IVGCVSW-6147 ConstTensorsAsInput: Optimizer - FusePermuteIntoConstLayer

  * No trailing permute layer after a constant layer
  * Unit test for optimization

Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I0d098f5af41d2c55df7cef1ccfb848093320ddc1

1 files changed, 16 insertions, 7 deletions

diff --git a/src/armnnOnnxParser/OnnxParser.cpp b/src/armnnOnnxParser/OnnxParser.cpp
index 4eaf63653b..60bd962db7 100644
--- a/src/armnnOnnxParser/OnnxParser.cpp
+++ b/src/armnnOnnxParser/OnnxParser.cpp
@@ -1043,15 +1043,24 @@ void OnnxParserImpl::AddConvLayerWithDepthwiseConv(const onnx::NodeProto& node,
     desc.m_BiasEnabled  = convDesc.m_BiasEnabled;
 
     armnn::IConnectableLayer* layer = m_Network->AddDepthwiseConvolution2dLayer(desc, node.name().c_str());
-    std::vector<std::string> tensorIndexes= {node.input(0), node.input(1)};
-
-    // weights come in as [O,1,H,W] from ONNX and need to be converted to ArmNNs dephtwise weights layout [1,H,W,O]
-    armnn::PermutationVector perVec {3,0,1,2};
-    auto weightTensor = CreateConstTensor(node.input(1), perVec);
+    std::string permuteStr = "permute_" + node.input(1);
+    std::vector<std::string> tensorIndexes= {node.input(0), permuteStr};
 
+    auto weightTensor = CreateConstTensor(node.input(1));
     IConnectableLayer* weightsLayer = m_Network->AddConstantLayer(weightTensor.first);
+
+    // weights come in as [O,1,H,W] from ONNX and need to be converted to ArmNNs depthwise weights layout [1,H,W,O]
+    armnn::PermutationVector perVec {3, 0, 1, 2};
+    TensorInfo weightsPermuted = armnnUtils::Permuted(weightTensor.first.GetInfo(), perVec);
+
+    // Inserts NewLayer so layers don't need to be re-sorted.
+    IConnectableLayer* permuteLayer = m_Network->AddPermuteLayer(PermuteDescriptor(perVec),
+                                                                 "permute_layer");
+    permuteLayer->GetOutputSlot(0).SetTensorInfo(weightsPermuted);
+    permuteLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u));
+
     weightsLayer->GetOutputSlot(0).SetTensorInfo(weightTensor.first.GetInfo());
-    weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u));
+    weightsLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0u));
 
     if (node.input_size() == 3)
     {
@@ -1076,7 +1085,7 @@ void OnnxParserImpl::AddConvLayerWithDepthwiseConv(const onnx::NodeProto& node,
 
     auto outputInfo = ComputeOutputInfo({ node.output(0) }, layer,
                                         { m_TensorsInfo[node.input(0)].m_info->GetShape(),
-                                          weightTensor.first.GetInfo().GetShape() });
+                                          weightsPermuted.GetShape() });
 
     layer->GetOutputSlot(0).SetTensorInfo(outputInfo[0]);