1 files changed, 11 insertions, 6 deletions
diff --git a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
index 4c453cc799..778d7b0814 100644
--- a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2017 Arm Ltd. All rights reserved.
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -25,33 +25,38 @@ TEST_CASE("ConvertConstantsHalfToFloatTest")
     std::vector<uint16_t> halfWeights(4);
     armnnUtils::FloatingPointConverter::ConvertFloat32To16(convWeightsData.data(), convWeightsData.size(),
                                                            halfWeights.data());
-    armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float16, 0.0f, 0, true), halfWeights);
+    armnn::TensorInfo weightInfo = armnn::TensorInfo(4, dims, armnn::DataType::Float16, 0.0f, 0, true);
+    armnn::ConstTensor weights(weightInfo, halfWeights);
 
     //Create the simple test network
     auto input = graph.AddLayer<armnn::InputLayer>(0, "input");
     input->GetOutputSlot().SetTensorInfo(info);
 
     auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
     fc->GetOutputSlot().SetTensorInfo(info);
 
+    auto weightsLayer = graph.AddLayer<armnn::ConstantLayer>("weights");
+    weightsLayer->m_LayerOutput = std::make_unique<armnn::ScopedTensorHandle>(weights);
+    weightsLayer->GetOutputSlot(0).SetTensorInfo(weightInfo);
+
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
 
     //Connect up the layers
     input->GetOutputSlot().Connect(fc->GetInputSlot(0));
+    weightsLayer->GetOutputSlot().Connect(fc->GetInputSlot(1));
     fc->GetOutputSlot().Connect(output->GetInputSlot(0));
 
     //Test the tensor info is correct.
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+    CHECK(weightsLayer->m_LayerOutput->GetTensorInfo().GetDataType() == armnn::DataType::Float16);
 
     // Run the optimizer
     armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsHalfToFloat()));
 
     //Test the tensor info is correct.
-    CHECK(fc->m_Weight->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
+    CHECK(weightsLayer->m_LayerOutput->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
 
     // Now test the data matches float32 data
-    const float* data = fc->m_Weight->GetConstTensor<float>();
+    const float* data = weightsLayer->m_LayerOutput->GetConstTensor<float>();
     CHECK(1.0f == data[0]);
     CHECK(2.0f == data[1]);
     CHECK(3.0f == data[2]);