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Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp')
-rw-r--r--src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp130
1 files changed, 63 insertions, 67 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
index cd7f4efe31..c47048e566 100644
--- a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
@@ -29,9 +29,9 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
armnn::TensorInfo outputTensorInfo,
armnn::TensorInfo weightsDesc,
armnn::TensorInfo biasesDesc,
- boost::multi_array<T, 2>& weights,
- boost::multi_array<B, 1>& bias,
- boost::multi_array<T, 4>& input,
+ std::vector<T>& weights,
+ std::vector<B>& bias,
+ std::vector<T>& input,
bool biasEnabled,
bool transposeWeights)
{
@@ -43,8 +43,10 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
armnn::ScopedTensorHandle weightsTensor(weightsDesc);
armnn::ScopedTensorHandle biasTensor(biasesDesc);
- AllocateAndCopyDataToITensorHandle(&weightsTensor, &weights[0][0]);
- AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
+ std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
+
+ AllocateAndCopyDataToITensorHandle(&weightsTensor, weights.data());
+ AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data());
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
@@ -58,11 +60,12 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
inputHandle->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+ CopyDataToITensorHandle(inputHandle.get(), input.data());
ExecuteWorkload(*workload, memoryManager);
- CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
+ result.m_ActualData = actualOutput;
return result;
}
@@ -76,9 +79,9 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestWeightsAsInputsImpl(
armnn::TensorInfo outputTensorInfo,
armnn::TensorInfo weightsTensorInfo,
armnn::TensorInfo biasesTensorInfo,
- boost::multi_array<T, 2>& weights,
- boost::multi_array<B, 1>& bias,
- boost::multi_array<T, 4>& input,
+ std::vector<T>& weights,
+ std::vector<B>& bias,
+ std::vector<T>& input,
bool biasEnabled,
bool transposeWeights)
{
@@ -86,6 +89,8 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestWeightsAsInputsImpl(
std::unique_ptr<armnn::ITensorHandle> input1Handle = tensorHandleFactory.CreateTensorHandle(weightsTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
+
armnn::FullyConnectedQueueDescriptor data;
armnn::WorkloadInfo info;
@@ -109,17 +114,18 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestWeightsAsInputsImpl(
input0Handle->Allocate();
input1Handle->Allocate();
outputHandle->Allocate();
- CopyDataToITensorHandle(input0Handle.get(), &input[0][0][0][0]);
- CopyDataToITensorHandle(input1Handle.get(), &weights[0][0]);
+ CopyDataToITensorHandle(input0Handle.get(), input.data());
+ CopyDataToITensorHandle(input1Handle.get(), weights.data());
if (biasEnabled)
{
input2Handle->Allocate();
- CopyDataToITensorHandle(input2Handle.get(), &bias[0]);
+ CopyDataToITensorHandle(input2Handle.get(), bias.data());
}
ExecuteWorkload(*workload, memoryManager);
- CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+ CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
+ result.m_ActualData = actualOutput;
return result;
}
@@ -158,21 +164,21 @@ LayerTestResult<T, 2> FullyConnectedTest(
LayerTestResult<T, 2> result(outputTensorInfo);
- auto input = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(
+ std::vector<T> input = ConvertToDataType<ArmnnType>(
{
-1.2f, 6.1f, -3.5f,
18.8f, -5.5f, 2.9f
},
- inputTensorInfo));
+ inputTensorInfo);
- auto weights = MakeTensor<T, 2>(weightsDesc, ConvertToDataType<ArmnnType>(
+ std::vector<T> weights = ConvertToDataType<ArmnnType>(
{
-8.4f, 20.0f, -10.4f, -8, 16.4f, -11.8f,
23.4f, 10.4f, -14.0f, -3.8f, -11.8f, 11.4f
},
- weightsDesc));
+ weightsDesc);
- auto bias = MakeTensor<int32_t, 1>(biasesDesc, std::vector<int32_t>{9250, 67500});
+ std::vector<int32_t> bias = {9250, 67500};
if (constantWeights)
{
@@ -207,13 +213,11 @@ LayerTestResult<T, 2> FullyConnectedTest(
if (biasEnabled)
{
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
