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Diffstat (limited to 'src/armnn/optimizations/MaxMinIntoBoundedRelu.hpp')
| -rw-r--r-- | src/armnn/optimizations/MaxMinIntoBoundedRelu.hpp | 136 |
1 files changed, 136 insertions, 0 deletions
diff --git a/src/armnn/optimizations/MaxMinIntoBoundedRelu.hpp b/src/armnn/optimizations/MaxMinIntoBoundedRelu.hpp new file mode 100644 index 0000000000..99089f3a3e --- /dev/null +++ b/src/armnn/optimizations/MaxMinIntoBoundedRelu.hpp @@ -0,0 +1,136 @@ +// +// Copyright © 2024 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "Optimization.hpp" + +namespace armnn::optimizations +{ + +class MaxMinIntoBoundedReluImpl +{ +public: + /// Run for every exclusive connection between any Max & Min layers + /// The Max, Min and its associated constant inputs will be removed, and replaced with a BoundedRelu Activation + static void Run(Graph& graph, InputSlot& connection) + { + Layer& base = connection.GetConnectedOutputSlot()->GetOwningLayer(); + Layer& child = connection.GetOwningLayer(); + + auto& maxLayer = *PolymorphicDowncast<ElementwiseBinaryLayer*>(&base); + if (maxLayer.GetParameters().m_Operation != BinaryOperation::Maximum) + { + return; + } + auto& minLayer = *PolymorphicDowncast<ElementwiseBinaryLayer*>(&child); + if (minLayer.GetParameters().m_Operation != BinaryOperation::Minimum) + { + return; + } + + if (maxLayer.GetDataType() != minLayer.GetDataType()) + { + return; + } + + // get max and min values + float_t maxValue; + if (!GetValue(maxLayer, maxValue)) + { + return; + } + float_t minValue; + if (!GetValue(minLayer, minValue)) + { + return; + } + + // Save original parent output slot of the max layer + OutputSlot& parentOut = *maxLayer.GetInputSlot(0).GetConnectedOutputSlot(); + + // Insert activation layer between max layer and its parent layer + ActivationDescriptor boundedReluDescriptor(ActivationFunction::BoundedReLu, minValue, maxValue); + const std::string name = std::string("replaced-") + maxLayer.GetName() + std::string("-") + minLayer.GetName() + + std::string("-with-BoundedRelu"); + auto& boundedReluLayer = *graph.InsertNewLayer<ActivationLayer>(maxLayer.GetInputSlot(0), + boundedReluDescriptor, + name.c_str()); + + // Reconnects with original parent. + boundedReluLayer.GetOutputSlot().MoveAllConnections(parentOut); + + // Moves connections in min layer output to parent layer. + // Min layer will be removed as it's left unconnected. + // Max layer will be removed if left unconnected. + minLayer.GetOutputSlot().MoveAllConnections(boundedReluLayer.GetOutputSlot()); + } + +protected: + MaxMinIntoBoundedReluImpl() = default; + ~MaxMinIntoBoundedReluImpl() = default; + +private: + static float_t GetConstTensorValue(Layer& layer) + { + auto& constLayer = *PolymorphicDowncast<ConstantLayer*>(&layer); + switch (constLayer.GetDataType()) + { + case DataType::Float32: + return *constLayer.m_LayerOutput->GetConstTensor<float>(); + case DataType::BFloat16: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<BFloat16>()); + case DataType::Float16: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<half_float::half>()); + case DataType::QAsymmU8: + case DataType::Boolean: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<uint8_t>()); + case DataType::QAsymmS8: + case DataType::QSymmS8: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<int8_t>()); + case DataType::QSymmS16: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<int16_t>()); + case DataType::Signed32: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<int32_t>()); + case DataType::Signed64: + return static_cast<float_t>(*constLayer.m_LayerOutput->GetConstTensor<int64_t>()); + default: + throw InvalidArgumentException("No supported Data Type"); + } + } + + static bool GetValue(Layer& layer, float_t& value) + { + Layer& input0 = layer.GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); + Layer& input1 = layer.GetInputSlot(1).GetConnectedOutputSlot()->GetOwningLayer(); + if (input0.GetType() == LayerType::Constant) + { + if (input0.GetOutputSlot(0).GetTensorInfo().GetNumElements() != 1) + { + return false; + } + value = GetConstTensorValue(input0); + } + else if (input1.GetType() == LayerType::Constant) + { + if (input1.GetOutputSlot(0).GetTensorInfo().GetNumElements() != 1) + { + return false; + } + value = GetConstTensorValue(input1); + } + else + { + return false; + } + return true; + }; +}; + +using MaxMinIntoBoundedRelu = OptimizeForExclusiveConnection<ElementwiseBinaryLayer, + ElementwiseBinaryLayer, + MaxMinIntoBoundedReluImpl>; + +} // namespace armnn::optimizations
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