GitHub #603 Add PADV2 support to TFLite Parser
* Added PADV2 support to TFLite Parser
* Added PADV2 unit tests
* Updated Parser Docs
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I06ea9a6ceddc38cdb89204c019432257d3f58e4c
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 5368401..d0a2d90 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -694,6 +694,7 @@
src/armnnTfLiteParser/test/Multiplication.cpp
src/armnnTfLiteParser/test/Pack.cpp
src/armnnTfLiteParser/test/Pad.cpp
+ src/armnnTfLiteParser/test/PadV2.cpp
src/armnnTfLiteParser/test/Prelu.cpp
src/armnnTfLiteParser/test/Reduce.cpp
src/armnnTfLiteParser/test/Reshape.cpp
diff --git a/docs/05_01_parsers.dox b/docs/05_01_parsers.dox
index e7124ce..a4526e0 100644
--- a/docs/05_01_parsers.dox
+++ b/docs/05_01_parsers.dox
@@ -155,6 +155,7 @@
- NOT_EQUAL
- PACK
- PAD
+- PADV2
- PRELU
- QUANTIZE
- RELU
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index f51cf50..81cbb9c 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -76,7 +76,7 @@
return pTfLiteParserImpl->CreateNetworkFromBinaryFile(graphFile);
}
-armnn::INetworkPtr ITfLiteParser::CreateNetworkFromBinary(const std::vector<uint8_t> & binaryContent)
+armnn::INetworkPtr ITfLiteParser::CreateNetworkFromBinary(const std::vector<uint8_t>& binaryContent)
{
return pTfLiteParserImpl->CreateNetworkFromBinary(binaryContent);
}
@@ -113,9 +113,9 @@
const uint32_t VIRTUAL_OPERATOR_ID = std::numeric_limits<uint32_t>::max();
-void CheckSubgraph(const TfLiteParserImpl::ModelPtr & model,
+void CheckSubgraph(const TfLiteParserImpl::ModelPtr& model,
size_t subgraphIndex,
- const CheckLocation & location)
+ const CheckLocation& location)
{
if (model.get() == nullptr)
{
@@ -141,10 +141,10 @@
#define CHECK_SUBGRAPH(MODEL, SUBGRAPH_INDEX) \
CheckSubgraph(MODEL, SUBGRAPH_INDEX, CHECK_LOCATION())
-void CheckModel(const TfLiteParserImpl::ModelPtr & model,
+void CheckModel(const TfLiteParserImpl::ModelPtr& model,
size_t subgraphIndex,
size_t operatorIndex,
- const CheckLocation & location)
+ const CheckLocation& location)
{
if (model.get() == nullptr)
{
@@ -183,10 +183,10 @@
#define CHECK_MODEL(MODEL, SUBGRAPH_INDEX, OPERATOR_INDEX) \
CheckModel(MODEL, SUBGRAPH_INDEX, OPERATOR_INDEX, CHECK_LOCATION())
-void CheckTensor(const TfLiteParserImpl::ModelPtr & model,
+void CheckTensor(const TfLiteParserImpl::ModelPtr& model,
size_t subgraphIndex,
size_t tensorIndex,
- const CheckLocation & location)
+ const CheckLocation& location)
{
// not checking model, because I assume CHECK_MODEL already run
// and checked that. An assert would do.
