From 0506ef0a099f5ba564af5e110e6857a68f462080 Mon Sep 17 00:00:00 2001 From: Mike Kelly Date: Tue, 3 Jan 2023 16:29:44 +0000 Subject: GitHub #543 Problem Parsing Mixed-Precision Model * Fixed bug when converting Constants with Per-Axis Quantization Signed-off-by: Mike Kelly Change-Id: Ifbea23e60483746ec987da491dae96e74cb33af4 --- src/armnnTfLiteParser/TfLiteParser.cpp | 104 ++++++++++++++++----------------- src/armnnTfLiteParser/TfLiteParser.hpp | 8 +++ src/armnnTfLiteParser/test/Conv2D.cpp | 2 +- 3 files changed, 59 insertions(+), 55 deletions(-) (limited to 'src/armnnTfLiteParser') diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 0484c6f478..191cfd2b48 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -316,6 +316,14 @@ std::vector GetUIntBuffer(armnn::TensorInfo info, ::memcpy(uint64Buffer.data(), bufferPtr->data.data(), bufferPtr->data.size()); buffer.assign(std::begin(uint64Buffer), std::end(uint64Buffer)); } + else + { + CheckLocation location = CHECK_LOCATION(); + throw ParseException( + fmt::format("Unsupported data type for uint buffer {}, only Signed 32 or Signed 64 are supported. {}", + GetDataTypeName(info.GetDataType()), + location.AsString())); + } return buffer; } @@ -911,42 +919,16 @@ INetworkPtr TfLiteParserImpl::CreateNetworkFromModel() return std::move(m_Network); } -std::unique_ptr AsFloatArray(TfLiteParserImpl::BufferRawPtr bufferPtr, - const TensorInfo& tensorInfo) +bool TfLiteParserImpl::ShouldConstantTensorBeConverted(TfLiteParserImpl::TensorRawPtr tensorPtr, + armnn::DataType inputDataType, + armnn::DataType tensorDataType) { - if (tensorInfo.GetDataType() == DataType::QAsymmS8 || tensorInfo.GetDataType() == DataType::QSymmS8 || - tensorInfo.GetDataType() == DataType::QAsymmU8) - { - std::unique_ptr buffer(new float[tensorInfo.GetNumElements()]); - - if (tensorInfo.HasPerAxisQuantization()) - { - unsigned int axis = tensorInfo.GetQuantizationDim().value(); - auto axisDimensionality = tensorInfo.GetShape()[axis]; - auto axisFactor = armnnUtils::GetNumElementsAfter(tensorInfo.GetShape(), axis); - - for (unsigned int i = 0; i < tensorInfo.GetNumDimensions(); ++i) - { - unsigned int axisIndex = (i / axisFactor) % axisDimensionality; - buffer[i] = Dequantize(bufferPtr->data[i], tensorInfo.GetQuantizationScales()[axisIndex], - tensorInfo.GetQuantizationOffset()); - } - } - else - { - for (unsigned int i = 0; i < tensorInfo.GetNumElements(); ++i) - { - buffer[i] = Dequantize(bufferPtr->data[i], tensorInfo.GetQuantizationScale(), - tensorInfo.GetQuantizationOffset()); - } - } - return buffer; - } - throw ParseException( - fmt::format("Unsupported input/weights combination: Input {} not supported with Weights {}", - GetDataTypeName(DataType::Float32), - GetDataTypeName(tensorInfo.GetDataType()), - CHECK_LOCATION().AsString())); + return (TfLiteParserImpl::IsConstTensor(tensorPtr) && inputDataType == DataType::Float32 && + (tensorDataType == DataType::QAsymmU8 || + tensorDataType == DataType::QAsymmS8 || + tensorDataType == DataType::QSymmS8 || + tensorDataType == DataType::Signed32 || + tensorDataType == DataType::Signed64)); } void TfLiteParserImpl::RegisterProducerOfTensor(size_t