IVGCVSW-1803 : add Ref Subtraction layer

Change-Id: I4c019d626f9369245eca6d549bbe7a28e141f198

6 files changed, 178 insertions, 0 deletions

diff --git a/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.cpp b/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.cpp
new file mode 100644
index 0000000000..4440eedab7
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.cpp
@@ -0,0 +1,31 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefSubtractionFloat32Workload.hpp"
+
+#include "Subtraction.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include "Profiling.hpp"
+
+namespace armnn
+{
+
+void RefSubtractionFloat32Workload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefSubtractionFloat32Workload_Execute");
+
+    const TensorShape& inShape0 = GetTensorInfo(m_Data.m_Inputs[0]).GetShape();
+    const TensorShape& inShape1 = GetTensorInfo(m_Data.m_Inputs[1]).GetShape();
+    const TensorShape& outShape = GetTensorInfo(m_Data.m_Outputs[0]).GetShape();
+
+    const float* inData0 = GetInputTensorDataFloat(0, m_Data);
+    const float* inData1 = GetInputTensorDataFloat(1, m_Data);
+    float* outData = GetOutputTensorDataFloat(0, m_Data);
+
+    Subtraction(inShape0, inShape1, outShape, inData0, inData1, outData);
+}
+
+} //namespace armnn
diff --git a/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.hpp b/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.hpp
new file mode 100644
index 0000000000..b3f5ed9474
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/RefSubtractionFloat32Workload.hpp
@@ -0,0 +1,21 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "backends/Workload.hpp"
+#include "backends/WorkloadData.hpp"
+
+namespace armnn
+{
+
+class RefSubtractionFloat32Workload : public Float32Workload<SubtractionQueueDescriptor>
+{
+public:
+    using Float32Workload<SubtractionQueueDescriptor>::Float32Workload;
+    virtual void Execute() const override;
+};
+
+} //namespace armnn
diff --git a/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.cpp b/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.cpp
new file mode 100644
index 0000000000..8066762e48
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.cpp
@@ -0,0 +1,41 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefSubtractionUint8Workload.hpp"
+
+#include "Subtraction.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include "Profiling.hpp"
+
+#include <vector>
+
+namespace armnn
+{
+
+void RefSubtractionUint8Workload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefSubtractionUint8Workload_Execute");
+
+    const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
+    const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
+    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+
+    auto dequant0 = Dequantize(GetInputTensorDataU8(0, m_Data), inputInfo0);
+    auto dequant1 = Dequantize(GetInputTensorDataU8(1, m_Data), inputInfo1);
+
+    std::vector<float> results(outputInfo.GetNumElements());
+
+    Subtraction(inputInfo0.GetShape(),
+                inputInfo1.GetShape(),
+                outputInfo.GetShape(),
+                dequant0.data(),
+                dequant1.data(),
+                results.data());
+
+    Quantize(GetOutputTensorDataU8(0, m_Data), results.data(), outputInfo);
+}
+
+} //namespace armnn
diff --git a/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.hpp b/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.hpp
new file mode 100644
index 0000000000..582533253b
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/RefSubtractionUint8Workload.hpp
@@ -0,0 +1,21 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "backends/Workload.hpp"
+#include "backends/WorkloadData.hpp"
+
+namespace armnn
+{
+
+class RefSubtractionUint8Workload : public Uint8Workload<SubtractionQueueDescriptor>
+{
+public:
+    using Uint8Workload<SubtractionQueueDescriptor>::Uint8Workload;
+    virtual void Execute() const override;
+};
+
+} //namespace armnn
diff --git a/src/armnn/backends/RefWorkloads/Subtraction.cpp b/src/armnn/backends/RefWorkloads/Subtraction.cpp
new file mode 100644
index 0000000000..f25c8adb1c
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/Subtraction.cpp
@@ -0,0 +1,44 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "Subtraction.hpp"
+#include "Broadcast.hpp"
+
+#include <functional>
+
+namespace
+{
+
+void ElementwiseSubtraction(unsigned int numElements, const float* inData0, const float* inData1, float* outData)
+{
+    for (unsigned int i = 0; i < numElements; ++i)
+    {
+        outData[i] = inData0[i] - inData1[i];
+    }
+}
+
+} // namespace
+
+namespace armnn
+{
+
+void Subtraction(const TensorShape& inShape0,
+                 const TensorShape& inShape1,
+                 const TensorShape& outShape,
+                 const float* inData0,
+                 const float* inData1,
+                 float* outData)
+{
+    if (inShape0 == inShape1)
+    {
+        ElementwiseSubtraction(inShape0.GetNumElements(), inData0, inData1, outData);
+    }
+    else
+    {
+        BroadcastLoop(inShape0, inShape1, outShape).Unroll(std::minus<float>(), 0, inData0, inData1, outData);
+    }
+}
+
+} //namespace armnn
diff --git a/src/armnn/backends/RefWorkloads/Subtraction.hpp b/src/armnn/backends/RefWorkloads/Subtraction.hpp
new file mode 100644
index 0000000000..3956797185
--- /dev/null
+++ b/src/armnn/backends/RefWorkloads/Subtraction.hpp
@@ -0,0 +1,20 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/Tensor.hpp>
+
+namespace armnn
+{
+
+void Subtraction(const TensorShape& inShape0,
+                 const TensorShape& inShape1,
+                 const TensorShape& outShape,
+                 const float* inData0,
+                 const float* inData1,
+                 float* outData);
+
+} //namespace armnn