IVGCVSW-2632 Fix RefMerger from QAsymm8 types with different quantization parameters
Change-Id: Ie67ce4966c5e5fef618876b027292da429de1485
Signed-off-by: Ferran Balaguer <ferran.balaguer@arm.com>
diff --git a/src/armnn/NetworkQuantizerUtils.cpp b/src/armnn/NetworkQuantizerUtils.cpp
index 1bec63b..551760f 100644
--- a/src/armnn/NetworkQuantizerUtils.cpp
+++ b/src/armnn/NetworkQuantizerUtils.cpp
@@ -12,7 +12,7 @@
namespace armnn
{
-std::pair<int, float> ComputeQAsymmParams(int numBits, double min, double max)
+std::pair<float, int> ComputeQAsymmParams(int numBits, double min, double max)
{
BOOST_ASSERT_MSG(min < max, "min >= max will result in invalid quantization.");
double highest = (1 << numBits) - 1;
@@ -27,7 +27,7 @@
// Clamp offset [0-highest]
offset = std::max(0.0, std::min(highest, offset));
- return std::make_pair(static_cast<int>(std::round(offset)), static_cast<float>(scale));
+ return std::make_pair(static_cast<float>(scale), static_cast<int>(std::round(offset)));
}
ConstTensor CreateQuantizedConst(const ConstTensor& tensor, std::vector<uint8_t>& backing)
diff --git a/src/armnn/NetworkQuantizerUtils.hpp b/src/armnn/NetworkQuantizerUtils.hpp
index 458d21a..c23517e 100644
--- a/src/armnn/NetworkQuantizerUtils.hpp
+++ b/src/armnn/NetworkQuantizerUtils.hpp
@@ -17,7 +17,7 @@
namespace armnn
{
-std::pair<int, float> ComputeQAsymmParams(int numBits, double min, double max);
+std::pair<float, int> ComputeQAsymmParams(int numBits, double min, double max);
template<typename srcType>
void Quantize(const srcType* src, uint8_t* dst, size_t numElements, float& scale, int& offset)
@@ -34,8 +34,8 @@
}
auto qParams = ComputeQAsymmParams(8, min, max);
- offset = qParams.first;
- scale = qParams.second;
+ scale = qParams.first;
+ offset = qParams.second;
for (size_t i = 0; i < numElements; ++i)
{
dst[i] = armnn::Quantize<uint8_t>(src[i], scale, offset);
diff --git a/src/armnn/QuantizerVisitor.cpp b/src/armnn/QuantizerVisitor.cpp
index 437d7b9..110594c 100644
--- a/src/armnn/QuantizerVisitor.cpp
+++ b/src/armnn/QuantizerVisitor.cpp
@@ -50,8 +50,8 @@
// Set the quantization params
TensorInfo info(newOutputSlot.GetTensorInfo());
info.SetDataType(DataType::QuantisedAsymm8);
- info.SetQuantizationOffset(qParams.first);
- info.SetQuantizationScale(qParams.second);
+ info.SetQuantizationOffset(qParams.second);
+ info.SetQuantizationScale(qParams.first);
newOutputSlot.SetTensorInfo(info);
}
}
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp
index fcce208..f7723bd 100644
--- a/src/armnn/test/QuantizerTest.cpp
+++ b/src/armnn/test/QuantizerTest.cpp
@@ -997,15 +997,15 @@
const OriginsDescriptor& mergerDescriptor,
const char* name = nullptr)
{
- std::pair<int, float> expectedValues = ComputeQAsymmParams(8, m_Min, m_Max);
+ std::pair<float, int> expectedValues = ComputeQAsymmParams(8, m_Min, m_Max);
TensorInfo info = layer->GetOutputSlot(0).GetTensorInfo();
BOOST_TEST((info.GetDataType() == DataType::QuantisedAsymm8));
- BOOST_TEST((info.GetQuantizationOffset() == expectedValues.first));
+ BOOST_TEST((info.GetQuantizationOffset() == expectedValues.second));
- BOOST_CHECK_CLOSE(info.GetQuantizationScale(), expectedValues.second, 0.000001f);
+ BOOST_CHECK_CLOSE(info.GetQuantizationScale(), expectedValues.first, 0.000001f);
}
private:
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index 6060b30..a6b3b3d 100644
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -5993,6 +5993,148 @@
return ConstantTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 1.0f, 0);
}
+LayerTestResult<uint8_t, 3> MergerUint8DifferentQParamsTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ unsigned int outputWidth = 3;
+ unsigned int outputHeight = 6;
+ unsigned int outputChannels = 3;
+
+ unsigned int inputWidth1 = 3;
+ unsigned int inputHeight1 = 6;
+ unsigned int inputChannels1 = 2;
+
+ unsigned int inputWidth2 = 3;
+ unsigned int inputHeight2 = 6;
+ unsigned int inputChannels2 = 1;
+
+ // Defines the tensor descriptors.
+ armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedAsymm8);
+ armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedAsymm8);
+ armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedAsymm8);
+
+ // Quantized input1 tensor. Range [-3, 1]
+ const float inputScale1 = 0.015686f;
+ const int32_t inputOffset1 = 192;
+
+ auto input1 = MakeTensor<uint8_t, 3>(inputTensorInfo1, std::vector<uint8_t>(
+ {
+ 1, 2, 3,
+ 4, 5, 6,
+ 7, 8, 9,
+ 10, 11, 12,
+ 13, 14, 15,
+ 16, 17, 18,
+
+ 19, 20, 21,
+ 22, 23, 24,
+ 25, 26, 27,
+ 28, 29, 30,
+ 31, 32, 33,
+ 34, 35, 36,
+ })
+ );
+
+ // Quatized input2 tensor. Range [-1, 4]
+ const float inputScale2 = 0.019608f;
+ const int32_t inputOffset2 = 50;
+
+ auto input2 = MakeTensor<uint8_t, 3>(inputTensorInfo2, std::vector<uint8_t>(
+ {
+ 37, 38, 39,
+ 40, 41, 42,
+ 43, 44, 45,
+ 46, 47, 48,
+ 49, 50, 51,
+ 52, 53, 54,
+ })
+ );
+
+ // Output has the same quantization parameters than input1,
+ // so that only the requantization of input2 is required
+ const float outputScale = 0.015686f;
+ const int32_t outputOffset = 192;
+
+ LayerTestResult<uint8_t, 3> ret(outputTensorInfo);
+
+ ret.outputExpected = MakeTensor<uint8_t, 3>(outputTensorInfo, std::vector<uint8_t>(
+ {
+ 1, 2, 3,
+ 4, 5, 6,
+ 7, 8, 9,
+ 10, 11, 12,
+ 13, 14, 15,
+ 16, 17, 18,
+
+ 19, 20, 21,
+ 22, 23, 24,
+ 25, 26, 27,
+ 28, 29, 30,
+ 31, 32, 33,
+ 34, 35, 36,
+
+ 176, 177, 178,
+ 179, 181, 182,
+ 183, 184, 186,
+ 187, 188, 189,
+ 191, 192, 193,
+ 195, 196, 197,
+ })
+ );
+
+ outputTensorInfo.SetQuantizationScale(outputScale);
+ outputTensorInfo.SetQuantizationOffset(outputOffset);
+ inputTensorInfo1.SetQuantizationScale(inputScale1);
+ inputTensorInfo1.SetQuantizationOffset(inputOffset1);
+ inputTensorInfo2.SetQuantizationScale(inputScale2);
+ inputTensorInfo2.SetQuantizationOffset(inputOffset2);
+
+ std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0].
+ armnn::MergerQueueDescriptor::ViewOrigin window1(wOrigin1);
+
+ std::vector<unsigned int> wOrigin2 = { 2, 0, 0 }; //Extent of the window is defined by size of input[1].
+ armnn::MergerQueueDescriptor::ViewOrigin window2(wOrigin2);
+
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ bool subTensorsSupported = workloadFactory.SupportsSubTensors();
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle1 =
+ subTensorsSupported ?
+ workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) :
+ workloadFactory.CreateTensorHandle(inputTensorInfo1);
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle2 =
+ subTensorsSupported ?
+ workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) :
+ workloadFactory.CreateTensorHandle(inputTensorInfo2);
+
+ armnn::MergerQueueDescriptor data;
+ armnn::WorkloadInfo info;
+ AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());
+ AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+ data.m_ViewOrigins.push_back(window1);
+ data.m_ViewOrigins.push_back(window2);
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(data, info);
+
+ inputHandle1->Allocate();
+ inputHandle2->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
+ CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
+
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
+
+ return ret;
+}
+
LayerTestResult<uint8_t, 3> MergerUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index 05d510e..93385f0 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -745,6 +745,10 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+LayerTestResult<uint8_t, 3> MergerUint8DifferentQParamsTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
+
LayerTestResult<uint8_t, 4> AdditionUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
diff --git a/src/backends/reference/backend.mk b/src/backends/reference/backend.mk
index acaedc9..a75146b 100644
--- a/src/backends/reference/backend.mk
+++ b/src/backends/reference/backend.mk
@@ -21,6 +21,7 @@
workloads/FullyConnected.cpp \
workloads/Gather.cpp \
workloads/Mean.cpp \
+ workloads/Merger.cpp \
workloads/Pad.cpp \
workloads/Pooling2d.cpp \
workloads/RefActivationFloat32Workload.cpp \
diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp
index b4ef85a..cf8e6a2 100644
--- a/src/backends/reference/test/RefLayerTests.cpp
+++ b/src/backends/reference/test/RefLayerTests.cpp
@@ -209,6 +209,7 @@
// Merger
ARMNN_AUTO_TEST_CASE(SimpleMerger, MergerTest)
ARMNN_AUTO_TEST_CASE(MergerUint8, MergerUint8Test)
+ARMNN_AUTO_TEST_CASE(MergerUint8DifferentQParams, MergerUint8DifferentQParamsTest)
// Add
ARMNN_AUTO_TEST_CASE(SimpleAdd, AdditionTest)
diff --git a/src/backends/reference/workloads/CMakeLists.txt b/src/backends/reference/workloads/CMakeLists.txt
index 47e42f7..89aed91 100644
--- a/src/backends/reference/workloads/CMakeLists.txt
+++ b/src/backends/reference/workloads/CMakeLists.txt
@@ -25,6 +25,7 @@
Gather.hpp
Maximum.hpp
Merger.hpp
+ Merger.cpp
Minimum.hpp
Pad.cpp
Pad.hpp
diff --git a/src/backends/reference/workloads/Merger.cpp b/src/backends/reference/workloads/Merger.cpp
new file mode 100644
index 0000000..10cc249
--- /dev/null
+++ b/src/backends/reference/workloads/Merger.cpp
@@ -0,0 +1,110 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "Merger.hpp"
+#include "RefWorkloadUtils.hpp"
+
+namespace armnn
+{
+
+template <>
+void CopyValue<float>(const float& source, const TensorInfo& sourceInfo, float& dest, const TensorInfo& destInfo)
+{
+ dest = source;
+}
+
+template <>
+void CopyValue<uint8_t>(const uint8_t& source, const TensorInfo& sourceInfo, uint8_t& dest, const TensorInfo& destInfo)
+{
+ if (sourceInfo.GetQuantizationScale() != destInfo.GetQuantizationScale() ||
+ sourceInfo.GetQuantizationOffset() != destInfo.GetQuantizationOffset())
+ {
+ // Dequantize value acording to sourceInfo params
+ float dequantizedValue = armnn::Dequantize<uint8_t>(source,
+ sourceInfo.GetQuantizationScale(),
+ sourceInfo.GetQuantizationOffset());
+
+ // Quantize again according to destInfo paramns
+ dest = armnn::Quantize<uint8_t>(dequantizedValue,
+ destInfo.GetQuantizationScale(),
+ destInfo.GetQuantizationOffset());
+ }
+ else
+ {
+ dest = source;
+ }
+}
+
+template <typename DataType>
+void Merger(const MergerQueueDescriptor& data)
+{
+ const TensorInfo& outputInfo0 = GetTensorInfo(data.m_Outputs[0]);
+
+ for (unsigned int index = 0 ; index < outputInfo0.GetNumElements(); ++index)
+ {
+ unsigned int indices[MaxNumOfTensorDimensions] = { 0 };
+
+ unsigned int indexRemainder = index;
+ unsigned int dimensionStride = outputInfo0.GetNumElements();
+
+ for (unsigned int i = 0; i < outputInfo0.GetNumDimensions(); i++)
+ {
+ dimensionStride /= outputInfo0.GetShape()[i];
+ indices[i] = indexRemainder / dimensionStride; // Use integer division to round down.
+ indexRemainder -= indices[i] * dimensionStride;
+ }
+
+ for (unsigned int viewIdx = 0; viewIdx < data.m_ViewOrigins.size(); ++viewIdx)
+ {
+ MergerQueueDescriptor::ViewOrigin const& view = data.m_ViewOrigins[viewIdx];
+
+ //Split view extents are defined by the size of (the corresponding) input tensor.
+ const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[viewIdx]);
+ BOOST_ASSERT(inputInfo.GetNumDimensions() == outputInfo0.GetNumDimensions());
+
+ // Check all dimensions to see if this element is inside the given input view.