@@ -213,7 +213,7 @@
CheckTensor(MODEL, SUBGRAPH_INDEX, TENSOR_INDEX, CHECK_LOCATION())
void CheckTensorPtr(TfLiteParserImpl::TensorRawPtr rawPtr,
- const CheckLocation & location)
+ const CheckLocation& location)
{
if (rawPtr == nullptr)
{
@@ -225,9 +225,9 @@
#define CHECK_TENSOR_PTR(TENSOR_PTR) \
CheckTensorPtr(TENSOR_PTR, CHECK_LOCATION())
-void CheckBuffer(const TfLiteParserImpl::ModelPtr & model,
+void CheckBuffer(const TfLiteParserImpl::ModelPtr& model,
size_t bufferIndex,
- const CheckLocation & location)
+ const CheckLocation& location)
{
if (model.get() == nullptr)
{
@@ -261,9 +261,9 @@
CheckBuffer(MODEL, BUFFER_INDEX, CHECK_LOCATION())
void CheckBufferSize(TfLiteParserImpl::BufferRawPtr bufferPtr,
- const armnn::TensorInfo & tensorInfo,
+ const armnn::TensorInfo& tensorInfo,
uint32_t bufferId,
- const CheckLocation & location)
+ const CheckLocation& location)
{
if (bufferPtr == nullptr)
{
@@ -284,6 +284,42 @@
}
}
+
+tflite::BuiltinOperator GetOpCode(const TfLiteParserImpl::ModelPtr& model, size_t subgraphIndex, size_t operatorIndex)
+{
+ const auto& operatorPtr = model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ auto opcodeIndex = operatorPtr->opcode_index;
+
+// work around the introduction of the deprecated_builtin_code introduced in 2.4 in a backwards compatible manner
+#if defined(ARMNN_POST_TFLITE_2_3)
+ auto opcode = std::max(model->operator_codes[opcodeIndex]->builtin_code,
+ static_cast<tflite::BuiltinOperator>(model->operator_codes[opcodeIndex]->deprecated_builtin_code));
+#else
+ auto opcode = model->operator_codes[opcodeIndex]->builtin_code;
+#endif
+ return opcode;
+}
+
+std::vector<unsigned int> GetUIntBuffer(armnn::TensorInfo info,
+ const TfLiteParserImpl::ModelPtr& model,
+ size_t bufferIndex)
+{
+ TfLiteParserImpl::BufferRawPtr bufferPtr = TfLiteParserImpl::GetBuffer(model, bufferIndex);
+ std::vector<unsigned int> buffer(info.GetNumElements());
+
+ if (info.GetDataType() == DataType::Signed32)
+ {
+ ::memcpy(buffer.data(), bufferPtr->data.data(), bufferPtr->data.size());
+ }
+ else if (info.GetDataType() == DataType::Signed64)
+ {
+ std::vector<uint64_t> uint64Buffer(info.GetNumElements());
+ ::memcpy(uint64Buffer.data(), bufferPtr->data.data(), bufferPtr->data.size());
+ buffer.assign(std::begin(uint64Buffer), std::end(uint64Buffer));
+ }
+ return buffer;
+}
+
#define CHECK_BUFFER_SIZE(BUFFER_PTR, TENSOR_INFO, BUFFER_ID) \
CheckBufferSize(BUFFER_PTR, TENSOR_INFO, BUFFER_ID, CHECK_LOCATION())
@@ -323,11 +359,11 @@
} while(false)
-std::vector<unsigned int> AsUnsignedVector(const std::vector<int32_t> & in)
+std::vector<unsigned int> AsUnsignedVector(const std::vector<int32_t>& in)
{
std::vector<unsigned int> result;
result.reserve(in.size());
- for (auto & i : in)
+ for (auto& i : in)
{
// If the location of the input data is -1 then the input should be ignored.
