IVGCVSW-2970 Support QSymm16 for FullyConnected workloads
* Add support for QSymm16 for FullyConnected
* Add templating to Uint8 RefLayerTest to test QSymm16
Change-Id: Ie6e989daf2ca966d6c6805b8017126eb77ebfec4
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index a1c74df..d9779e4 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -511,6 +511,23 @@
ValidateTensorQuantizationMultiplier(workloadInfo.m_InputTensorInfos[0], m_Weight->GetTensorInfo(),
workloadInfo.m_OutputTensorInfos[0], "FullyConnectedQueueDescriptor", "input", "weights", "output");
+
+ // Check the supported data types
+ std::vector<DataType> supportedTypes =
+ {
+ DataType::Float32,
+ DataType::Float16,
+ DataType::QuantisedAsymm8,
+ DataType::QuantisedSymm16
+ };
+
+ ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+ supportedTypes,
+ "FullyConnectedQueueDescriptor");
+
+ ValidateDataTypes(workloadInfo.m_OutputTensorInfos[0],
+ {workloadInfo.m_InputTensorInfos[0].GetDataType()},
+ "FullyConnectedQueueDescriptor");
}
//---------------------------------------------------------------
diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp
index 0490a94..7631071 100644
--- a/src/backends/backendsCommon/WorkloadFactory.cpp
+++ b/src/backends/backendsCommon/WorkloadFactory.cpp
@@ -17,6 +17,7 @@
#include <backendsCommon/BackendRegistry.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
#include <boost/cast.hpp>
#include <boost/iterator/transform_iterator.hpp>
@@ -40,26 +41,6 @@
return TensorInfo(info.GetShape(), type.value(), info.GetQuantizationScale(), info.GetQuantizationOffset());
}
-Optional<DataType> GetBiasTypeFromWeightsType(Optional<DataType> weightsType)
-{
- if (!weightsType)
- {
- return weightsType;
- }
-
- switch(weightsType.value())
- {
- case DataType::Float16:
- case DataType::Float32:
- return weightsType;
- case DataType::QuantisedAsymm8:
- return DataType::Signed32;
- default:
- BOOST_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type.");
- }
- return EmptyOptional();
-}
-
} // anonymous namespace
bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId,
diff --git a/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp b/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp
index 3e6223a..402a3e6 100644
--- a/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp
+++ b/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp
@@ -5,61 +5,8 @@
#include <ResolveType.hpp>
#include "WorkloadTestUtils.hpp"
-
#include <backendsCommon/IBackendInternal.hpp>
-template<typename T, typename B>
-LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
- armnn::IWorkloadFactory& workloadFactory,
- const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- armnn::TensorInfo inputTensorInfo,
- 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,
- bool biasEnabled,
- bool transposeWeights)
-{
- std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
- std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
- armnn::FullyConnectedQueueDescriptor data;
- armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(weightsDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasesDesc);
-
- AllocateAndCopyDataToITensorHandle(&weightsTensor, &weights[0][0]);
- AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
-
- AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
- data.m_Weight = &weightsTensor;
- data.m_Bias = &biasTensor;
- data.m_Parameters.m_BiasEnabled = biasEnabled;
- data.m_Parameters.m_TransposeWeightMatrix = transposeWeights;
-
- std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFullyConnected(data, info);
- LayerTestResult<T, 2> result(outputTensorInfo);
-
- inputHandle->Allocate();
- outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
- ExecuteWorkload(*workload, memoryManager);
-
- if (workloadFactory.GetBackendId() == armnn::Compute::CpuRef)
- {
- workload->PostAllocationConfigure();
- workload->Execute();
- }
-
- CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
-
- return result;
-}
-
LayerTestResult<float, 2> FullyConnectedFloat32Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
