1 files changed, 57 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/RefStackWorkload.cpp b/src/backends/reference/workloads/RefStackWorkload.cpp
new file mode 100644
index 0000000000..be36f40633
--- /dev/null
+++ b/src/backends/reference/workloads/RefStackWorkload.cpp
@@ -0,0 +1,57 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefStackWorkload.hpp"
+
+#include "RefWorkloadUtils.hpp"
+#include "Stack.hpp"
+
+#include <Profiling.hpp>
+
+namespace armnn
+{
+
+RefStackWorkload::RefStackWorkload(const StackQueueDescriptor& descriptor,
+                                   const WorkloadInfo& info)
+    : BaseWorkload(descriptor, info)
+{}
+
+void RefStackWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefStackWorkload_Execute");
+
+    // Can perform a simple concatenation when axis == 0
+    if (!m_Data.m_Parameters.m_Axis)
+    {
+        float* output = GetOutputTensorData<float>(0, m_Data);
+        BOOST_ASSERT(output != nullptr);
+
+        unsigned int numInputs = m_Data.m_Parameters.m_NumInputs;
+        unsigned int inputLength = GetTensorInfo(m_Data.m_Inputs[0]).GetNumElements();
+
+        for (unsigned int inputIdx=0; inputIdx<numInputs; ++inputIdx)
+        {
+            const float* input = GetInputTensorData<float>(inputIdx, m_Data);
+            for (unsigned int elmt=0; elmt<inputLength; ++elmt)
+            {
+                output[(inputIdx * inputLength) + elmt] = input[elmt];
+            }
+        }
+        return;
+    }
+
+    std::vector<std::unique_ptr<Decoder<float>>> inputDecoders;
+    for (unsigned int i=0; i<m_Data.m_Inputs.size(); ++i)
+    {
+        inputDecoders.push_back(MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[i]),
+                                                   m_Data.m_Inputs[i]->Map()));
+    }
+    std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]),
+                                                                       m_Data.m_Outputs[0]->Map());
+
+    Stack(m_Data, inputDecoders, *outputEncoder);
+}
+
+} // namespace armnn