if (i == -1)
@@ -519,14 +555,14 @@
armnn::TensorInfo ToTensorInfo(TfLiteParserImpl::TensorRawPtr tensorPtr)
{
- auto const & dimensions = AsUnsignedVector(tensorPtr->shape);
+ auto const& dimensions = AsUnsignedVector(tensorPtr->shape);
return ToTensorInfo(tensorPtr, dimensions);
}
armnn::TensorInfo ToTensorInfo(TfLiteParserImpl::TensorRawPtr tensorPtr,
const bool outputTensor)
{
- auto const & dimensions = AsUnsignedVector(tensorPtr->shape);
+ auto const& dimensions = AsUnsignedVector(tensorPtr->shape);
return ToTensorInfo(tensorPtr, dimensions, outputTensor);
}
@@ -676,6 +712,7 @@
m_ParserFunctions[tflite::BuiltinOperator_NOT_EQUAL] = &TfLiteParserImpl::ParseNotEqual;
m_ParserFunctions[tflite::BuiltinOperator_PACK] = &TfLiteParserImpl::ParsePack;
m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParserImpl::ParsePad;
+ m_ParserFunctions[tflite::BuiltinOperator_PADV2] = &TfLiteParserImpl::ParsePad;
m_ParserFunctions[tflite::BuiltinOperator_PRELU] = &TfLiteParserImpl::ParsePrelu;
m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE] = &TfLiteParserImpl::ParseQuantize;
m_ParserFunctions[tflite::BuiltinOperator_RELU] = &TfLiteParserImpl::ParseRelu;
@@ -720,7 +757,7 @@
return CreateNetworkFromModel();
}
-INetworkPtr TfLiteParserImpl::CreateNetworkFromBinary(const std::vector<uint8_t> & binaryContent)
+INetworkPtr TfLiteParserImpl::CreateNetworkFromBinary(const std::vector<uint8_t>& binaryContent)
{
ResetParser();
m_Model = LoadModelFromBinary(binaryContent.data(), binaryContent.size());
@@ -976,8 +1013,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsConv2DOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsConv2DOptions();
CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex);
@@ -1135,8 +1172,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsDepthwiseConv2DOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsDepthwiseConv2DOptions();
CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex);
@@ -1345,8 +1382,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsTransposeConvOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsTransposeConvOptions();
TransposeConvolution2dDescriptor desc;
desc.m_BiasEnabled = false;
@@ -1604,8 +1641,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsPool2DOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsPool2DOptions();
CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex);
@@ -1743,8 +1780,8 @@
void TfLiteParserImpl::ParseSoftmax(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.AsSoftmaxOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsSoftmaxOptions();
SoftmaxDescriptor desc;
desc.m_Beta = options->beta;
@@ -1822,7 +1859,7 @@
}
armnn::TensorInfo TfLiteParserImpl::OutputShapeOfSqueeze(std::vector<uint32_t> squeezeDims,
- const armnn::TensorInfo & inputTensorInfo)
+ const armnn::TensorInfo& inputTensorInfo)
{
CHECK_VALID_SIZE(squeezeDims.size(), 0, 1, 2, 3, 4);
static const uint32_t dimensionSequence[] = { 0, 1, 2, 3 };
@@ -1964,8 +2001,8 @@
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(outputs.size(), 1);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsStridedSliceOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsStridedSliceOptions();
StridedSliceDescriptor desc;
desc.m_BeginMask = options->begin_mask;
@@ -2015,8 +2052,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsSubOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsSubOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
@@ -2047,8 +2084,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsDivOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsDivOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
@@ -2078,8 +2115,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsAddOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsAddOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
@@ -2109,8 +2146,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsMulOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsMulOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
@@ -2183,25 +2220,82 @@
CHECK_VALID_SIZE(outputs.size(), 1);
armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
-
armnn::TensorInfo padTensorInfo = ToTensorInfo(inputs[1]);