@@ -155,72 +102,6 @@
return result;
}
-LayerTestResult<uint8_t, 2> FullyConnectedUint8Test(
- armnn::IWorkloadFactory& workloadFactory,
- const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- bool biasEnabled)
-{
- constexpr static unsigned int inputWidth = 3u;
- constexpr static unsigned int inputHeight = 2u;
- constexpr static unsigned int inputChannels = 1u;
-
- constexpr static unsigned int inputSize = inputWidth * inputHeight * inputChannels;
-
- constexpr static unsigned int outputChannels = 2u;
-
- armnn::TensorInfo inputTensorInfo({ 1, inputChannels, inputHeight, inputWidth }, armnn::DataType::QuantisedAsymm8);
- inputTensorInfo.SetQuantizationScale(0.1f);
- inputTensorInfo.SetQuantizationOffset(63);
-
- armnn::TensorInfo outputTensorInfo({ 1, outputChannels }, armnn::DataType::QuantisedAsymm8);
- outputTensorInfo.SetQuantizationScale(5.f);
- outputTensorInfo.SetQuantizationOffset(biasEnabled ? -50 : 10);
-
- armnn::TensorInfo weightsDesc({ outputChannels, inputSize }, armnn::DataType::QuantisedAsymm8);
- weightsDesc.SetQuantizationScale(0.2f);
- weightsDesc.SetQuantizationOffset(93);
-
- armnn::TensorInfo biasesDesc({ outputChannels }, armnn::DataType::Signed32);
- biasesDesc.SetQuantizationScale(inputTensorInfo.GetQuantizationScale() * weightsDesc.GetQuantizationScale());
- biasesDesc.SetQuantizationOffset(0);
-
- LayerTestResult<uint8_t, 2> result(outputTensorInfo);
-
- auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>{51, 124, 28,
- 251, 8, 92});
-
- auto weights = MakeTensor<uint8_t, 2>(weightsDesc, std::vector<uint8_t>{51, 193, 42, 53, 175, 34,
- 210, 145, 23, 74, 34, 150});
-
- // scale = 0.02
- // offset = 0
- auto bias = MakeTensor<int32_t, 1>(biasesDesc, std::vector<int32_t>{9250, 67500});
-
- result = SimpleFullyConnectedTestImpl<uint8_t>(
- workloadFactory,
- memoryManager,
- inputTensorInfo, outputTensorInfo,
- weightsDesc, biasesDesc,
- weights, bias, input,
- biasEnabled, true
- );
-
- // Manually calculated.
- // Note one of these values has been clamped to 0.
- if (biasEnabled)
- {
- result.outputExpected = MakeTensor<uint8_t, 2>(outputTensorInfo, std::vector<uint8_t>{0, 242});
- }
- else
- {
- result.outputExpected = MakeTensor<uint8_t, 2>(outputTensorInfo, std::vector<uint8_t>{0, 32});
- }
-
- return result;
-}
-
-
-
//
// ArmNN variant of the AndroidNN fully_connected_float_large test.
//
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index 9e57ec5..f8f5036 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -8,9 +8,15 @@
#include <armnn/Tensor.hpp>
#include <Half.hpp>
+#include "TensorCopyUtils.hpp"
+#include "WorkloadTestUtils.hpp"
+#include <backendsCommon/CpuTensorHandle.hpp>
#include <backendsCommon/IBackendInternal.hpp>
#include <backendsCommon/IMemoryManager.hpp>
+#include <reference/workloads/Decoders.hpp>
+#include <reference/workloads/Encoders.hpp>
+#include <test/TensorHelpers.hpp>
#include <boost/multi_array.hpp>
#include <boost/assert.hpp>
@@ -793,7 +799,8 @@
float upperBound,
float lowerBound);
-LayerTestResult<uint8_t, 2> FullyConnectedUint8Test(
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 2> FullyConnectedTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled);
@@ -1638,3 +1645,139 @@
LayerTestResult<int16_t, 4> QuantizeClampInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
+template<typename T, typename B>
+LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ armnn::TensorInfo inputTensorInfo,
+ 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,
+ bool biasEnabled,
+ bool transposeWeights)
+{
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::FullyConnectedQueueDescriptor data;
+ armnn::WorkloadInfo info;
+ armnn::ScopedCpuTensorHandle weightsTensor(weightsDesc);
+ armnn::ScopedCpuTensorHandle biasTensor(biasesDesc);
+
+ AllocateAndCopyDataToITensorHandle(&weightsTensor, &weights[0][0]);
+ AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
+
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+ data.m_Weight = &weightsTensor;
+ data.m_Bias = &biasTensor;
