1 files changed, 16 insertions, 9 deletions
diff --git a/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp b/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp
index b9736db642..8eef587644 100644
--- a/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp
+++ b/src/backends/cl/workloads/ClBatchToSpaceNdWorkload.cpp
@@ -17,11 +17,17 @@ namespace armnn
 {
 using namespace armcomputetensorutils;
 
-ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& desc,
+ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& descriptor,
                                                    const WorkloadInfo& info,
                                                    const arm_compute::CLCompileContext& clCompileContext)
-   : BaseWorkload<BatchToSpaceNdQueueDescriptor>(desc, info)
+    : BaseWorkload<BatchToSpaceNdQueueDescriptor>(descriptor, info)
 {
+    // Report Profiling Details
+    ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClBatchToSpaceWorkload_Construct",
+                                         descriptor.m_Parameters,
+                                         info,
+                                         this->GetGuid());
+
     m_Data.ValidateInputsOutputs("ClBatchToSpaceNdWorkload", 1, 1);
 
     arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
@@ -30,8 +36,8 @@ ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDesc
     input.info()->set_data_layout(aclDataLayout);
 
     // ArmNN blockShape is [H, W] Cl asks for W, H
-    int32_t blockHeight = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[0]);
-    int32_t blockWidth = armnn::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[1]);
+    int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[0]);
+    int32_t blockWidth = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[1]);
 
     arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
     output.info()->set_data_layout(aclDataLayout);
@@ -41,19 +47,20 @@ ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDesc
 
 void ClBatchToSpaceNdWorkload::Execute() const
 {
-    ARMNN_SCOPED_PROFILING_EVENT_CL("ClBatchToSpaceNdWorkload_Execute");
+    ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClBatchToSpaceNdWorkload_Execute", this->GetGuid());
     RunClFunction(m_Layer, CHECK_LOCATION());
 }
 
 arm_compute::Status ClBatchToSpaceNdWorkloadValidate(const TensorInfo& input,
                                                      const TensorInfo& output,
-                                                     const BatchToSpaceNdDescriptor& desc) {
-    DataLayout dataLayout = desc.m_DataLayout;
+                                                     const BatchToSpaceNdDescriptor& descriptor)
+{
+    DataLayout dataLayout = descriptor.m_DataLayout;
     const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, dataLayout);
 
     // ArmNN blockShape is [H, W] Cl asks for W, H
-    int32_t blockHeight = armnn::numeric_cast<int32_t>(desc.m_BlockShape[0]);
-    int32_t blockWidth = armnn::numeric_cast<int32_t>(desc.m_BlockShape[1]);
+    int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[0]);
+    int32_t blockWidth = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[1]);
 
     const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, dataLayout);