IVGCVSW-3650 Add TfLite Parser support for Transpose Convolution layer
* Added ParseTransposeConv to TfLite Parser
* New TransposeConv test file
* Updated documentation for supported Transpose Convolution
Change-Id: Id7356d8525556805c164af693ae2b16f6a8492fa
Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index f345d4a..0e11a5c 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -460,6 +460,7 @@
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_TRANSPOSE_CONV] = &TfLiteParser::ParseTransposeConv;
m_ParserFunctions[tflite::BuiltinOperator_UNPACK] = &TfLiteParser::ParseUnpack;
}
@@ -737,7 +738,7 @@
auto filterTensorAndData = CreateConstTensor(inputs[1],
filterTensorInfo,
armnn::Optional<armnn::PermutationVector&>());
- armnn::IConnectableLayer* layer;
+ armnn::IConnectableLayer* layer = nullptr;
auto layerName = boost::str(boost::format("Conv2D:%1%:%2%") % subgraphIndex % operatorIndex);
@@ -826,7 +827,7 @@
desc.m_DilationX, desc.m_PadLeft, desc.m_PadRight, options->padding);
auto filterTensorAndData = CreateConstTensor(inputs[1], filterTensorInfo, permutationVector);
- armnn::IConnectableLayer* layer;
+ armnn::IConnectableLayer* layer = nullptr;
auto layerName = boost::str(boost::format("DepthwiseConv2D:%1%:%2%") % subgraphIndex % operatorIndex);
if (inputs.size() == 3)
@@ -864,6 +865,91 @@
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
+void TfLiteParser::ParseTransposeConv(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.AsTransposeConvOptions();
+
+ TransposeConvolution2dDescriptor desc;
+ desc.m_BiasEnabled = false;
+ desc.m_StrideX = CHECKED_NON_NEGATIVE(options->stride_w);
+ desc.m_StrideY = CHECKED_NON_NEGATIVE(options->stride_h);
+ desc.m_DataLayout = armnn::DataLayout::NHWC;
+
+ auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(inputs.size(), 2, 3);
+
+ auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
+ armnn::TensorInfo filterTensorInfo = ToTensorInfo(inputs[1]);
+
+ // TfLite uses NHWC tensors
+ const unsigned int inputHeight = inputTensorInfo.GetShape()[1];
+ const unsigned int inputWidth = inputTensorInfo.GetShape()[2];
+
+ const unsigned int filterHeight = filterTensorInfo.GetShape()[1];
+ const unsigned int filterWidth = filterTensorInfo.GetShape()[2];
+
+ CalcPadding(inputHeight,
+ filterHeight,
+ desc.m_StrideY,
+ 1, // DilationY
+ desc.m_PadTop,
+ desc.m_PadBottom,
+ options->padding);
+
+ CalcPadding(inputWidth,
+ filterWidth,
+ desc.m_StrideX,
+ 1, // DilationX
+ desc.m_PadLeft,
+ desc.m_PadRight,
+ options->padding);
+
+ auto filterTensorAndData = CreateConstTensor(inputs[1],
+ filterTensorInfo,
+ armnn::Optional<armnn::PermutationVector&>());
+
+ armnn::IConnectableLayer* layer = nullptr;
+ auto layerName = boost::str(boost::format("TransposeConv:%1%:%2%") % subgraphIndex % operatorIndex);
+
+ if (inputs.size() == 3)
+ {
+ desc.m_BiasEnabled = true;
+ armnn::TensorInfo biasTensorInfo = ToTensorInfo(inputs[2]);
+ auto biasTensorAndData = CreateConstTensor(inputs[2],
+ biasTensorInfo,
+ armnn::Optional<armnn::PermutationVector&>());
+ layer = m_Network->AddTransposeConvolution2dLayer(desc,
+ filterTensorAndData.first,
+ Optional<ConstTensor>(biasTensorAndData.first),
+ layerName.c_str());
+ }
+ else
+ {
+ layer = m_Network->AddTransposeConvolution2dLayer(desc,
+ filterTensorAndData.first,
+ EmptyOptional(),
+ layerName.c_str());
+ }
+
+ BOOST_ASSERT(layer != nullptr);
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ // only the tensors for the inputs are relevant, exclude the const (filter) tensor
+ 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::ParseAveragePool2D(size_t subgraphIndex, size_t operatorIndex)
{
ParsePool(subgraphIndex, operatorIndex, PoolingAlgorithm::Average);
@@ -1776,7 +1862,7 @@
auto filterTensorAndData = CreateConstTensor(inputs[1],
filterTensorInfo,
armnn::Optional<armnn::PermutationVector&>());
- armnn::IConnectableLayer* layer;
+ armnn::IConnectableLayer* layer = nullptr;
auto layerName = boost::str(boost::format("FullyConnected:%1%:%2%") % subgraphIndex % operatorIndex);
if (inputs.size() == 3)