- BufferRawPtr bufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
- std::vector<unsigned int> padBuffer(padTensorInfo.GetNumElements());
- ::memcpy(padBuffer.data(), bufferPtr->data.data(), padTensorInfo.GetNumBytes());
+ std::vector<unsigned int> padBuffer = GetUIntBuffer(padTensorInfo, m_Model, inputs[1]->buffer);
size_t step = 2;
armnn::PadDescriptor desc;
- if (inputTensorInfo.IsQuantized())
+ auto opcode = GetOpCode(m_Model, subgraphIndex, operatorIndex);
+
+ if (opcode == tflite::BuiltinOperator_PAD)
{
- desc.m_PadValue = static_cast<float>(inputTensorInfo.GetQuantizationOffset());
+ CHECK_VALID_SIZE(inputs.size(), 2);
+
+ if (inputTensorInfo.IsQuantized())
+ {
+ desc.m_PadValue = static_cast<float>(inputTensorInfo.GetQuantizationOffset());
+ }
}
+ else if (opcode == tflite::BuiltinOperator_PADV2)
+ {
+ CHECK_VALID_SIZE(inputs.size(), 3);
+
+ armnn::TensorInfo padValueTensorInfo = ToTensorInfo(inputs[2]);
+
+ if (padValueTensorInfo.GetNumElements() != 1)
+ {
+ ARMNN_THROW_PARSE_EXCEPTION("Multiple padding values are not supported in PADV2");
+ }
+ BufferRawPtr padValueBufferPtr = GetBuffer(m_Model, inputs[2]->buffer);
+
+ // Get the pad value from the input tensor
+ if (padValueBufferPtr->data.size() > 0)
+ {
+ switch (padValueTensorInfo.GetDataType())
+ {
+ case armnn::DataType::Float32:
+ {
+ std::vector<float> padValueBuffer(padValueTensorInfo.GetNumElements());
+ ::memcpy(padValueBuffer.data(), padValueBufferPtr->data.data(), padValueBufferPtr->data.size());
+ desc.m_PadValue = padValueBuffer[0];
+ break;
+ }
+ case armnn::DataType::QAsymmU8:
+ {
+ std::vector<uint8_t> padValueBuffer(padValueTensorInfo.GetNumElements());
+ ::memcpy(padValueBuffer.data(), padValueBufferPtr->data.data(), padValueBufferPtr->data.size());
+ desc.m_PadValue = armnn::Dequantize<uint8_t>(padValueBuffer[0],
+ padValueTensorInfo.GetQuantizationScale(),
+ padValueTensorInfo.GetQuantizationOffset());
+ break;
+ }
+ case armnn::DataType::QAsymmS8:
+ case armnn::DataType::QSymmS8:
+ {
+ std::vector<int8_t> padValueBuffer(padValueTensorInfo.GetNumElements());
+ ::memcpy(padValueBuffer.data(), padValueBufferPtr->data.data(), padValueBufferPtr->data.size());
+ desc.m_PadValue = armnn::Dequantize<int8_t>(padValueBuffer[0],
+ padValueTensorInfo.GetQuantizationScale(),
+ padValueTensorInfo.GetQuantizationOffset());
+ break;
+ }
+ default: ARMNN_THROW_PARSE_EXCEPTION("Unsupported DataType");
+ }
+ }
+ else if (inputTensorInfo.IsQuantized())
+ {
+ desc.m_PadValue = static_cast<float>(inputTensorInfo.GetQuantizationOffset());
+ }
+ }
+
for (unsigned int i = 0; i < padTensorInfo.GetNumElements() / step; ++i)
{
desc.m_PadList.emplace_back(padBuffer[i * step], padBuffer[i * step + 1]);
}
- auto layerName = fmt::format("Pad:{}:{}", subgraphIndex, operatorIndex);
+ auto layerName = (opcode == tflite::BuiltinOperator_PAD) ? fmt::format("Pad:{}:{}", subgraphIndex, operatorIndex)
+ : fmt::format("PadV2:{}:{}", subgraphIndex, operatorIndex);
TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
IConnectableLayer* layer = m_Network->AddPadLayer(desc, layerName.c_str());
@@ -2399,7 +2493,7 @@
void TfLiteParserImpl::ParseActivation(size_t subgraphIndex, size_t operatorIndex, ActivationFunction activationType)
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
IgnoreUnused(operatorPtr);
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
@@ -2441,7 +2535,7 @@
case ActivationFunction::LeakyReLu:
{
layerName += fmt::format("LEAKYRELU:{}:{}", subgraphIndex, operatorIndex);
- const auto * options = operatorPtr->builtin_options.AsLeakyReluOptions();
+ const auto* options = operatorPtr->builtin_options.AsLeakyReluOptions();
activationDesc.m_A = options->alpha;
break;
}
@@ -2478,8 +2572,8 @@
auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
-armnn::TensorInfo TfLiteParserImpl::OutputShapeOfReshape(const armnn::TensorInfo & inputTensorInfo,
- const std::vector<int32_t> & targetDimsIn)
+armnn::TensorInfo TfLiteParserImpl::OutputShapeOfReshape(const armnn::TensorInfo& inputTensorInfo,
+ const std::vector<int32_t>& targetDimsIn)
{
std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());
