1 files changed, 67 insertions, 0 deletions
diff --git a/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp b/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp
new file mode 100644
index 0000000000..a6e7aa4415
--- /dev/null
+++ b/src/backends/neon/workloads/NeonBatchToSpaceNdWorkload.cpp
@@ -0,0 +1,67 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonBatchToSpaceNdWorkload.hpp"
+
+#include "NeonWorkloadUtils.hpp"
+#include <ResolveType.hpp>
+
+namespace armnn
+{
+
+using namespace armcomputetensorutils;
+
+arm_compute::Status NeonBatchToSpaceNdWorkloadValidate(const TensorInfo& input,
+                                                       const TensorInfo& output,
+                                                       const BatchToSpaceNdDescriptor& desc)
+{
+    const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, desc.m_DataLayout);
+    const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, desc.m_DataLayout);
+
+    // ArmNN blockShape is [H, W] Cl asks for W, H
+    int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_BlockShape[0]);
+    int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_BlockShape[1]);
+
+    const arm_compute::Status aclStatus = arm_compute::NEBatchToSpaceLayer::validate(&aclInputInfo,
+                                                                                     blockWidth,
+                                                                                     blockHeight,
+                                                                                     &aclOutputInfo);
+    return aclStatus;
+}
+
+NeonBatchToSpaceNdWorkload::NeonBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& desc,
+                                                       const WorkloadInfo& info)
+    : BaseWorkload<BatchToSpaceNdQueueDescriptor>(desc, info)
+{
+    m_Data.ValidateInputsOutputs("NeonBatchToSpaceNdWorkload", 1, 1);
+
+    arm_compute::ITensor& input  =
+            boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ITensor& output =
+            boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor();
+
+    arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
+    input.info()->set_data_layout(aclDataLayout);
+    output.info()->set_data_layout(aclDataLayout);
+
+    // ArmNN blockShape is [H, W] Cl asks for W, H
+    int32_t blockHeight = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[0]);
+    int32_t blockWidth = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockShape[1]);
+
+    m_Layer.reset(new arm_compute::NEBatchToSpaceLayer());
+    m_Layer->configure(&input, blockWidth, blockHeight, &output);
+    m_Layer->prepare();
+}
+
+void NeonBatchToSpaceNdWorkload::Execute() const
+{
+    if (m_Layer)
+    {
+        ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonSpaceToBatchNdWorkload_Execute");
+        m_Layer->run();
+    }
+}
+
+} //namespace armnn