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Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp')
-rw-r--r--src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp143
1 files changed, 118 insertions, 25 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index bd7cc40f27..4203fed23a 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -1736,19 +1736,38 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
}
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ armnn::DepthwiseConvolution2dQueueDescriptor data;
+ armnn::WorkloadInfo info;
+
armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ // AllocateAndCopyDataToITensorHandle() is required twice for the weights AND biases:
+ // 1) ScopedTensorHandle (weightsTensor) required for QueueDescriptor (data.m_Weight).
+ // Needed in Neon and Cl Workload when permuting. Backend TensorHandle in (2) below will not work.
+ // 2) ITensorHandle (converts to Backend TensorHandle) required in RefWorkload for GetTensorInfo() method.
+ // Cannot PolymorphicDowncast from ScopedTensorHandle->RefTensorHandle.
+ // Need to PolymorphicDowncast from ITensorHandle->RefTensorHandle.
AllocateAndCopyDataToITensorHandle(&weightsTensor, kernel.data());
+ AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernel.data()); // required for ConstantTensor
+
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
armnn::ScopedTensorHandle biasTensor(biasDesc);
if (biasEnabled)
{
AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data());
+
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data());
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
}
- armnn::DepthwiseConvolution2dQueueDescriptor data;
data.m_Weight = &weightsTensor;
data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled - it can be a source of bugs.
data.m_Parameters.m_StrideX = strideX;
@@ -1760,12 +1779,9 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
data.m_Parameters.m_BiasEnabled = biasEnabled;
data.m_Parameters.m_DataLayout = layout;
- armnn::WorkloadInfo info;
- AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
std::unique_ptr<armnn::IWorkload> workload
= workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info);
+
inputHandle->Allocate();
outputHandle->Allocate();
@@ -1890,19 +1906,35 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedTensorHandle biasTensor(biasDesc);
- AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data());
- AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data());
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ // 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(&weightsTensor, kernelData.data()); // required for QueueDescriptor
+ AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
+ if (biasEnabled)
+ {
+ AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data());
+
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasV.data());
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
+ }
+
data.m_Weight = &weightsTensor;
data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled.
data.m_Parameters.m_StrideX = 1;
@@ -1916,6 +1948,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
std::unique_ptr<armnn::IWorkload> workload
= workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info);
+
inputHandle->Allocate();
outputHandle->Allocate();
@@ -2086,19 +2119,35 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedTensorHandle biasTensor(biasDesc);
- AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data());
- AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data());
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ // 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(&weightsTensor, kernelData.data()); // required for QueueDescriptor
+ AllocateAndCopyDataToITensorHandle(weightsHandle.get(), kernelData.data()); // required for ConstantTensor
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
+ if (biasEnabled)
+ {
+ AllocateAndCopyDataToITensorHandle(&biasTensor, biasV.data());
+
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasV.data());
+ AddInputToWorkload(data, info, biasDesc, biasHandle.get());
+ }
+
data.m_Weight = &weightsTensor;
data.m_Bias = &biasTensor; // Still set this whether or not bias is enabled.
data.m_Parameters.m_StrideX = 2;
@@ -2112,6 +2161,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
std::unique_ptr<armnn::IWorkload> workload
= workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info);
+
inputHandle->Allocate();
outputHandle->Allocate();
@@ -2247,22 +2297,34 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
}
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = nullptr;
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
+
armnn::ScopedTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedTensorHandle biasTensor(biasDesc);
+ // 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(&weightsTensor, originalKernel.data()); // required for QueueDescriptor
+ AllocateAndCopyDataToITensorHandle(weightsHandle.get(), originalKernel.data()); // required for ConstantTensor
- AllocateAndCopyDataToITensorHandle(&weightsTensor, originalKernel.data());
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddInputToWorkload(data, info, kernelDesc, weightsHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
- if(biasEnabled)
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
+ if (biasEnabled)
{
AllocateAndCopyDataToITensorHandle(&biasTensor, bias.data());
- }
- AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), bias.data());
+ 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.
@@ -2279,6 +2341,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
std::unique_ptr<armnn::IWorkload> workload
= workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, data, info);
+
inputHandle->Allocate();
outputHandle->Allocate();
@@ -2970,18 +3033,30 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl(
std::vector<T> expectedOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelDesc);
+ std::unique_ptr<armnn::ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasDesc);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
armnn::DepthwiseConvolution2dQueueDescriptor 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;
@@ -2994,11 +3069,15 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl(
data.m_Parameters.m_DataLayout = layout.GetDataLayout();
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::DepthwiseConvolution2dQueueDescriptor 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
@@ -3007,6 +3086,8 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl(
= refWorkloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d, refData, refInfo);
outputHandleRef->Allocate();
+ weightsHandleRef->Allocate();
+ biasHandleRef->Allocate();
inputHandleRef->Allocate();
inputHandle->Allocate();
@@ -3014,6 +3095,8 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl(
CopyDataToITensorHandle(inputHandle.get(), input.data());
CopyDataToITensorHandle(inputHandleRef.get(), input.data());
+ CopyDataToITensorHandle(weightsHandleRef.get(), kernel.data());
+ CopyDataToITensorHandle(biasHandleRef.get(), bias.data());
ExecuteWorkload(*workload, memoryManager);
@@ -3739,23 +3822,33 @@ LayerTestResult<uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest(
descriptor.m_DataLayout = layout;
std::unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo);
+ std::unique_ptr<ITensorHandle> weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo);
+ std::unique_ptr<ITensorHandle> biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo);
std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);
+ DepthwiseConvolution2dQueueDescriptor queueDescriptor;
WorkloadInfo workloadInfo;
ScopedTensorHandle weightTensor(kernelInfo);
ScopedTensorHandle biasTensor(biasInfo);
+ AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());
+ AddInputToWorkload(queueDescriptor, workloadInfo, kernelInfo, weightsHandle.get());
+ AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());
+ AddInputToWorkload(queueDescriptor, workloadInfo, biasInfo, biasHandle.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(), kernelData.data());
AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data());
+ AllocateAndCopyDataToITensorHandle(biasHandle.get(), biasData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());
- DepthwiseConvolution2dQueueDescriptor queueDescriptor;
queueDescriptor.m_Parameters = descriptor;
queueDescriptor.m_Weight = &weightTensor;
queueDescriptor.m_Bias = &biasTensor;
- AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());
- AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());
-
std::unique_ptr<IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::DepthwiseConvolution2d,
queueDescriptor,
workloadInfo);
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-16 16:46:09 +0000