1 files changed, 53 insertions, 0 deletions
diff --git a/src/backends/neon/workloads/NeonMeanWorkload.cpp b/src/backends/neon/workloads/NeonMeanWorkload.cpp
new file mode 100644
index 0000000000..d736e42e0e
--- /dev/null
+++ b/src/backends/neon/workloads/NeonMeanWorkload.cpp
@@ -0,0 +1,53 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonMeanWorkload.hpp"
+
+#include <aclCommon/ArmComputeTensorUtils.hpp>
+
+#include <neon/NeonTensorHandle.hpp>
+
+#include "NeonWorkloadUtils.hpp"
+
+namespace armnn
+{
+using namespace armcomputetensorutils;
+
+arm_compute::Status NeonMeanWorkloadValidate(const TensorInfo& input,
+                                             const TensorInfo& output,
+                                             const MeanDescriptor& desc)
+{
+    const arm_compute::TensorInfo aclInputInfo  = armcomputetensorutils::BuildArmComputeTensorInfo(input);
+    const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
+
+    arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
+                                                                          input.GetNumDimensions(),
+                                                                          desc.m_Axis);
+
+    return arm_compute::NEReduceMean::validate(&aclInputInfo, coords, desc.m_KeepDims, &aclOutputInfo);
+}
+
+NeonMeanWorkload::NeonMeanWorkload(const MeanQueueDescriptor& descriptor, const WorkloadInfo& info)
+    : BaseWorkload<MeanQueueDescriptor>(descriptor, info)
+{
+    m_Data.ValidateInputsOutputs("NeonMeanWorkload", 1, 1);
+
+    arm_compute::ITensor& input  = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ITensor& output = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(input.info()->num_dimensions(),
+                                                                          info.m_InputTensorInfos[0].GetNumDimensions(),
+                                                                          m_Data.m_Parameters.m_Axis);
+
+    m_Layer.configure(&input, coords, m_Data.m_Parameters.m_KeepDims, &output);
+}
+
+void NeonMeanWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonMeanWorkload_Execute");
+    m_Layer.run();
+}
+
+} //namespace armnn