1 files changed, 49 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 4acd30805e..31aab029ab 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -419,6 +419,7 @@ TfLiteParser::TfLiteParser()
 {
     // register supported operators
     m_ParserFunctions[tflite::BuiltinOperator_AVERAGE_POOL_2D]   =  &TfLiteParser::ParseAveragePool2D;
+    m_ParserFunctions[tflite::BuiltinOperator_BATCH_TO_SPACE_ND] =  &TfLiteParser::ParseBatchToSpaceND;
     m_ParserFunctions[tflite::BuiltinOperator_CONCATENATION]     =  &TfLiteParser::ParseConcatenation;
     m_ParserFunctions[tflite::BuiltinOperator_CONV_2D]           =  &TfLiteParser::ParseConv2D;
     m_ParserFunctions[tflite::BuiltinOperator_DEPTHWISE_CONV_2D] =  &TfLiteParser::ParseDepthwiseConv2D;
@@ -836,6 +837,54 @@ void TfLiteParser::ParseAveragePool2D(size_t subgraphIndex, size_t operatorIndex
     ParsePool(subgraphIndex, operatorIndex, PoolingAlgorithm::Average);
 }
 
+void TfLiteParser::ParseBatchToSpaceND(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 3);
+
+    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    armnn::TensorInfo blockShapeTensorInfo = ToTensorInfo(inputs[1]);
+    BufferRawPtr blockShapeBufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
+
+    armnn::TensorInfo cropsTensorInfo = ToTensorInfo(inputs[2]);
+    BufferRawPtr cropsBufferPtr = GetBuffer(m_Model, inputs[2]->buffer);
+
+    std::vector<unsigned int> blockShape(blockShapeTensorInfo.GetNumElements());
+    ::memcpy(blockShape.data(), blockShapeBufferPtr->data.data(), blockShapeTensorInfo.GetNumBytes());
+
+    std::vector<unsigned int> cropsVector(cropsTensorInfo.GetNumElements());
+    ::memcpy(cropsVector.data(), cropsBufferPtr->data.data(), cropsTensorInfo.GetNumBytes());
+
+    size_t step = 2;
+    std::vector<std::pair<unsigned int, unsigned int>> crops;
+    for (unsigned int i = 0; i < cropsTensorInfo.GetNumElements() / step; ++i)
+    {
+        crops.emplace_back(cropsVector[i * step], cropsVector[i * step + 1]);
+    }
+
+    armnn::BatchToSpaceNdDescriptor desc;
+    desc.m_BlockShape = blockShape;
+    desc.m_Crops = crops;
+    desc.m_DataLayout = armnn::DataLayout::NHWC;
+
+    armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+
+    auto layerName = boost::str(boost::format("BatchToSpaceND:%1%:%2%") % subgraphIndex % operatorIndex);
+    IConnectableLayer* layer = m_Network->AddBatchToSpaceNdLayer(desc, layerName.c_str());
+
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
 void TfLiteParser::ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex)
 {
     ParsePool(subgraphIndex, operatorIndex, PoolingAlgorithm::Max);