IVGCVSW-2848 - Add TfLite Parser support for Unpack layer
* Added ParseUnpack in TfLiteParser
* New Unpack test file with test reproducing unpack in DeepSpeechV1 model
* Added documentation for supported Unpack to TensorflorLiteSupport.md
Signed-off-by: Nina Drozd <nina.drozd@arm.com>
Change-Id: Ie920d46254ff4b4ab544407ace4c1d489af83157
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index f689dee..86688ad 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -468,6 +468,7 @@
m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParser::ParsePad;
m_ParserFunctions[tflite::BuiltinOperator_SPLIT] = &TfLiteParser::ParseSplit;
m_ParserFunctions[tflite::BuiltinOperator_TANH] = &TfLiteParser::ParseTanH;
+ m_ParserFunctions[tflite::BuiltinOperator_UNPACK] = &TfLiteParser::ParseUnpack;
}
void TfLiteParser::ResetParser()
@@ -1867,6 +1868,83 @@
outputTensorIndexes[3]});
}
+void TfLiteParser::ParseUnpack(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.AsUnpackOptions();
+
+ // This unpackAxis indicates the axis to unpack
+ const unsigned int unpackAxis = CHECKED_NON_NEGATIVE(options->axis);
+
+ auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(inputs.size(), 1);
+
+ armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
+ unsigned int unpackNum = CHECKED_NON_NEGATIVE(options->num);
+ // If num is not defined, automatically infer from the length of the dimension axis.
+ if(unpackNum == 0)
+ {
+ unpackNum = inputTensorInfo.GetShape()[unpackAxis];
+ }
+
+ // If unpack number cannot be inferred and is still zero, throw ParseException.
+ if(unpackNum == 0)
+ {
+ throw ParseException("Number to unpack must greater than zero.");
+ }
+
+ auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(outputs.size(), unpackNum);
+
+ auto inputDimSize = inputTensorInfo.GetNumDimensions();
+ std::vector<unsigned int> unpackDimSizes(inputDimSize);
+
+ // Add current input shape to unpackDimSizes
+ for (unsigned int i = 0; i < inputDimSize; ++i)
+ {
+ unpackDimSizes[i] = inputTensorInfo.GetShape()[i];
+ }
+
+ if (unpackDimSizes[unpackAxis] != unpackNum)
+ {
+ throw ParseException("Number to unpack must be the same as length of the dimension to "
+ "unpack along.");
+ }
+
+ unpackDimSizes[unpackAxis] /= unpackNum;
+
+ SplitterDescriptor splitDesc(unpackNum, static_cast<unsigned int>(unpackDimSizes.size()));
+ for (unsigned int j = 0; j < unpackNum; ++j)
+ {
+ // Set the size of the views.
+ for (unsigned int dimIdx = 0; dimIdx < unpackDimSizes.size(); ++dimIdx)
+ {
+ splitDesc.SetViewSize(j, dimIdx, unpackDimSizes[dimIdx]);
+ }
+ splitDesc.SetViewOriginCoord(j, unpackAxis, unpackDimSizes[unpackAxis] * j);
+ }
+
+ auto layerName = boost::str(boost::format("Unpack:%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>(unpackDimSizes.size()),
+ unpackDimSizes.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);
+}
+
void TfLiteParser::ParseSplit(size_t subgraphIndex, size_t operatorIndex)
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
@@ -1876,6 +1954,12 @@
const unsigned int numSplits = CHECKED_NON_NEGATIVE(options->num_splits);
+ // If number of splits cannot be inferred and is zero, throw ParseException.
+ if(numSplits == 0)
+ {
+ throw ParseException("Number to splits must greater than zero.");
+ }
+
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);