Add space-to-batch-nd parser to tf-lite
Change-Id: I3bf86d44f811380559ec35eed0bc43b3bd97da80
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 31aab02..e19edc3 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -432,6 +432,7 @@
m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParser::ParseReshape;
m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR] = &TfLiteParser::ParseResizeBilinear;
m_ParserFunctions[tflite::BuiltinOperator_SOFTMAX] = &TfLiteParser::ParseSoftmax;
+ m_ParserFunctions[tflite::BuiltinOperator_SPACE_TO_BATCH_ND] = &TfLiteParser::ParseSpaceToBatchND;
m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE] = &TfLiteParser::ParseSqueeze;
m_ParserFunctions[tflite::BuiltinOperator_SUB] = &TfLiteParser::ParseSub;
m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParser::ParseAdd;
@@ -990,6 +991,54 @@
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
+void TfLiteParser::ParseSpaceToBatchND(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 padListTensorInfo = ToTensorInfo(inputs[2]);
+ BufferRawPtr padListBufferPtr = 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> padListVector(padListTensorInfo.GetNumElements());
+ ::memcpy(padListVector.data(), padListBufferPtr->data.data(), padListTensorInfo.GetNumBytes());
+
+ size_t step = 2;
+ std::vector<std::pair<unsigned int, unsigned int>> padList;
+ for (unsigned int i = 0; i < padListTensorInfo.GetNumElements() / step; ++i)
+ {
+ padList.emplace_back(padListVector[i * step], padListVector[i * step + 1]);
+ }
+
+ armnn::SpaceToBatchNdDescriptor desc;
+ desc.m_BlockShape = blockShape;
+ desc.m_PadList = padList;
+ desc.m_DataLayout = armnn::DataLayout::NHWC;
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+
+ auto layerName = boost::str(boost::format("SpaceToBatchND:%1%:%2%") % subgraphIndex % operatorIndex);
+ IConnectableLayer* layer = m_Network->AddSpaceToBatchNdLayer(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]});
+}
+
armnn::TensorInfo TfLiteParser::OutputShapeOfSqueeze(const std::vector<uint32_t> & squeezeDimsIn,
const armnn::TensorInfo & inputTensorInfo)
{