From cec6b655d9f6ddb73c721ca47a7d67eeaad5c043 Mon Sep 17 00:00:00 2001
From: Nikhil Raj <nikhil.raj@arm.com>
Date: Fri, 12 Oct 2018 13:51:57 +0100
Subject: IVGCVSW-1922 Unit test for DepthwiseConvolution with NHWC

Change-Id: I3e6e5b9a62f30d03c05bd7178adea8f4c8275da8
---
 src/armnn/layers/DepthwiseConvolution2dLayer.cpp |  2 --
 src/armnn/test/CreateWorkload.hpp                | 46 +++++++++++++-----------
 2 files changed, 25 insertions(+), 23 deletions(-)

(limited to 'src/armnn')

diff --git a/src/armnn/layers/DepthwiseConvolution2dLayer.cpp b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
index e1d433c640..393c4bf6f2 100644
--- a/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
+++ b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
@@ -29,8 +29,6 @@ std::unique_ptr<IWorkload> DepthwiseConvolution2dLayer::CreateWorkload(const Gra
 
     descriptor.m_Weight = m_Weight.get();
 
-    descriptor.m_DataLayout = GetParameters().m_DataLayout;
-
     if (m_Param.m_BiasEnabled)
     {
         BOOST_ASSERT_MSG(m_Bias != nullptr, "DepthwiseConvolution2dLayer: Bias data should not be null.");
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp
index a33189efeb..f3cf544fa3 100644
--- a/src/armnn/test/CreateWorkload.hpp
+++ b/src/armnn/test/CreateWorkload.hpp
@@ -397,52 +397,56 @@ std::unique_ptr<Convolution2dWorkload> CreateDirectConvolution2dWorkloadTest(arm
     return workload;
 }
 
-template <typename DepthwiseConvolution2dFloat32Workload>
+template <typename DepthwiseConvolution2dFloat32Workload, armnn::DataType DataType>
 std::unique_ptr<DepthwiseConvolution2dFloat32Workload> CreateDepthwiseConvolution2dWorkloadTest(
-    armnn::IWorkloadFactory& factory, armnn::Graph& graph)
+    armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW)
 {
     // Creates the layer we're testing.
     DepthwiseConvolution2dDescriptor layerDesc;
-    layerDesc.m_PadLeft         = 3;
-    layerDesc.m_PadRight        = 3;
+    layerDesc.m_PadLeft         = 1;
+    layerDesc.m_PadRight        = 2;
     layerDesc.m_PadTop          = 1;
-    layerDesc.m_PadBottom       = 1;
-    layerDesc.m_StrideX         = 2;
-    layerDesc.m_StrideY         = 4;
-    layerDesc.m_BiasEnabled     = true;
+    layerDesc.m_PadBottom       = 2;
+    layerDesc.m_StrideX         = 1;
+    layerDesc.m_StrideY         = 1;
+    layerDesc.m_BiasEnabled     = false;
+    layerDesc.m_DataLayout = dataLayout;
 
     DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer");
 
-    layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32));
-    layer->m_Bias   = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({9}, DataType::Float32));
+    layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({1, 4, 4, 2}, DataType));
     layer->m_Weight->Allocate();
-    layer->m_Bias->Allocate();
 
     // Creates extra layers.
     Layer* const input = graph.AddLayer<InputLayer>(0, "input");
     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
 
+    TensorShape inputShape = (dataLayout == DataLayout::NCHW) ?
+                TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
+    TensorShape outputShape = (dataLayout == DataLayout::NCHW) ?
+                TensorShape{ 2, 2, 5, 5 } : TensorShape{ 2, 5, 5, 2 };
+
     // Connects up.
-    Connect(input, layer, TensorInfo({2, 3, 8, 16}, armnn::DataType::Float32));
-    Connect(layer, output, TensorInfo({2, 9, 2, 10}, armnn::DataType::Float32));
+    Connect(input, layer, TensorInfo(inputShape, DataType));
+    Connect(layer, output, TensorInfo(outputShape, DataType));
     CreateTensorHandles(graph, factory);
 
     // Makes the workload and checks it.
     auto workload = MakeAndCheckWorkload<DepthwiseConvolution2dFloat32Workload>(*layer, graph, factory);
 
     DepthwiseConvolution2dQueueDescriptor queueDescriptor = workload->GetData();
-    BOOST_TEST(queueDescriptor.m_Parameters.m_StrideX == 2);
-    BOOST_TEST(queueDescriptor.m_Parameters.m_StrideY == 4);
-    BOOST_TEST(queueDescriptor.m_Parameters.m_PadLeft == 3);
-    BOOST_TEST(queueDescriptor.m_Parameters.m_PadRight == 3);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_StrideX == 1);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_StrideY == 1);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_PadLeft == 1);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_PadRight == 2);
     BOOST_TEST(queueDescriptor.m_Parameters.m_PadTop == 1);
-    BOOST_TEST(queueDescriptor.m_Parameters.m_PadBottom == 1);
-    BOOST_TEST(queueDescriptor.m_Parameters.m_BiasEnabled == true);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_PadBottom == 2);
+    BOOST_TEST(queueDescriptor.m_Parameters.m_BiasEnabled == false);
+    BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout == dataLayout));
 
     BOOST_TEST(queueDescriptor.m_Inputs.size() == 1);
     BOOST_TEST(queueDescriptor.m_Outputs.size() == 1);
-    BOOST_TEST((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({3, 3, 5, 3}, DataType::Float32)));
-    BOOST_TEST((queueDescriptor.m_Bias->GetTensorInfo() == TensorInfo({9}, DataType::Float32)));
+    BOOST_TEST((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo({1, 4, 4, 2}, DataType)));
 
     // Returns so we can do extra, backend-specific tests.
     return workload;
-- 
cgit v1.2.1