+ bool insideView = true;
+ for (unsigned int i = 0; i < inputInfo.GetNumDimensions(); i++)
+ {
+ if (indices[i] < view.m_Origin[i])
+ {
+ insideView = false;
+ }
+ if (indices[i] >= view.m_Origin[i] + inputInfo.GetShape()[i])
+ {
+ insideView = false;
+ }
+ }
+
+ if (insideView)
+ {
+ unsigned int inIndex = 0;
+ unsigned int dimensionStride = 1;
+
+ for (unsigned int i = inputInfo.GetNumDimensions(); i-- > 0;)
+ {
+ inIndex += dimensionStride * (indices[i] - view.m_Origin[i]);
+ dimensionStride *= inputInfo.GetShape()[i];
+ }
+
+ CopyValue<DataType>((GetInputTensorData<DataType>(viewIdx, data))[inIndex],
+ GetTensorInfo(data.m_Inputs[viewIdx]),
+ (GetOutputTensorData<DataType>(0, data))[index],
+ outputInfo0);
+
+ //What should we do if input views overlap on the output tensor?
+ //We could error, take the average, or shm else...
+ //For now just stop after finding first view (input) that matches.
+ break;
+ }
+ }
+ }
+}
+
+template void Merger<float>(const MergerQueueDescriptor& data);
+
+template void Merger<uint8_t>(const MergerQueueDescriptor& data);
+
+} //namespace armnn
diff --git a/src/backends/reference/workloads/Merger.hpp b/src/backends/reference/workloads/Merger.hpp
index 76d807c..ba3b99b 100644
--- a/src/backends/reference/workloads/Merger.hpp
+++ b/src/backends/reference/workloads/Merger.hpp
@@ -5,8 +5,6 @@
#pragma once
-#include "RefWorkloadUtils.hpp"
-
#include <backendsCommon/WorkloadData.hpp>
#include <armnn/Tensor.hpp>
@@ -14,68 +12,9 @@
{
template <typename DataType>
-void Merger(const MergerQueueDescriptor& data)
-{
- const TensorInfo& outputInfo0 = GetTensorInfo(data.m_Outputs[0]);
+void CopyValue(const DataType& source, const TensorInfo& sourceInfo, DataType& dest, const TensorInfo& destInfo);
- for (unsigned int index = 0 ; index < outputInfo0.GetNumElements(); ++index)
- {
- unsigned int indices[MaxNumOfTensorDimensions] = { 0 };
-
- unsigned int indexRemainder = index;
- unsigned int dimensionStride = outputInfo0.GetNumElements();
-
- for (unsigned int i=0; i<outputInfo0.GetNumDimensions(); i++)
- {
- dimensionStride /= outputInfo0.GetShape()[i];
- indices[i] = indexRemainder / dimensionStride; // Use integer division to round down.
- indexRemainder -= indices[i] * dimensionStride;
- }
-
- for (unsigned int viewIdx = 0; viewIdx < data.m_ViewOrigins.size(); ++viewIdx)
- {
- MergerQueueDescriptor::ViewOrigin const& view = data.m_ViewOrigins[viewIdx];
-
- //Split view extents are defined by the size of (the corresponding) input tensor.
- const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[viewIdx]);
- BOOST_ASSERT(inputInfo.GetNumDimensions() == outputInfo0.GetNumDimensions());
-
- // Check all dimensions to see if this element is inside the given input view.
- bool insideView = true;
- for (unsigned int i=0; i<inputInfo.GetNumDimensions(); i++)
- {
- if (indices[i] < view.m_Origin[i])
- {
- insideView = false;
- }
- if (indices[i] >= view.m_Origin[i] + inputInfo.GetShape()[i])
- {
- insideView = false;
- }
- }
-
- if (insideView)
- {
- unsigned int inIndex = 0;
- unsigned int dimensionStride = 1;
-
- for (unsigned int i = inputInfo.GetNumDimensions(); i-- > 0;)
- {
- inIndex += dimensionStride * (indices[i] - view.m_Origin[i]);
- dimensionStride *= inputInfo.GetShape()[i];
- }
-
- //We are within the view, copy input data to the output corresponding to this view.
- (GetOutputTensorData<DataType>(0, data))[index] =
- (GetInputTensorData<DataType>(viewIdx, data))[inIndex];
-
- //What should we do if input views overlap on the output tensor?
- //We could error, take the average, or shm else...
- //For now just stop after finding first view (input) that matches.
- break;
- }
- }
- }
-}
+template <typename DataType>
+void Merger(const MergerQueueDescriptor& data);
} //namespace armnn