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//
// Copyright © 2020-2021,2023-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "FullyConnectedTestHelper.hpp"
#include <doctest/doctest.h>
namespace
{
void FullyConnectedFp32Test(const std::vector<armnn::BackendId>& backends = {}, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 1, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
std::vector<int32_t> biasTensorShape { 1 };
std::vector<int32_t> outputTensorShape { 1, 1 };
std::vector<float> inputValues = { 10, 20, 30, 40 };
std::vector<float> weightsData = { 2, 3, 4, 5 };
std::vector<float> expectedOutputValues = { (400 + 10) };
// bias is set std::vector<float> biasData = { 10 } in the model
FullyConnectedTest<float>(::tflite::TensorType_FLOAT32,
tflite::ActivationFunctionType_NONE,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData,
backends,
constantWeights);
}
void FullyConnectedActivationTest(const std::vector<armnn::BackendId>& backends = {}, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 1, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
std::vector<int32_t> biasTensorShape { 1 };
std::vector<int32_t> outputTensorShape { 1, 1 };
std::vector<float> inputValues = { -10, 20, 30, 40 };
std::vector<float> weightsData = { 2, 3, 4, -5 };
std::vector<float> expectedOutputValues = { 0 };
// bias is set std::vector<float> biasData = { 10 } in the model
FullyConnectedTest<float>(::tflite::TensorType_FLOAT32,
tflite::ActivationFunctionType_RELU,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData,
backends,
constantWeights);
}
void FullyConnectedInt8Test(const std::vector<armnn::BackendId>& backends = {}, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 2, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
std::vector<int32_t> biasTensorShape { 1 };
std::vector<int32_t> outputTensorShape { 2, 1 };
std::vector<int8_t> inputValues = { 1, 2, 3, 4, 5, 10, 15, 20 };
std::vector<int8_t> weightsData = { 2, 3, 4, 5 };
std::vector<int8_t> expectedOutputValues = { 25, 105 }; // (40 + 10) / 2, (200 + 10) / 2
// bias is set std::vector<int32_t> biasData = { 10 } in the model
// input and weights quantization scale 1.0f and offset 0 in the model
// output quantization scale 2.0f and offset 0 in the model
FullyConnectedTest<int8_t>(::tflite::TensorType_INT8,
tflite::ActivationFunctionType_NONE,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData,
backends,
constantWeights);
}
TEST_SUITE("FullyConnectedTests")
{
TEST_CASE ("FullyConnected_FP32_Test")
{
FullyConnectedFp32Test();
}
TEST_CASE ("FullyConnected_Int8_Test")
{
FullyConnectedInt8Test();
}
TEST_CASE ("FullyConnected_Activation_Test")
{
FullyConnectedActivationTest();
}
TEST_CASE ("FullyConnected_Weights_As_Inputs_FP32_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
FullyConnectedFp32Test(backends, false);
}
TEST_CASE ("FullyConnected_Weights_As_Inputs_Int8_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
FullyConnectedInt8Test(backends, false);
}
TEST_CASE ("FullyConnected_Weights_As_Inputs_Activation_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
FullyConnectedActivationTest(backends, false);
}
} // End of TEST_SUITE("FullyConnectedTests")
} // anonymous namespace
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