src/armnn/layers/DepthwiseConvolution2dLayer.cpp

   1 //
   2 // Copyright © 2017 Arm Ltd. All rights reserved.
   3 // SPDX-License-Identifier: MIT
   4 //
   5 #include "DepthwiseConvolution2dLayer.hpp"
   6
   7 #include "LayerCloneBase.hpp"
   8
   9 #include <armnn/TypesUtils.hpp>
  10 #include <backendsCommon/CpuTensorHandle.hpp>
  11 #include <backendsCommon/WorkloadFactory.hpp>
  12
  13 namespace armnn
  14 {
  15
  16 DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor& param,
  17                                                          const char* name)
  18     : LayerWithParameters(1, 1, LayerType::DepthwiseConvolution2d, param, name)
  19 {
  20 }
  21
  22 std::unique_ptr<IWorkload> DepthwiseConvolution2dLayer::CreateWorkload(const Graph&                  graph,
  23                                                                        const IWorkloadFactory& factory) const
  24 {
  25     // on this level constant data should not be released..
  26     BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
  27
  28     DepthwiseConvolution2dQueueDescriptor descriptor;
  29
  30     descriptor.m_Weight = m_Weight.get();
  31
  32     if (m_Param.m_BiasEnabled)
  33     {
  34         BOOST_ASSERT_MSG(m_Bias != nullptr, "DepthwiseConvolution2dLayer: Bias data should not be null.");
  35         descriptor.m_Bias = m_Bias.get();
  36     }
  37     return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor, graph));
  38 }
  39
  40 DepthwiseConvolution2dLayer* DepthwiseConvolution2dLayer::Clone(Graph& graph) const
  41 {
  42     auto layer      = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
  43     layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
  44
  45     if (layer->m_Param.m_BiasEnabled)
  46     {
  47         layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
  48     }
  49
  50     return std::move(layer);
  51 }
  52
  53 std::vector<TensorShape>
  54 DepthwiseConvolution2dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
  55 {
  56     BOOST_ASSERT(inputShapes.size() == 2);
  57     const TensorShape& inputShape = inputShapes[0];
  58     const TensorShape filterShape = inputShapes[1];
  59
  60     BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
  61
  62     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
  63
  64     unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
  65     unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
  66     unsigned int inBatchSize = inputShape[0];
  67
  68     unsigned int filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];
  69     unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - (filterWidth);
  70     unsigned int outWidth =  1 + (readWidth / m_Param.m_StrideX);
  71
  72     unsigned int filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];
  73     unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - (filterHeight);
  74     unsigned int outHeight = 1 + (readHeight / m_Param.m_StrideY);
  75     unsigned int depthMultiplier = filterShape[0];
  76
  77     unsigned int outChannels = filterShape[dataLayoutIndex.GetChannelsIndex()] * depthMultiplier;
  78     unsigned int outBatchSize = inBatchSize;
  79
  80     TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
  81         TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
  82         TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
  83
  84     return std::vector<TensorShape>({ tensorShape });
  85 }
  86
  87 void DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs()
  88 {
  89     VerifyLayerConnections(1, CHECK_LOCATION());
  90
  91     // on this level constant data should not be released..
  92     BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
  93
  94     auto inferredShapes = InferOutputShapes({
  95         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
  96         m_Weight->GetTensorInfo().GetShape()
  97      });
  98
  99     BOOST_ASSERT(inferredShapes.size() == 1);
 100
 101     ConditionalThrowIfNotEqual<LayerValidationException>(
 102         "DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
 103         GetOutputSlot(0).GetTensorInfo().GetShape(),
 104         inferredShapes[0]);
 105 }
 106
 107 Layer::ConstantTensors DepthwiseConvolution2dLayer::GetConstantTensorsByRef()
 108 {
 109     return {m_Weight, m_Bias};
 110 }
 111
 112 } // namespace armnn