1 files changed, 89 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index b9a3522736..c00c2188a9 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -464,6 +464,7 @@ TfLiteParser::TfLiteParser()
     m_ParserFunctions[tflite::BuiltinOperator_MUL]               =  &TfLiteParser::ParseMul;
     m_ParserFunctions[tflite::BuiltinOperator_MEAN]              =  &TfLiteParser::ParseMean;
     m_ParserFunctions[tflite::BuiltinOperator_PAD]               =  &TfLiteParser::ParsePad;
+    m_ParserFunctions[tflite::BuiltinOperator_SPLIT]             =  &TfLiteParser::ParseSplit;
 }
 
 void TfLiteParser::ResetParser()
@@ -1851,6 +1852,94 @@ void TfLiteParser::ParseDetectionPostProcess(size_t subgraphIndex, size_t operat
                                                               outputTensorIndexes[3]});
 }
 
+void TfLiteParser::ParseSplit(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+    const auto * options = operatorPtr->builtin_options.AsSplitOptions();
+
+    const unsigned int numSplits = CHECKED_NON_NEGATIVE(options->num_splits);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 2);
+    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), numSplits);
+
+    armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[0]);
+    armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[1]);
+
+    // This splitDim indicates the data format: 3 is the NHWC, 1 is the NCHW.
+    const unsigned int splitDim = static_cast<unsigned int>(axisTensorInfo.GetShape()[0]);
+
+    // Armnn supports split along the channel dimension for data formats NHWC and NCHW.
+    if (splitDim == 0 || splitDim == 2)
+    {
+        throw ParseException(
+            boost::str(
+                boost::format(
+                    "Dimension %1% for split is not supported by Armnn. %2%")
+                    % splitDim
+                    % CHECK_LOCATION().AsString()));
+    }
+
+    auto inputDimSize = inputTensorInfo.GetNumDimensions();
+    if (inputDimSize != MaxNumOfTensorDimensions)
+    {
+        throw ParseException(
+            boost::str(
+                boost::format(
+                    "The number of dimensions: %1% for input tensors of the "
+                    "split op should be %2% %3%")
+                    % inputTensorInfo.GetNumDimensions()
+                    % MaxNumOfTensorDimensions
+                    % CHECK_LOCATION().AsString()));
+    }
+
+    std::vector<unsigned int> splitterDimSizes(inputDimSize);
+
+    // Add current input shape to splitterDimSizes
+    for (unsigned int i = 0; i < inputDimSize; ++i)
+    {
+        splitterDimSizes[i] = inputTensorInfo.GetShape()[i];
+    }
+
+    if (splitterDimSizes[splitDim] % numSplits != 0)
+    {
+        throw ParseException("Number of splits must evenly divide the dimension");
+    }
+    splitterDimSizes[splitDim] /= numSplits;
+
+    SplitterDescriptor splitDesc(numSplits);
+    for (unsigned int j = 0; j < numSplits; ++j)
+    {
+        // Set the size of the views.
+        for (unsigned int dimIdx = 0; dimIdx < splitterDimSizes.size(); ++dimIdx)
+        {
+            splitDesc.SetViewSize(j, dimIdx, splitterDimSizes[dimIdx]);
+        }
+        splitDesc.SetViewOriginCoord(j, splitDim, splitterDimSizes[splitDim] * j);
+    }
+
+    auto layerName = boost::str(boost::format("Split:%1%:%2%") % subgraphIndex % operatorIndex);
+    IConnectableLayer* layer = m_Network->AddSplitterLayer(splitDesc, layerName.c_str());
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+    TensorShape outShape = TensorShape(static_cast<unsigned int>(splitterDimSizes.size()),
+                                       splitterDimSizes.data());
+
+    for (unsigned int k = 0; k < layer->GetNumOutputSlots(); ++k)
+    {
+        layer->GetOutputSlot(k).SetTensorInfo(armnn::TensorInfo(outShape,
+                                                                inputTensorInfo.GetDataType()));
+    }
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
+}
+
 armnn::IConnectableLayer* TfLiteParser::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer,
                                                                 unsigned int outputSlot,
                                                                 tflite::ActivationFunctionType activationType)