const auto stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);
@@ -2517,8 +2611,8 @@
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(outputs.size(), 1);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsReshapeOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsReshapeOptions();
auto layerName = fmt::format("Reshape:{}:{}", subgraphIndex, operatorIndex);
armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
@@ -2727,8 +2821,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsConcatenationOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsConcatenationOptions();
CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex);
@@ -2777,7 +2871,7 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorRfr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto& operatorRfr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
const auto options = operatorRfr->builtin_options.AsFullyConnectedOptions();
CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex);
@@ -2884,7 +2978,7 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
@@ -3001,8 +3095,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsUnpackOptions();
+ 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);
@@ -3114,8 +3208,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsSplitOptions();
+ 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);
@@ -3226,8 +3320,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsSplitVOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsSplitVOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 3);
@@ -3472,8 +3566,8 @@
armnn::GatherDescriptor gatherDescriptor;
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsGatherOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsGatherOptions();
auto axis = options->axis;
auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions());
@@ -3521,8 +3615,8 @@
armnn::DepthToSpaceDescriptor descriptor;
- const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto * options = operatorPtr->builtin_options.AsDepthToSpaceOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsDepthToSpaceOptions();
auto blockSize = options->block_size;
if (blockSize < 2)
{
@@ -3570,8 +3664,8 @@
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
- const auto &operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
- const auto *options = operatorPtr->builtin_options.AsReducerOptions();
+ const auto& operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+ const auto* options = operatorPtr->builtin_options.AsReducerOptions();
auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(inputs.size(), 2);
@@ -3614,7 +3708,7 @@
desc.m_ReduceOperation = reduceOperation;
// Register a new layer object, Sum.
- IConnectableLayer *layer = m_Network->AddReduceLayer(desc, layerName.c_str());
+ IConnectableLayer* layer = m_Network->AddReduceLayer(desc, layerName.c_str());
armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
@@ -3849,7 +3943,7 @@
return activationLayer;
}
-TfLiteParserImpl::ModelPtr TfLiteParserImpl::LoadModelFromFile(const char * fileName)
+TfLiteParserImpl::ModelPtr TfLiteParserImpl::LoadModelFromFile(const char* fileName)
{
if (fileName == nullptr)
{
@@ -3873,7 +3967,7 @@
fileContent.size());
}
-TfLiteParserImpl::ModelPtr TfLiteParserImpl::LoadModelFromBinary(const uint8_t * binaryContent, size_t len)
+TfLiteParserImpl::ModelPtr TfLiteParserImpl::LoadModelFromBinary(const uint8_t* binaryContent, size_t len)
{
if (binaryContent == nullptr)
{
@@ -3892,18 +3986,18 @@
return tflite::UnPackModel(binaryContent);
}
-TfLiteParserImpl::TensorRawPtrVector TfLiteParserImpl::GetInputs(const ModelPtr & model,
+TfLiteParserImpl::TensorRawPtrVector TfLiteParserImpl::GetInputs(const ModelPtr& model,
size_t subgraphIndex,
size_t operatorIndex)
{
CHECK_MODEL(model, subgraphIndex, operatorIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
- const auto & operatorPtr = subgraphPtr->operators[operatorIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
size_t inputCount = operatorPtr->inputs.size();
TensorRawPtrVector result;
- for (size_t i=0; i<inputCount; ++i)
+ for (size_t i = 0; i < inputCount; ++i)
{
// If the input location is -1 then assume input is turned off.
if (operatorPtr->inputs[i] == -1)
@@ -3919,18 +4013,18 @@
return result;
}
-TfLiteParserImpl::TensorRawPtrVector TfLiteParserImpl::GetOutputs(const ModelPtr & model,
+TfLiteParserImpl::TensorRawPtrVector TfLiteParserImpl::GetOutputs(const ModelPtr& model,
size_t subgraphIndex,
size_t operatorIndex)
{
CHECK_MODEL(model, subgraphIndex, operatorIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
- const auto & operatorPtr = subgraphPtr->operators[operatorIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
size_t outputCount = operatorPtr->outputs.size();
TensorRawPtrVector result(outputCount);
- for (size_t i=0; i<outputCount; ++i)
+ for (size_t i = 0; i < outputCount; ++i)
{
uint32_t outputId = CHECKED_NON_NEGATIVE(operatorPtr->outputs[i]);
CHECK_TENSOR(model, subgraphIndex, outputId);
@@ -3939,15 +4033,15 @@
return result;
}
-TfLiteParserImpl::TensorIdRawPtrVector TfLiteParserImpl::GetSubgraphInputs(const ModelPtr & model,
+TfLiteParserImpl::TensorIdRawPtrVector TfLiteParserImpl::GetSubgraphInputs(const ModelPtr& model,
size_t subgraphIndex)
{
CHECK_SUBGRAPH(model, subgraphIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
size_t inputCount = subgraphPtr->inputs.size();
TensorIdRawPtrVector result(inputCount);
- for (size_t i=0; i<inputCount; ++i)
+ for (size_t i = 0; i < inputCount; ++i)
{
uint32_t inputId = CHECKED_NON_NEGATIVE(subgraphPtr->inputs[i]);
CHECK_TENSOR(model, subgraphIndex, inputId);
@@ -3956,15 +4050,15 @@
return result;
}
-TfLiteParserImpl::TensorIdRawPtrVector TfLiteParserImpl::GetSubgraphOutputs(const ModelPtr & model,
+TfLiteParserImpl::TensorIdRawPtrVector TfLiteParserImpl::GetSubgraphOutputs(const ModelPtr& model,
size_t subgraphIndex)
{
CHECK_SUBGRAPH(model, subgraphIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
size_t outputCount = subgraphPtr->outputs.size();
TensorIdRawPtrVector result(outputCount);
- for (size_t i=0; i<outputCount; ++i)
+ for (size_t i = 0; i < outputCount; ++i)
{
uint32_t outputId = CHECKED_NON_NEGATIVE(subgraphPtr->outputs[i]);
result[i] = std::make_pair(outputId, subgraphPtr->tensors[outputId].get());
@@ -3977,8 +4071,8 @@
size_t operatorIndex)
{
CHECK_MODEL(model, subgraphIndex, operatorIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
- const auto & operatorPtr = subgraphPtr->operators[operatorIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
return operatorPtr->inputs;
}
@@ -3987,8 +4081,8 @@
size_t operatorIndex)
{
CHECK_MODEL(model, subgraphIndex, operatorIndex);
- const auto & subgraphPtr = model->subgraphs[subgraphIndex];
- const auto & operatorPtr = subgraphPtr->operators[operatorIndex];
+ const auto& subgraphPtr = model->subgraphs[subgraphIndex];
+ const auto& operatorPtr = subgraphPtr->operators[operatorIndex];
return operatorPtr->outputs;
}
@@ -4053,7 +4147,7 @@
CHECK_SUBGRAPH(m_Model, subgraphIndex);
auto inputs = GetSubgraphInputs(m_Model, subgraphIndex);
- for (auto const & tensorIdAndPtr : inputs)
+ for (auto const& tensorIdAndPtr : inputs)
{
auto bindingId = GenerateLayerBindingId(subgraphIndex, tensorIdAndPtr.first);
IConnectableLayer* layer =
@@ -4074,7 +4168,7 @@
CHECK_SUBGRAPH(m_Model, subgraphIndex);
auto outputs = GetSubgraphOutputs(m_Model, subgraphIndex);
- for (auto const & tensorIdAndPtr : outputs)
+ for (auto const& tensorIdAndPtr : outputs)
{
auto bindingId = GenerateLayerBindingId(subgraphIndex, tensorIdAndPtr.first);
IConnectableLayer* layer =
@@ -4091,7 +4185,7 @@
{
CHECK_SUBGRAPH(m_Model, subgraphIndex);
- const auto & subgraphPtr = m_Model->subgraphs[subgraphIndex];
