1 files changed, 1 insertions, 54 deletions

diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index a042939265..43a8aae9a7 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -417,7 +417,7 @@ TEST_CASE("SerializeConvolution2d")
     deserializedNetwork->ExecuteStrategy(verifier);
 }
 
-TEST_CASE("SerializeConvolution2dWithPerAxisParams")
+TEST_CASE("SerializeConvolution2dWithPerAxisParamsTestDeprecatedMethod")
 {
     using namespace armnn;
 
@@ -521,59 +521,6 @@ TEST_CASE("SerializeConvolution2dWeightsAndBiasesAsConstantLayers")
     armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
     CHECK(deserializedNetwork);
 
-    Convolution2dLayerVerifier verifier(layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor);
-
-    deserializedNetwork->ExecuteStrategy(verifier);
-}
-
-TEST_CASE("SerializeConvolution2dWeightsAndBiasesAsConstantLayers")
-{
-    const std::string layerName("convolution2d");
-    const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
-    const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
-
-    const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true);
-    const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true);
-
-    std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
-    armnn::ConstTensor weights(weightsInfo, weightsData);
-
-    std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
-    armnn::ConstTensor biases(biasesInfo, biasesData);
-
-    armnn::Convolution2dDescriptor descriptor;
-    descriptor.m_PadLeft     = 1;
-    descriptor.m_PadRight    = 1;
-    descriptor.m_PadTop      = 1;
-    descriptor.m_PadBottom   = 1;
-    descriptor.m_StrideX     = 2;
-    descriptor.m_StrideY     = 2;
-    descriptor.m_DilationX   = 2;
-    descriptor.m_DilationY   = 2;
-    descriptor.m_BiasEnabled = true;
-    descriptor.m_DataLayout  = armnn::DataLayout::NHWC;
-
-    armnn::INetworkPtr network = armnn::INetwork::Create();
-    armnn::IConnectableLayer* const inputLayer  = network->AddInputLayer(0);
-    armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "Weights");
-    armnn::IConnectableLayer* const biasesLayer = network->AddConstantLayer(biases, "Biases");
-    armnn::IConnectableLayer* const convLayer   = network->AddConvolution2dLayer(descriptor,
-                                           layerName.c_str());
-    armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
-    inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
-    weightsLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1));
-    biasesLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
-    convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
-    inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-    weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
-    biasesLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
-    convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-
-    armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
-    CHECK(deserializedNetwork);
-
     const std::vector<armnn::ConstTensor>& constants {weights, biases};
     LayerVerifierBaseWithDescriptorAndConstants<armnn::Convolution2dDescriptor> verifier(
             layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants);