src/armnn/layers/DepthwiseConvolution2dLayer.cpp

   1 //
   2 // Copyright © 2017 Arm Ltd. All rights reserved.
   3 // See LICENSE file in the project root for full license information.
   4 //
   5 #include "DepthwiseConvolution2dLayer.hpp"
   6
   7 #include "LayerCloneBase.hpp"
   8
   9 #include <armnn/TypesUtils.hpp>
  10 #include <backends/CpuTensorHandle.hpp>
  11 #include <backends/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     DepthwiseConvolution2dQueueDescriptor descriptor;
  26
  27     descriptor.m_Weight = m_Weight.get();
  28     if (m_Param.m_BiasEnabled)
  29     {
  30         descriptor.m_Bias = m_Bias.get();
  31     }
  32     return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor, graph));
  33 }
  34
  35 DepthwiseConvolution2dLayer* DepthwiseConvolution2dLayer::Clone(Graph& graph) const
  36 {
  37     auto layer      = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
  38     layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
  39
  40     if (layer->m_Param.m_BiasEnabled)
  41     {
  42         layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
  43     }
  44
  45     return std::move(layer);
  46 }
  47
  48 void DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs()
  49 {
  50     ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection() != nullptr,
  51                      "DepthwiseConvolution2dLayer: InputSlot must be connected to an OutputSlot");
  52     ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection()->IsTensorInfoSet(),
  53                      "DepthwiseConvolution2dLayer: TensorInfo must be set on connected OutputSlot.");
  54
  55     IOutputSlot* input = GetInputSlot(0).GetConnection();
  56     const TensorShape& inputShape = input->GetTensorInfo().GetShape();
  57     const TensorShape filterShape = m_Weight->GetTensorInfo().GetShape();
  58
  59     BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
  60
  61     unsigned int inWidth = inputShape[3];
  62     unsigned int inHeight = inputShape[2];
  63     unsigned int inBatchSize = inputShape[0];
  64
  65     unsigned int filterWidth = filterShape[3];
  66     unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - (filterWidth);
  67     unsigned int outWidth =  1+(readWidth / m_Param.m_StrideX);
  68
  69     unsigned int filterHeight = filterShape[2];
  70     unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - (filterHeight);
  71     unsigned int outHeight = 1+(readHeight / m_Param.m_StrideY);
  72     unsigned int depthMultiplier = filterShape[0];
  73
  74     unsigned int outChannels = filterShape[1]*depthMultiplier;
  75     unsigned int outBatchSize = inBatchSize;
  76
  77     TensorShape outShape({outBatchSize, outChannels, outHeight, outWidth});
  78     ConditionalThrowIfNotEqual<LayerValidationException>(
  79         "DepthwiseConvolution2dLayer: "
  80         "TensorShape set on OutputSlot[0] does not match the inferred shape.",
  81         GetOutputSlot(0).GetTensorInfo().GetShape(),
  82         outShape);
  83 }
  84
  85 } // namespace armnn