+ const auto& subgraphPtr = m_Model->subgraphs[subgraphIndex];
for (unsigned int subgraphIndex = 0; subgraphIndex < m_SubgraphConnections.size(); ++subgraphIndex)
{
for (unsigned int tensorIndex = 0; tensorIndex < m_SubgraphConnections[subgraphIndex].size(); ++tensorIndex)
@@ -4107,7 +4201,7 @@
auto tensorAndData = CreateConstTensorNonPermuted(tensorPtr, tensorInfo);
std::string layerName = fmt::format("Constant:{}", tensorPtr->name);
- IConnectableLayer *layer = m_Network->AddConstantLayer(tensorAndData, layerName.c_str());
+ IConnectableLayer* layer = m_Network->AddConstantLayer(tensorAndData, layerName.c_str());
layer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
RegisterOutputSlots(subgraphIndex,
@@ -4234,7 +4328,7 @@
{
CHECK_SUBGRAPH(m_Model, subgraphId);
auto inputs = GetSubgraphInputs(m_Model, subgraphId);
- for (auto const & input : inputs)
+ for (auto const& input : inputs)
{
if (input.second->name == name)
{
@@ -4247,7 +4341,7 @@
}
std::stringstream bindings;
- for (auto const & input : inputs)
+ for (auto const& input : inputs)
{
bindings << "'" << input.second->name << "' ";
}
@@ -4279,7 +4373,7 @@
}
std::stringstream bindings;
- for (auto const & output : outputs)
+ for (auto const& output : outputs)
{
bindings << "'" << output.second->name << "' ";
}
@@ -4304,7 +4398,7 @@
auto inputs = GetSubgraphInputs(m_Model, subgraphId);
std::vector<std::string> result;
result.reserve(inputs.size());
- for (auto const & input : inputs)
+ for (auto const& input : inputs)
{
result.push_back(input.second->name);
}
@@ -4317,7 +4411,7 @@
auto outputs = GetSubgraphOutputs(m_Model, subgraphId);
std::vector<std::string> result;
result.reserve(outputs.size());
- for (auto const & output : outputs)
+ for (auto const& output : outputs)
{
result.push_back(output.second->name);
}
@@ -4329,7 +4423,7 @@
return TFLITE_PARSER_VERSION;
}
-TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<float[]> && data)
+TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<float[]>&& data)
: m_FloatData(std::move(data))
, m_Uint8Data(nullptr)
, m_Int8Data(nullptr)
@@ -4337,7 +4431,7 @@
{
}
-TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<uint8_t[]> && data)
+TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<uint8_t[]>&& data)
: m_FloatData(nullptr)
, m_Uint8Data(std::move(data))
, m_Int8Data(nullptr)
@@ -4345,7 +4439,7 @@
{
}
-TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<int8_t[]> && data)
+TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<int8_t[]>&& data)
: m_FloatData(nullptr)
, m_Uint8Data(nullptr)
, m_Int8Data(std::move(data))
@@ -4353,7 +4447,7 @@
{
}
-TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<int32_t[]> && data)
+TfLiteParserImpl::SupportedDataStorage::SupportedDataStorage(std::unique_ptr<int32_t[]>&& data)
: m_FloatData(nullptr)
, m_Uint8Data(nullptr)
, m_Int8Data(nullptr)
diff --git a/src/armnnTfLiteParser/test/PadV2.cpp b/src/armnnTfLiteParser/test/PadV2.cpp
new file mode 100644
index 0000000..ba333ed
--- /dev/null
+++ b/src/armnnTfLiteParser/test/PadV2.cpp
@@ -0,0 +1,173 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ParserFlatbuffersFixture.hpp"
+
+
+TEST_SUITE("TensorflowLiteParser_Pad")
+{
+struct PadV2Fixture : public ParserFlatbuffersFixture
+{
+ explicit PadV2Fixture(const std::string& inputShape,
+ const std::string& outputShape,
+ const std::string& padListShape,
+ const std::string& padListData,
+ const std::string& constantValuesShape,
+ const std::string& constantValuesData,
+ const std::string& dataType = "FLOAT32",
+ const std::string& scale = "1.0",
+ const std::string& offset = "0")