+ data.m_Parameters.m_BiasEnabled = biasEnabled;
+ data.m_Parameters.m_TransposeWeightMatrix = transposeWeights;
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFullyConnected(data, info);
+ LayerTestResult<T, 2> result(outputTensorInfo);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+ CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+ ExecuteWorkload(*workload, memoryManager);
+
+ CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+
+ return result;
+}
+
+template <armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+std::vector<T> ConvertToDataType(const std::vector<float>& input,
+ const armnn::TensorInfo& inputTensorInfo)
+{
+ std::vector<T> output(input.size());
+ auto outputTensorInfo = inputTensorInfo;
+ outputTensorInfo.SetDataType(ArmnnType);
+
+ std::unique_ptr<armnn::Encoder<float>> pOutputEncoder = armnn::MakeEncoder<float>(outputTensorInfo, output.data());
+ armnn::Encoder<float>& rOutputEncoder = *pOutputEncoder;
+
+ for (auto it = input.begin(); it != input.end(); ++it)
+ {
+ rOutputEncoder.Set(*it);
+ ++rOutputEncoder;
+ }
+ return output;
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<T, 2> FullyConnectedTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ bool biasEnabled)
+{
+ constexpr static unsigned int inputWidth = 3u;
+ constexpr static unsigned int inputHeight = 2u;
+ constexpr static unsigned int inputChannels = 1u;
+
+ constexpr static unsigned int inputSize = inputWidth * inputHeight * inputChannels;
+
+ constexpr static unsigned int outputChannels = 2u;
+
+ armnn::TensorInfo inputTensorInfo({ 1, inputChannels, inputHeight, inputWidth }, ArmnnType);
+ inputTensorInfo.SetQuantizationScale(0.1f);
+ inputTensorInfo.SetQuantizationOffset(63);
+
+ armnn::TensorInfo outputTensorInfo({ 1, outputChannels }, ArmnnType);
+ outputTensorInfo.SetQuantizationScale(5.f);
+ outputTensorInfo.SetQuantizationOffset(biasEnabled ? -50 : 10);
+
+ armnn::TensorInfo weightsDesc({ outputChannels, inputSize }, ArmnnType);
+ weightsDesc.SetQuantizationScale(0.2f);
+ weightsDesc.SetQuantizationOffset(93);
+
+ armnn::TensorInfo biasesDesc({ outputChannels }, GetBiasTypeFromWeightsType(weightsDesc.GetDataType()).value());
+ biasesDesc.SetQuantizationScale(inputTensorInfo.GetQuantizationScale() * weightsDesc.GetQuantizationScale());
+ biasesDesc.SetQuantizationOffset(0);
+
+ LayerTestResult<T, 2> result(outputTensorInfo);
+
+ auto input = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(
+ {
+ -1.2f, 6.1f, -3.5f,
+ 18.8f, -5.5f, 2.9f
+ },
+ inputTensorInfo));
+
+ auto weights = MakeTensor<T, 2>(weightsDesc, 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));
+
+ auto bias = MakeTensor<int32_t, 1>(biasesDesc, std::vector<int32_t>{9250, 67500});
+
+ result = SimpleFullyConnectedTestImpl<T>(
+ workloadFactory,
+ memoryManager,
+ inputTensorInfo, outputTensorInfo,
+ weightsDesc, biasesDesc,
+ weights, bias, input,
+ biasEnabled, true
+ );
+
+ if (biasEnabled)
+ {
+ result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
+ ConvertToDataType<ArmnnType>({80.f, 1460.f}, outputTensorInfo));
+ }
+ else
+ {
+ result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
+ ConvertToDataType<ArmnnType>({-107.04f, 110.f}, outputTensorInfo));
+ }
+
+ return result;
+}
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
index 212fea3..2f3e786 100644
--- a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
+++ b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
@@ -86,4 +86,26 @@
}
}
+inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Optional<armnn::DataType> weightsType)
+{
+ if (!weightsType)
+ {
+ return weightsType;
+ }
+
+ switch(weightsType.value())
+ {
+ case armnn::DataType::Float16:
+ case armnn::DataType::Float32:
+ return weightsType;
+ case armnn::DataType::QuantisedAsymm8:
+ return armnn::DataType::Signed32;
+ case armnn::DataType::QuantisedSymm16:
+ return armnn::DataType::Signed32;
+ default:
+ BOOST_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type.");
+ }
+ return armnn::EmptyOptional();
+}
+
} // anonymous namespace