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Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp')
-rw-r--r--src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp114
1 files changed, 101 insertions, 13 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 74c65e271c..1e0adc169a 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -309,6 +309,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
@@ -329,8 +330,15 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
}
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
+ if (biasEnabled)
+ {
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
+ }
data.m_Weight = &weightsTensor;
data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - can be a source of bugs.
data.m_Parameters.m_StrideX = strideX;
@@ -349,8 +357,16 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
info);
inputHandle->Allocate();
outputHandle->Allocate();
+ weightsHandle->Allocate();
+
+ if (biasEnabled)
+ {
+ biasHandle->Allocate();
+ CopyDataToITensorHandle(biasHandle.get(), bias.data());
+ }
CopyDataToITensorHandle(inputHandle.get(), inputData.data());
+ CopyDataToITensorHandle(weightsHandle.get(), kernel.data());
ExecuteWorkload(*workload, memoryManager);
@@ -423,6 +439,8 @@ LayerTestResult<O, 4> SimpleConvolution2dNhwcTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
armnn::ScopedTensorHandle weightsTensor(kernelDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data());
@@ -444,15 +462,30 @@ LayerTestResult<O, 4> SimpleConvolution2dNhwcTestImpl(
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ if (biasEnabled)
+ {
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
+ }
+
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d,
data,
info);
inputHandle->Allocate();
outputHandle->Allocate();
+ weightsHandle->Allocate();
+
+ if (biasEnabled)
+ {
+ biasHandle->Allocate();
+ CopyDataToITensorHandle(biasHandle.get(), bias.data());
+ }
CopyDataToITensorHandle(inputHandle.get(), inputData.data());
+ CopyDataToITensorHandle(weightsHandle.get(), kernel.data());
ExecuteWorkload(*workload, memoryManager);
@@ -552,35 +585,52 @@ LayerTestResult<T,4> Convolution1dTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedTensorHandle weightsTensor(kernelInfo);
- armnn::ScopedTensorHandle biasTensor(biasInfo);
+ armnn::ScopedTensorHandle weightsTensor(kernelInfo);
+ armnn::ScopedTensorHandle biasTensor(biasInfo);
AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());
AddInputToWorkload(data, info, inputInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelInfo, weightsHandle.get());
AddOutputToWorkload(data, info, outputInfo, outputHandle.get());
- data.m_Weight = &weightsTensor;
- data.m_Bias = &biasTensor;
- data.m_Parameters.m_StrideX = 1;
- data.m_Parameters.m_StrideY = stride;
- data.m_Parameters.m_PadLeft = 0;
- data.m_Parameters.m_PadRight = 0;
- data.m_Parameters.m_PadTop = padSize;
- data.m_Parameters.m_PadBottom = padSize;
- data.m_Parameters.m_BiasEnabled = biasEnabled;
+ data.m_Weight = &weightsTensor;
+ data.m_Bias = &biasTensor;
+ data.m_Parameters.m_StrideX = 1;
+ data.m_Parameters.m_StrideY = stride;
+ data.m_Parameters.m_PadLeft = 0;
+ data.m_Parameters.m_PadRight = 0;
+ data.m_Parameters.m_PadTop = padSize;
+ data.m_Parameters.m_PadBottom = padSize;
+ data.m_Parameters.m_BiasEnabled = biasEnabled;
+
+ if (biasEnabled)
+ {
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo);
+ AddInputToWorkload(data, info, biasInfo, biasHandle.get());
+ }
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d,
data,
info);
inputHandle->Allocate();
outputHandle->Allocate();
+ weightsHandle->Allocate();
+
+ if (biasEnabled)
+ {
+ biasHandle->Allocate();
+ CopyDataToITensorHandle(biasHandle.get(), biasData.data());
+ }
CopyDataToITensorHandle(inputHandle.get(), inputData.data());
+ CopyDataToITensorHandle(weightsHandle.get(), kernelData.data());
ExecuteWorkload(*workload, memoryManager);
@@ -1364,18 +1414,30 @@ LayerTestResult<T,4> CompareConvolution2dTestImpl(
std::vector<T> expectedOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
+
armnn::ScopedTensorHandle weightsTensor(kernelDesc);
armnn::ScopedTensorHandle biasTensor(biasDesc);
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+ // AllocateAndCopyDataToITensorHandle() is required twice for the weights AND biases:
+ // See comment in DepthwiseConvolution2dAsymmetricTestImpl() for reasons.
+ // 1) ScopedTensorHandle (weightsTensor) required for QueueDescriptor (data.m_Weight).
+ // 2) ITensorHandle (converts to Backend TensorHandle) required in RefWorkload for GetTensorInfo() method.
+ AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernel.data());
AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data());
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data());
- AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
data.m_Weight = &weightsTensor;
data.m_Bias = &biasTensor;
data.m_Parameters.m_StrideX = strideX;
@@ -1387,11 +1449,15 @@ LayerTestResult<T,4> CompareConvolution2dTestImpl(
data.m_Parameters.m_BiasEnabled = true;
std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandleRef = refTensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandleRef = refTensorHandleFactory.CreateTensorHandle(biasDesc);
std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo);
armnn::Convolution2dQueueDescriptor refData = data;
armnn::WorkloadInfo refInfo = info;
SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());
+ SetWorkloadInput(refData, refInfo, 1, kernelDesc, weightsHandleRef.get());
+ SetWorkloadInput(refData, refInfo, 2, biasDesc, biasHandleRef.get());
SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());
std::unique_ptr<armnn::IWorkload> workload
@@ -1401,12 +1467,16 @@ LayerTestResult<T,4> CompareConvolution2dTestImpl(
outputHandleRef->Allocate();
inputHandleRef->Allocate();
+ weightsHandleRef->Allocate();
+ biasHandleRef->Allocate();
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.data());
CopyDataToITensorHandle(inputHandleRef.get(), input.data());
+ CopyDataToITensorHandle(weightsHandleRef.get(), kernel.data());
+ CopyDataToITensorHandle(biasHandleRef.get(), bias.data());
ExecuteWorkload(*workload, memoryManager);
@@ -3622,6 +3692,8 @@ LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest(
std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo);
std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
WorkloadInfo workloadInfo;
ScopedTensorHandle weightTensor(kernelInfo);
@@ -3636,6 +3708,14 @@ LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest(
queueDescriptor.m_Bias = &biasTensor;
AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());
+ AddInputToWorkload(queueDescriptor, workloadInfo, kernelInfo, weightsHandle.get());
+
+ if (descriptor.m_BiasEnabled)
+ {
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo);
+ AddInputToWorkload(queueDescriptor, workloadInfo, biasInfo, biasHandle.get());
+ }
+
AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());
std::unique_ptr<IWorkload> workload= workloadFactory.CreateWorkload(armnn::LayerType::Convolution2d,
@@ -3643,8 +3723,16 @@ LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest(
workloadInfo);
inputHandle->Allocate();
outputHandle->Allocate();
+ weightsHandle->Allocate();
+ if (descriptor.m_BiasEnabled)
+ {
+ biasHandle->Allocate();
+ CopyDataToITensorHandle(biasHandle.get(), biasData.data());
+ }
CopyDataToITensorHandle(inputHandle.get(), inputData.data());
+ CopyDataToITensorHandle(weightsHandle.get(), kernelData.data());
+
ExecuteWorkload(*workload, memoryManager);
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-16 17:19:53 +0000