1 files changed, 85 insertions, 0 deletions
diff --git a/src/armnn/layers/DepthwiseConvolution2dLayer.cpp b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
new file mode 100644
index 0000000000..0442de6c60
--- /dev/null
+++ b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
@@ -0,0 +1,85 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+#include "DepthwiseConvolution2dLayer.hpp"
+
+#include "LayerCloneBase.hpp"
+
+#include <armnn/TypesUtils.hpp>
+#include <backends/CpuTensorHandle.hpp>
+#include <backends/WorkloadFactory.hpp>
+
+namespace armnn
+{
+
+DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor& param,
+                                                         const char* name)
+    : LayerWithParameters(1, 1, LayerType::DepthwiseConvolution2d, param, name)
+{
+}
+
+std::unique_ptr<IWorkload> DepthwiseConvolution2dLayer::CreateWorkload(const Graph&                  graph,
+                                                                       const IWorkloadFactory& factory) const
+{
+    DepthwiseConvolution2dQueueDescriptor descriptor;
+
+    descriptor.m_Weight = m_Weight.get();
+    if (m_Param.m_BiasEnabled)
+    {
+        descriptor.m_Bias = m_Bias.get();
+    }
+    return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor, graph));
+}
+
+DepthwiseConvolution2dLayer* DepthwiseConvolution2dLayer::Clone(Graph& graph) const
+{
+    auto layer      = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
+    layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
+
+    if (layer->m_Param.m_BiasEnabled)
+    {
+        layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
+    }
+
+    return std::move(layer);
+}
+
+void DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs()
+{
+    ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection() != nullptr,
+                     "DepthwiseConvolution2dLayer: InputSlot must be connected to an OutputSlot");
+    ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection()->IsTensorInfoSet(),
+                     "DepthwiseConvolution2dLayer: TensorInfo must be set on connected OutputSlot.");
+
+    IOutputSlot* input = GetInputSlot(0).GetConnection();
+    const TensorShape& inputShape = input->GetTensorInfo().GetShape();
+    const TensorShape filterShape = m_Weight->GetTensorInfo().GetShape();
+
+    BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
+
+    unsigned int inWidth = inputShape[3];
+    unsigned int inHeight = inputShape[2];
+    unsigned int inBatchSize = inputShape[0];
+
+    unsigned int filterWidth = filterShape[3];
+    unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - (filterWidth);
+    unsigned int outWidth =  1+(readWidth / m_Param.m_StrideX);
+
+    unsigned int filterHeight = filterShape[2];
+    unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - (filterHeight);
+    unsigned int outHeight = 1+(readHeight / m_Param.m_StrideY);
+    unsigned int depthMultiplier = filterShape[0];
+
+    unsigned int outChannels = filterShape[1]*depthMultiplier;
+    unsigned int outBatchSize = inBatchSize;
+
+    TensorShape outShape({outBatchSize, outChannels, outHeight, outWidth});
+    ConditionalThrowIfNotEqual<LayerValidationException>(
+        "DepthwiseConvolution2dLayer: "
+        "TensorShape set on OutputSlot[0] does not match the inferred shape.",
+        GetOutputSlot(0).GetTensorInfo().GetShape(),
+        outShape);
+}
+
+} // namespace armnn