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//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "FullyConnectedTestHelper.hpp"
namespace
{
TEST_SUITE("FullyConnectedTest")
{
void FullyConnectedFp32Test(std::vector<armnn::BackendId>& backends)
{
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>(backends,
::tflite::TensorType_FLOAT32,
tflite::ActivationFunctionType_NONE,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData);
}
void FullyConnectedActicationTest(std::vector<armnn::BackendId>& backends)
{
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>(backends,
::tflite::TensorType_FLOAT32,
tflite::ActivationFunctionType_RELU,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData);
}
void FullyConnectedUint8Test(std::vector<armnn::BackendId>& backends)
{
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<uint8_t> inputValues = { 1, 2, 3, 4, 10, 20, 30, 40 };
std::vector<uint8_t> weightsData = { 2, 3, 4, 5 };
std::vector<uint8_t> expectedOutputValues = { (40 + 10) / 2, (400 + 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<uint8_t>(backends,
::tflite::TensorType_UINT8,
tflite::ActivationFunctionType_NONE,
inputTensorShape,
weightsTensorShape,
biasTensorShape,
outputTensorShape,
inputValues,
expectedOutputValues,
weightsData);
}
TEST_CASE ("FULLY_CONNECTED_FP32_GpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc,
armnn::Compute::CpuRef };
FullyConnectedFp32Test(backends);
}
TEST_CASE ("FULLY_CONNECTED_FP32_CpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc,
armnn::Compute::CpuRef };
FullyConnectedFp32Test(backends);
}
TEST_CASE ("FULLY_CONNECTED_UINT8_GpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc,
armnn::Compute::CpuRef };
FullyConnectedUint8Test(backends);
}
TEST_CASE ("FULLY_CONNECTED_UINT8_CpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc,
armnn::Compute::CpuRef };
FullyConnectedUint8Test(backends);
}
TEST_CASE ("FULLY_CONNECTED_Activation_GpuAcc_Test")
{
std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc,
armnn::Compute::CpuRef };
FullyConnectedActicationTest(backends);
}
} // End of TEST_SUITE("FullyConnectedTest")
} // anonymous namespace
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