1 files changed, 85 insertions, 0 deletions
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index fc6d3653..946bc95d 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -1800,5 +1800,90 @@ bool ConvertSub(const Operation& operation, const Model& model, ConversionData&
     return Fail("%s: ProcessActivation failed", __func__);
 }
 
+template<typename HalPolicy,
+         typename HalOperation   = typename HalPolicy::Operation,
+         typename HalModel       = typename HalPolicy::Model>
+bool ConvertBatchToSpaceNd(const HalOperation& operation,
+                           const HalModel& model,
+                           ConversionData& data)
+{
+    using HalOperand     = typename HalPolicy::Operand;
+    using HalOperandType = typename HalPolicy::OperandType;
+
+    LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+    if (!input.IsValid())
+    {
+        return Fail("%s: Operation has invalid inputs", __func__);
+    }
+
+    const HalOperand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+    if (!output)
+    {
+        return Fail("%s: Could not read output 0", __func__);
+    }
+
+    const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+    if (IsDynamicTensor(outputInfo))
+    {
+        return Fail("%s: Dynamic output tensors are not supported", __func__);
+    }
+
+    const HalOperand* blockOperand = GetInputOperand<HalPolicy>(operation, 1, model);
+    if (!blockOperand)
+    {
+        return Fail("%s: Could not read input 1", __func__);
+    }
+
+    // Convert the block operand to int32
+    std::vector<int32_t> block;
+    if (!GetTensorInt32Values<HalPolicy>(*blockOperand, block, model, data))
+    {
+        return Fail("%s: Input 1 has invalid values", __func__);
+    }
+
+    const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
+
+    unsigned int rank = inputInfo.GetNumDimensions();
+    if (rank != 4)
+    {
+        Fail("%s: Only inputs with rank equal to 4 are supported", __func__);
+    }
+
+    if (std::any_of(block.cbegin(), block.cend(), [](int32_t i){ return i < 1; }))
+    {
+        return Fail("%s: Block sizes for each spatial dimension of the input tensor must be"
+                    " greater than or equal to 1", __func__);
+    }
+
+    armnn::BatchToSpaceNdDescriptor batchToSpaceNdDesc;
+    batchToSpaceNdDesc.m_BlockShape.assign(block.cbegin(), block.cend());
+    batchToSpaceNdDesc.m_DataLayout = armnn::DataLayout::NHWC;
+
+    if (Is12Operand(*output))
+    {
+        batchToSpaceNdDesc.m_DataLayout = OptionalDataLayout<HalPolicy>(operation, 3, model, data);
+    }
+    // Setting crops to 0,0 0,0 as it is not supported in Android NN API
+    batchToSpaceNdDesc.m_Crops = {{0, 0}, {0, 0}};
+
+    bool isSupported = false;
+    FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                               IsBatchToSpaceNdSupported,
+                               data.m_Backends,
+                               isSupported,
+                               inputInfo,
+                               outputInfo,
+                               batchToSpaceNdDesc);
+    if (!isSupported)
+    {
+        return false;
+    }
+
+    armnn::IConnectableLayer* const layer = data.m_Network->AddBatchToSpaceNdLayer(batchToSpaceNdDesc);
+    assert(layer != nullptr);
+    input.Connect(layer->GetInputSlot(0));
+
+    return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
 
 } // namespace armnn_driver