subgraphIndex, @@ -1136,9 +1118,7 @@ void TfLiteParserImpl::ParseConv2D(size_t subgraphIndex, size_t operatorIndex) auto layerName = fmt::format("Conv2D:{}:{}", subgraphIndex, operatorIndex); armnn::IConnectableLayer* layer = m_Network->AddConvolution2dLayer(desc, layerName.c_str()); - if (IsConstTensor(inputs[1]) && inputTensorInfo.GetDataType() == DataType::Float32 && - (filterTensorInfo.GetDataType() == DataType::QAsymmU8 || - filterTensorInfo.GetDataType() == DataType::QAsymmS8)) + if (ShouldConstantTensorBeConverted(inputs[1], inputTensorInfo.GetDataType(), filterTensorInfo.GetDataType())) { m_ConstantsToDequantize.emplace_back(inputs[1]->buffer); } @@ -1150,9 +1130,7 @@ void TfLiteParserImpl::ParseConv2D(size_t subgraphIndex, size_t operatorIndex) // Add the biases input to the registration list, a constant layer will be added by SetupConstantLayers. tensorIndexesToRegister.emplace_back(inputTensorIndexes[2]); - if (IsConstTensor(inputs[2]) && inputTensorInfo.GetDataType() == DataType::Float32 && - (filterTensorInfo.GetDataType() == DataType::QAsymmU8 || - filterTensorInfo.GetDataType() == DataType::QAsymmS8)) + if (ShouldConstantTensorBeConverted(inputs[2], inputTensorInfo.GetDataType(), biasTensorInfo.GetDataType())) { m_ConstantsToDequantize.emplace_back(inputs[2]->buffer); } @@ -3112,9 +3090,7 @@ void TfLiteParserImpl::ParseFullyConnected(size_t subgraphIndex, size_t operator // Add the weights input to the registration list, constant layers will be added by SetupConstantLayers if constant. tensorIndexesToRegister.emplace_back(inputTensorIndexes[1]); - if (desc.m_ConstantWeights && inputTensorInfo.GetDataType() == DataType::Float32 && - (filterTensorInfo.GetDataType() == DataType::QAsymmU8 || - filterTensorInfo.GetDataType() == DataType::QAsymmS8)) + if (ShouldConstantTensorBeConverted(inputs[1], inputTensorInfo.GetDataType(), filterTensorInfo.GetDataType())) { m_ConstantsToDequantize.emplace_back(inputs[1]->buffer); } @@ -3127,9 +3103,7 @@ void TfLiteParserImpl::ParseFullyConnected(size_t subgraphIndex, size_t operator // Add the biases input to the registration list, constant layer will be added by SetupConstantLayers. tensorIndexesToRegister.emplace_back(inputTensorIndexes[2]); - if (desc.m_ConstantWeights && inputTensorInfo.GetDataType() == DataType::Float32 && - (biasTensorInfo.GetDataType() == DataType::QAsymmU8 || - biasTensorInfo.GetDataType() == DataType::QAsymmS8)) + if (ShouldConstantTensorBeConverted(inputs[2], inputTensorInfo.GetDataType(), biasTensorInfo.GetDataType())) { m_ConstantsToDequantize.emplace_back(inputs[2]->buffer); } @@ -4925,11 +4899,22 @@ TfLiteParserImpl::CreateConstTensorNonPermuted(TensorRawPtr tensorPtr, // Make sure isConstant flag is set. tensorInfo.SetConstant(); - if (inputDataType == DataType::Float32 && tensorInfo.GetDataType() != DataType::Float32) + if (inputDataType == DataType::Float32 && tensorInfo.GetDataType() != DataType::Float32) { - TensorInfo constTensorInfo(tensorInfo.GetShape(), DataType::Float32, 0.0f, 0, true); - std::unique_ptr data = AsFloatArray(bufferPtr, tensorInfo); - return