputTensors, outputTensors); + + // retrieve the Profiler.Print() output + std::stringstream ss; + profilerManager.GetProfiler()->Print(ss); + + return ss.str(); +} + +inline void SoftmaxProfilerTestValidationHelper(std::string& result, const std::string& testData) +{ + // ensure all measurements are greater than zero + std::vector<double> measurementsVector = ExtractMeasurements(result); + BOOST_CHECK(!measurementsVector.empty()); + + // check sections contain raw and unit tags + // first ensure Parenthesis are balanced + if (AreParenthesesMatching(result)) + { + // remove parent sections that will not have raw or unit tag + std::vector<std::string> sectionVector = ExtractSections(result); + for (size_t i = 0; i < sectionVector.size(); ++i) + { + if (boost::contains(sectionVector[i], "\"ArmNN\":") + || boost::contains(sectionVector[i], "\"inference_measurements\":")) + { + sectionVector.erase(sectionVector.begin() + static_cast<int>(i)); + } + } + BOOST_CHECK(!sectionVector.empty()); + + BOOST_CHECK(std::all_of(sectionVector.begin(), sectionVector.end(), + [](std::string i) { return boost::contains(i, "\"raw\":"); })); + + BOOST_CHECK(std::all_of(sectionVector.begin(), sectionVector.end(), + [](std::string i) { return boost::contains(i, "\"unit\":"); })); + } + + // remove the time measurements as they vary from test to test + result.erase(std::remove_if (result.begin(),result.end(), + [](char c) { return c == '.'; }), result.end()); + result.erase(std::remove_if (result.begin(), result.end(), &isdigit), result.end()); + result.erase(std::remove_if (result.begin(),result.end(), + [](char c) { return c == '\t'; }), result.end()); + + BOOST_CHECK(boost::contains(result, "ArmNN")); + BOOST_CHECK(boost::contains(result, "inference_measurements")); + BOOST_CHECK(boost::contains(result, "layer_measurements")); + BOOST_CHECK_EQUAL(result, testData); + + // ensure no spare parenthesis present in print output + BOOST_CHECK(AreParenthesesMatching(result)); +} + +inline void SetupSoftmaxProfilerWithSpecifiedBackendsAndValidateJsonPrinterResult( + const std::vector<armnn::BackendId>& backends) +{ + // setup the test fixture and obtain JSON Printer result + std::string result = SoftmaxProfilerTestSetupHelper(backends); + + std::string backend = "Ref"; + std::string changeLine31 = "\n},\n\"CopyMemGeneric_Execute\": {"; + std::string changeLine39 = "us\""; + std::string changeLine40; + std::string changeLine45; + + if (backends[0] == armnn::Compute::GpuAcc) { + backend = "Cl"; + changeLine31 = ",\n\"OpenClKernelTimer/: softmax_layer_max_shift_exp_sum_quantized_serial GWS[,,]\": {"; + changeLine39 = R"(us" +}, +"OpenClKernelTimer/: softmax_layer_norm_quantized GWS[,,]": { +"raw": [ +, +, + +], +"unit": "us")"; + + changeLine40 = R"( +}, +"CopyMemGeneric_Execute": { +"raw": [ +, +, + +], +"unit": "us")"; + changeLine45 = "}\n"; + } + else if (backends[0] == armnn::Compute::CpuAcc) + { + backend = "Neon"; + changeLine31 = ",\n\"NeonKernelTimer/: NEFillBorderKernel\": {"; + changeLine39 = R"(us" +}, +"NeonKernelTimer/: NELogitsDMaxKernel": { +"raw": [ +, +, + +], +"unit": "us" +}, +"NeonKernelTimer/: NELogitsDSoftmaxKernel": { +"raw": [ +, +, + +], +"unit": "us")"; + changeLine40 = R"( +}, +"CopyMemGeneric_Execute": { +"raw": [ +, +, + +], +"unit": "us")"; + changeLine45 = "}\n"; + } + + std::string testData = R"({ +"ArmNN": { +"inference_measurements": { +"raw": [ +, +, + +], +"unit": "us", +"layer_measurements": { +"raw": [ +, +, + +], +"unit": "us", +"CopyMemGeneric_Execute": { +"raw": [ +, +, + +], +"unit": "us" +}, +")" + backend + R"(SoftmaxUintWorkload_Execute": { +"raw": [ +, +, + +], +"unit": "us")" + changeLine31 + R"( +"raw": [ +, +, + +], +"unit": ")" + changeLine39 + R"( +})" + changeLine40 + R"( +} +} +} +} +)" + changeLine45 + R"()"; + + // validate the JSON Printer result + SoftmaxProfilerTestValidationHelper(result, testData); +} |