diff options
Diffstat (limited to 'delegate/src/test/FullyConnectedTestHelper.hpp')
| -rw-r--r-- | delegate/src/test/FullyConnectedTestHelper.hpp | 101 |
1 files changed, 61 insertions, 40 deletions
diff --git a/delegate/src/test/FullyConnectedTestHelper.hpp b/delegate/src/test/FullyConnectedTestHelper.hpp index 1b6ca941b8..37062c3400 100644 --- a/delegate/src/test/FullyConnectedTestHelper.hpp +++ b/delegate/src/test/FullyConnectedTestHelper.hpp @@ -5,6 +5,8 @@ #pragma once +#include "TestUtils.hpp" + #include <armnn_delegate.hpp> #include <flatbuffers/flatbuffers.h> @@ -25,8 +27,9 @@ std::vector<char> CreateFullyConnectedTfLiteModel(tflite::TensorType tensorType, const std::vector <int32_t>& inputTensorShape, const std::vector <int32_t>& weightsTensorShape, const std::vector <int32_t>& biasTensorShape, - const std::vector <int32_t>& outputTensorShape, - const std::vector <T>& weightsData, + std::vector <int32_t>& outputTensorShape, + std::vector <T>& weightsData, + bool constantWeights = true, float quantScale = 1.0f, int quantOffset = 0, float outputQuantScale = 2.0f, @@ -36,26 +39,38 @@ std::vector<char> CreateFullyConnectedTfLiteModel(tflite::TensorType tensorType, flatbuffers::FlatBufferBuilder flatBufferBuilder; std::array<flatbuffers::Offset<tflite::Buffer>, 3> buffers; buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); - buffers[1] = CreateBuffer(flatBufferBuilder, - flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(weightsData.data()), - sizeof(T) * weightsData.size())); auto biasTensorType = ::tflite::TensorType_FLOAT32; if (tensorType == ::tflite::TensorType_INT8) { biasTensorType = ::tflite::TensorType_INT32; - std::vector<int32_t> biasData = { 10 }; - buffers[2] = CreateBuffer(flatBufferBuilder, - flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), - sizeof(int32_t) * biasData.size())); + } + if (constantWeights) + { + buffers[1] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(weightsData.data()), + sizeof(T) * weightsData.size())); + if (tensorType == ::tflite::TensorType_INT8) + { + std::vector<int32_t> biasData = { 10 }; + buffers[2] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), + sizeof(int32_t) * biasData.size())); + + } + else + { + std::vector<float> biasData = { 10 }; + buffers[2] = CreateBuffer(flatBufferBuilder, + flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), + sizeof(float) * biasData.size())); + } } else { - std::vector<float> biasData = { 10 }; - buffers[2] = CreateBuffer(flatBufferBuilder, - flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), - sizeof(float) * biasData.size())); + buffers[1] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); + buffers[2] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({})); } auto quantizationParameters = @@ -155,10 +170,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends, const std::vector <int32_t>& inputTensorShape, const std::vector <int32_t>& weightsTensorShape, const std::vector <int32_t>& biasTensorShape, - const std::vector <int32_t>& outputTensorShape, - const std::vector <T>& inputValues, - const std::vector <T>& expectedOutputValues, - const std::vector <T>& weightsData, + std::vector <int32_t>& outputTensorShape, + std::vector <T>& inputValues, + std::vector <T>& expectedOutputValues, + std::vector <T>& weightsData, + bool constantWeights = true, float quantScale = 1.0f, int quantOffset = 0) { @@ -171,10 +187,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends, biasTensorShape, outputTensorShape, weightsData, + constantWeights, quantScale, quantOffset); - const Model* tfLiteModel = GetModel(modelBuffer.data()); + // Create TfLite Interpreters std::unique_ptr<Interpreter> armnnDelegateInterpreter; CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) @@ -191,25 +208,34 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends, // Create the ArmNN Delegate armnnDelegate::DelegateOptions delegateOptions(backends); std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> - theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), - armnnDelegate::TfLiteArmnnDelegateDelete); + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); CHECK(theArmnnDelegate != nullptr); + // Modify armnnDelegateInterpreter to use armnnDelegate CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); // Set input data - auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0]; - auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) - { - tfLiteDelageInputData[i] = inputValues[i]; - } + armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, inputValues); + armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, inputValues); - auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0]; - auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInputId); - for (unsigned int i = 0; i < inputValues.size(); ++i) + if (!constantWeights) { - armnnDelegateInputData[i] = inputValues[i]; + armnnDelegate::FillInput<T>(tfLiteInterpreter, 1, weightsData); + armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 1, weightsData); + + if (tensorType == ::tflite::TensorType_INT8) + { + std::vector <int32_t> biasData = {10}; + armnnDelegate::FillInput<int32_t>(tfLiteInterpreter, 2, biasData); + armnnDelegate::FillInput<int32_t>(armnnDelegateInterpreter, 2, biasData); + } + else + { + std::vector<float> biasData = {10}; + armnnDelegate::FillInput<float>(tfLiteInterpreter, 2, biasData); + armnnDelegate::FillInput<float>(armnnDelegateInterpreter, 2, biasData); + } } // Run EnqueWorkload @@ -217,16 +243,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends, CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); // Compare output data - auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; - auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId); - auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; - auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId); - for (size_t i = 0; i < expectedOutputValues.size(); i++) - { - CHECK(expectedOutputValues[i] == tfLiteDelageOutputData[i]); - CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]); - CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]); - } + armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, + armnnDelegateInterpreter, + outputTensorShape, + expectedOutputValues); + armnnDelegateInterpreter.reset(nullptr); } } // anonymous namespace
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