std::make_pair(ConstTensor(constTensorInfo, data.get()), std::move(data)); + try + { + TensorInfo constTensorInfo(tensorInfo.GetShape(), DataType::Float32, 0.0f, 0, true); + std::unique_ptr data = armnnUtils::ToFloatArray(bufferPtr->data, tensorInfo); + return std::make_pair(ConstTensor(constTensorInfo, data.get()), std::move(data)); + } + catch (armnn::InvalidArgumentException) + { + throw ParseException( + fmt::format("Unsupported input/weights combination: Input {} not supported with Weights {}", + GetDataTypeName(DataType::Float32), + GetDataTypeName(tensorInfo.GetDataType()), + CHECK_LOCATION().AsString())); + } } else { @@ -4950,9 +4935,20 @@ TfLiteParserImpl::CreateConstTensorPtr(TensorRawPtr tensorPtr, armnn::TensorInfo if (inputTensorInfo.GetDataType() == DataType::Float32 && tensorInfo.GetDataType() != DataType::Float32) { - TensorInfo constTensorInfo(tensorInfo.GetShape(), DataType::Float32, 0.0f, 0, true); - std::unique_ptr data = AsFloatArray(bufferPtr, tensorInfo); - return std::make_pair(new ConstTensor(constTensorInfo, data.get()), std::move(data)); + try + { + TensorInfo constTensorInfo(tensorInfo.GetShape(), DataType::Float32, 0.0f, 0, true); + std::unique_ptr data = armnnUtils::ToFloatArray(bufferPtr->data, tensorInfo); + return std::make_pair(new ConstTensor(constTensorInfo, data.get()), std::move(data)); + } + catch (armnn::InvalidArgumentException) + { + throw ParseException( + fmt::format("Unsupported input/weights combination: Input {} not supported with Weights {}", + GetDataTypeName(DataType::Float32), + GetDataTypeName(tensorInfo.GetDataType()), + CHECK_LOCATION().AsString())); + } } else { diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index f8ddc55649..7eb6c48501 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -242,7 +242,13 @@ private: }; bool ShouldConstantTensorBeCreated(unsigned int tensorIndex); + bool IsConstTensor(TensorRawPtr tensorPtr); + + bool ShouldConstantTensorBeConverted(TfLiteParserImpl::TensorRawPtr tensorPtr, + armnn::DataType inputDataType, + armnn::DataType filterDataType); + armnn::ConstTensor CreateConstTensorNonPermuted(TensorRawPtr tensorPtr, armnn::TensorInfo& tensorInfo); @@ -250,6 +256,7 @@ private: CreateConstTensorPermuted(TensorRawPtr tensorPtr, armnn::TensorInfo& tensorInfo, armnn::Optional permutationVector); + std::pair> CreateConstTensorNonPermuted(TensorRawPtr tensorPtr, armnn::TensorInfo& tensorInfo, @@ -261,6 +268,7 @@ private: TfLiteParserImpl::TensorRawPtr tensorPtr, armnn::TensorInfo& tensorInfo, armnn::Optional permutationVector); + std::pair> CreateConstTensorPtr(TensorRawPtr tensorPtr, armnn::TensorInfo& inputTensorInfo); diff --git a/src/armnnTfLiteParser/test/Conv2D.cpp b/src/armnnTfLiteParser/test/Conv2D.cpp index 45c4a43519..334c102344 100644 --- a/src/armnnTfLiteParser/test/Conv2D.cpp +++ b/src/armnnTfLiteParser/test/Conv2D.cpp @@ -673,7 +673,7 @@ struct Conv2FloatWithInt8WeightsAndBiasesFixture : Conv2DWithBiasesFixture "[ 1, 2, 2, 1 ]", // filterShape "[ 2,1, 0,6 ]", // filterData "[ 1 ]", // biasShape - "[ 10, 0, 0, 0 ]", // biasData + "[ 10 ]", // biasData "1", // stride w and h "NONE", // activation "1.0", // filterScale -- cgit v1.2.1