- ConvertToDataType<ArmnnType>({80.f, 1460.f}, outputTensorInfo));
+ result.m_ExpectedData = ConvertToDataType<ArmnnType>({80.f, 1460.f}, outputTensorInfo);
}
else
{
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
- ConvertToDataType<ArmnnType>({-107.04f, 110.f}, outputTensorInfo));
+ result.m_ExpectedData = ConvertToDataType<ArmnnType>({-107.04f, 110.f}, outputTensorInfo);
}
return result;
@@ -274,22 +278,19 @@ LayerTestResult<T, 2> FullyConnectedLargeTestCommon(
LayerTestResult<T, 2> result(outputTensorInfo);
- boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputTensorInfo,
- armnnUtils::QuantizedVector<T>({
+ std::vector<T> input = armnnUtils::QuantizedVector<T>(
+ {
1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f,
},
- qScale, qOffset)
- );
+ qScale, qOffset);
- boost::multi_array<T, 2> weights = MakeTensor<T, 2>(weightsDesc,
- armnnUtils::QuantizedVector<T>({
+ std::vector<T> weights = armnnUtils::QuantizedVector<T>(
+ {
2.0f, 3.0f, 4.0f, 5.0f, 6.0f
},
- qScale, qOffset)
- );
+ qScale, qOffset);
std::vector<T> biasValues({900000.f});
- boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasesDesc, biasValues);
result = SimpleFullyConnectedTestImpl<T>(
workloadFactory,
@@ -297,12 +298,11 @@ LayerTestResult<T, 2> FullyConnectedLargeTestCommon(
tensorHandleFactory,
inputTensorInfo, outputTensorInfo,
weightsDesc, biasesDesc,
- weights, bias, input,
+ weights, biasValues, input,
true, transposeWeights
);
- result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
- armnnUtils::QuantizedVector<T>({ 965432.0f }, qScale, qOffset));
+ result.m_ExpectedData = armnnUtils::QuantizedVector<T>({ 965432.0f }, qScale, qOffset);
return result;
}
@@ -370,40 +370,36 @@ LayerTestResult<float, 2> FullyConnectedFloat32Test(
LayerTestResult<float, 2> result(outputTensorInfo);
- boost::multi_array<float, 4> input = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(
- {
- 1.0f, 2.0f, 3.0f, 4.0f, 5.0f,
-
- 5.0f, 4.0f, 3.0f, 2.0f, 1.0f
- })
- );
+ std::vector<float> input =
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f,
+ 5.0f, 4.0f, 3.0f, 2.0f, 1.0f
+ };
- boost::multi_array<float, 2> weights = MakeTensor<float, 2>(weightsDesc, std::vector<float>(
- {
- .5f, 2.f, .5f,
- .5f, 2.f, 1.f,
- .5f, 2.f, 2.f,
- .5f, 2.f, 3.f,
- .5f, 2.f, 4.f
- }));
+ std::vector<float> weights =
+ {
+ .5f, 2.f, .5f,
+ .5f, 2.f, 1.f,
+ .5f, 2.f, 2.f,
+ .5f, 2.f, 3.f,
+ .5f, 2.f, 4.f
+ };
if (transposeWeights)
{
- weights = MakeTensor<float, 2>(weightsDesc, std::vector<float>(
+ weights =
{
.5f, .5f, .5f, .5f, .5f,
2.f, 2.f, 2.f, 2.f, 2.f,
.5f, 1.f, 2.f, 3.f, 4.f
- }));
+ };
}
-
std::vector<float> biasValues({0.f, 0.f, 0.f});
if (biasEnabled)
{
- biasValues = std::vector<float>({10.f, 20.f, 30.f});
+ biasValues = std::vector<float>({10.f, 20.f, 30.f});
}
- boost::multi_array<float, 1> bias = MakeTensor<float, 1>(biasesDesc, biasValues);
result = SimpleFullyConnectedTestImpl<float>(
workloadFactory,
@@ -411,21 +407,21 @@ LayerTestResult<float, 2> FullyConnectedFloat32Test(
tensorHandleFactory,
inputTensorInfo, outputTensorInfo,
weightsDesc, biasesDesc,
- weights, bias, input,
+ weights, biasValues, input,
biasEnabled, transposeWeights
);
- result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>(
- {
- 0.5f + 1.0f + 1.5f + 2.0f + 2.5f + biasValues[0],
- 2.0f + 4.0f + 6.0f + 8.0f + 10.f + biasValues[1],
- 0.5f + 2.0f + 6.0f + 12.f + 20.f + biasValues[2],
-
- 2.5f + 2.0f + 1.5f + 1.0f + 0.5f + biasValues[0],
- 10.0f + 8.0f + 6.0f + 4.0f + 2.f + biasValues[1],
- 2.5f + 4.0f + 6.0f + 6.f + 4.f + biasValues[2]
- })
- );
+ std::vector<float> expectedOutput =
+ {
+ 0.5f + 1.0f + 1.5f + 2.0f + 2.5f + biasValues[0],
+ 2.0f + 4.0f + 6.0f + 8.0f + 10.f + biasValues[1],
+ 0.5f + 2.0f + 6.0f + 12.f + 20.f + biasValues[2],
+
+ 2.5f + 2.0f + 1.5f + 1.0f + 0.5f + biasValues[0],
+ 10.0f + 8.0f + 6.0f + 4.0f + 2.f + biasValues[1],
+ 2.5f + 4.0f + 6.0f + 6.f + 4.f + biasValues[2]
+ };
+ result.m_ExpectedData = expectedOutput;
return result;
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-07 17:45:34 +0000