commit 075c7504b6d6ecd50fa61ca53ab1bcccc8865843
author Matteo Martincigh <matteo.martincigh@arm.com> Wed Dec 05 13:10:45 2018 +0000
committer Matteo Martincigh <matteo.martincigh@arm.com> Wed Dec 05 13:56:16 2018 +0000
tree 6cf8009a0c63fc13927e8f8e11d5713683cf1d72
parent 4631582a4c8b92917633d0af4ebcc8fff2abd04a

IVGCVSW-2267 Remove the input swizzling from ParseFusedBatchNorm

 * Removed the input swizzling when the data layout is NHWC
 * Split the unit test into NHWC and NCHW cases

Change-Id: I6b9fef70bc4ba5e01d14cbfaea3c842a289b0a0e

src/armnnTfParser/TfParser.cpp

diff --git a/src/armnnTfParser/TfParser.cpp b/src/armnnTfParser/TfParser.cpp
index b40b054..73bdb65 100644
--- a/src/armnnTfParser/TfParser.cpp
+++ b/src/armnnTfParser/TfParser.cpp
@@ -1421,9 +1421,14 @@
     ParsedConstTfOperation<float>* varianceNode =
         boost::polymorphic_downcast<ParsedConstTfOperation<float> *>(inputs[4].m_IndexedValue);
 
+    const std::string dataFormat = ReadMandatoryNodeStringAttribute(nodeDef, "data_format");
+
+    CHECK_DATA_FORMAT(nodeDef, dataFormat, "FusedBatchNorm");
+
     // The descriptor only has the epsilon attribute.
     BatchNormalizationDescriptor desc;
     desc.m_Eps = ReadMandatoryNodeFloatAttribute(nodeDef, "epsilon");
+    desc.m_DataLayout = dataFormat == "NHWC" ? DataLayout::NHWC : DataLayout::NCHW;
 
     // Data for the parsed tensor args (scale, offset, mean, variance) must be stored
     // locally until the layer is added.
@@ -1448,19 +1453,8 @@
 
     IOutputSlot& inputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
 
-    const std::string dataFormat = ReadMandatoryNodeStringAttribute(nodeDef, "data_format");
-
-    if (dataFormat == "NHWC")
-    {
-        const TensorInfo outputTensorInfo = armnnUtils::Permuted(inputSlot.GetTensorInfo(), NHWCToArmNN);
-        layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-        layer = SwizzleInDeswizzleOut(*m_Network, inputSlot, *layer, nodeDef.name());
-    }
-    else
-    {
-        layer->GetOutputSlot(0).SetTensorInfo(inputSlot.GetTensorInfo());
-        inputSlot.Connect(layer->GetInputSlot(0));
-    }
+    layer->GetOutputSlot(0).SetTensorInfo(inputSlot.GetTensorInfo());
+    inputSlot.Connect(layer->GetInputSlot(0));
 
     return std::make_unique<SingleLayerParsedTfOperation>(this, nodeDef, layer);
 }