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "PADV2" } ],
+ "subgraphs": [ {
+ "tensors": [
+ {
+ "shape": )" + inputShape + R"(,
+ "type": )" + dataType + R"(,
+ "buffer": 0,
+ "name": "inputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ )" + scale + R"( ],
+ "zero_point": [ )" + offset + R"( ],
+ }
+ },
+ {
+ "shape": )" + outputShape + R"(,
+ "type": )" + dataType + R"(,
+ "buffer": 1,
+ "name": "outputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ )" + scale + R"( ],
+ "zero_point": [ )" + offset + R"( ],
+ }
+ },
+ {
+ "shape": )" + padListShape + R"( ,
+ "type": "INT64",
+ "buffer": 2,
+ "name": "padList",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + constantValuesShape + R"( ,
+ "type": )" + dataType + R"(,
+ "buffer": 3,
+ "name": "constantValues",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ }
+ ],
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0, 2, 3 ],
+ "outputs": [ 1 ],
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { },
+ { "data": )" + padListData + R"(, },
+ { "data": )" + constantValuesData + R"(, },
+ ]
+ }
+ )";
+ SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+ }
+};
+
+struct SimplePadV2Fixture : public PadV2Fixture
+{
+ SimplePadV2Fixture() : PadV2Fixture("[ 2,3 ]", "[ 4,7 ]", "[ 2,2 ]",
+ "[ 1,0,0,0,0,0,0,0, 1,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0 ]",
+ "[1]", "[0,0,160,64]") {}
+};
+
+TEST_CASE_FIXTURE(SimplePadV2Fixture, "ParsePadV2")
+{
+ RunTest<2, armnn::DataType::Float32>
+ (0,
+ {{ "inputTensor", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }}},
+ {{ "outputTensor", { 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f,
+ 5.0f, 5.0f, 1.0f, 2.0f, 3.0f, 5.0f, 5.0f,
+ 5.0f, 5.0f, 4.0f, 5.0f, 6.0f, 5.0f, 5.0f,
+ 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f }}});
+}
+
+struct NoConstValuePadV2Fixture : public PadV2Fixture
+{
+ NoConstValuePadV2Fixture() : PadV2Fixture("[ 2,3 ]", "[ 4,7 ]", "[ 2,2 ]",
+ "[ 1,0,0,0,0,0,0,0, 1,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0 ]",
+ "[]", "[]") {}
+};
+
+TEST_CASE_FIXTURE(NoConstValuePadV2Fixture, "ParsePadV2NoConstValue")
+{
+ RunTest<2, armnn::DataType::Float32>
+ (0,
+ {{ "inputTensor", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }}},
+ {{ "outputTensor", { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, .0f,
+ 0.0f, 0.0f, 1.0f, 2.0f, 3.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 4.0f, 5.0f, 6.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }}});
+}
+
+struct Uint8PadV2Fixture : public PadV2Fixture
+{
+ Uint8PadV2Fixture() : PadV2Fixture("[ 2,3 ]", "[ 4,7 ]", "[ 2,2 ]",
+ "[ 1,0,0,0,0,0,0,0, 1,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0 ]",
+ "[1]", "[1]","UINT8", "-2.0", "3") {}
+};
+
+TEST_CASE_FIXTURE(Uint8PadV2Fixture, "ParsePadV2Uint8")
+{
+ RunTest<2, armnn::DataType::QAsymmU8>
+ (0,
+ {{ "inputTensor", { 1, 2, 3, 4, 5, 6 }}},
+ {{ "outputTensor", { 1, 1, 1, 1, 1, 1, 1,
+ 1, 1, 1, 2, 3, 1, 1,
+ 1, 1, 4, 5, 6, 1, 1,
+ 1, 1, 1, 1, 1, 1, 1 }}});
+}
+
+struct Int8PadV2Fixture : public PadV2Fixture
+{
+ Int8PadV2Fixture() : PadV2Fixture("[ 2,3 ]", "[ 4,7 ]", "[ 2,2 ]",
+ "[ 1,0,0,0,0,0,0,0, 1,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0, 2,0,0,0,0,0,0,0 ]",
+ "[1]", "[2]","INT8", "-2.0", "3") {}
+};
+
+TEST_CASE_FIXTURE(Int8PadV2Fixture, "ParsePadV2Int8")
+{
+ RunTest<2, armnn::DataType::QAsymmS8>
+ (0,
+ {{ "inputTensor", { 1, -2, 3, 4, 5, -6 }}},
+ {{ "outputTensor", { 2, 2, 2, 2, 2, 2, 2,
+ 2, 2, 1, -2, 3, 2, 2,
+ 2, 2, 4, 5, -6, 2, 2,
+ 2, 2, 2, 2, 2, 2, 2 }}});
+}
+
+}