diff options
Diffstat (limited to 'src/armnnTfParser')
-rw-r--r-- | src/armnnTfParser/TfParser.cpp | 116 | ||||
-rw-r--r-- | src/armnnTfParser/test/Convolution2d.cpp | 143 |
2 files changed, 176 insertions, 83 deletions
diff --git a/src/armnnTfParser/TfParser.cpp b/src/armnnTfParser/TfParser.cpp index 53cdfa37a2..b40b05409a 100644 --- a/src/armnnTfParser/TfParser.cpp +++ b/src/armnnTfParser/TfParser.cpp @@ -14,6 +14,7 @@ #include <ParserHelper.hpp> #include <Permute.hpp> #include <VerificationHelpers.hpp> +#include <DataLayoutIndexed.hpp> #include <google/protobuf/io/zero_copy_stream_impl.h> #include <google/protobuf/text_format.h> @@ -36,6 +37,7 @@ #include <numeric> #include <functional> +using namespace armnnUtils; using namespace armnn; namespace armnnTfParser @@ -752,6 +754,16 @@ public: return constTensor; } + const T* GetStorage() const + { + return m_Storage.data(); + } + + const TensorInfo& GetTensorInfo() const + { + return m_TensorInfo; + } + private: ///< Manages the lifetime of the tensor data. std::vector<T> m_Storage; @@ -1059,59 +1071,85 @@ ParsedTfOperationPtr TfParser::ParseConv2D(const tensorflow::NodeDef& nodeDef, CHECK_DATA_FORMAT(nodeDef, dataFormat, "Conv2D"); - if (dataFormat == "NHWC") - { - desc.m_StrideX = strides[2]; - desc.m_StrideY = strides[1]; - // Swizzles input to supported memory layout. - inputTensorInfo = armnnUtils::Permuted(inputSlot.GetTensorInfo(), NHWCToArmNN); - } - else if (dataFormat == "NCHW") - { - desc.m_StrideX = strides[3]; - desc.m_StrideY = strides[2]; - } + DataLayout dataLayout = dataFormat == "NHWC" ? DataLayout::NHWC : DataLayout::NCHW; - uint32_t inputHeight = inputTensorInfo.GetShape()[2]; - uint32_t inputWidth = inputTensorInfo.GetShape()[3]; + desc.m_DataLayout = dataLayout; - std::vector<float> outputTensorData; + DataLayoutIndexed dataLayoutIndexed(dataLayout); - ConstTensor weightTensor = weightNode->GetConstTensor(true, outputTensorData); + desc.m_StrideX = strides[dataLayoutIndexed.GetWidthIndex()]; + desc.m_StrideY = strides[dataLayoutIndexed.GetHeightIndex()]; - uint32_t weightHeight = weightTensor.GetShape()[2]; - uint32_t weightWidth = weightTensor.GetShape()[3]; + uint32_t inputHeight = inputTensorInfo.GetShape()[dataLayoutIndexed.GetHeightIndex()]; + uint32_t inputWidth = inputTensorInfo.GetShape()[dataLayoutIndexed.GetWidthIndex()]; + + // Mappings from TensorFlow filter tensors to the ArmNN filter tensors. + // Tensorflow weights are [H, W, In, Out]. + // ArmNN weights have to be [Out, H, W, In] when the data layout is NHWC, + // and [Out, In, H, W] when the data layout is NCHW. + PermutationVector permutationVector = + dataLayout == DataLayout::NHWC ? + std::initializer_list<unsigned int>{ 1, 2, 3, 0 } : // NHWC: [H, W, In, Out] -> [Out, H, W, In] + std::initializer_list<unsigned int>{ 2, 3, 1, 0 }; // NCHW: [H, W, In, Out] -> [Out, In, H, W] + + // Swizzle the tensor using the given permutation vector. + const TensorInfo& weightTensorInfo = weightNode->GetTensorInfo(); + const TensorInfo weightTensorSwizzledInfo = armnnUtils::Permuted(weightTensorInfo, permutationVector); + + // Swizzles the content of the tensor's permanent storage into a local storage. + std::vector<float> weightTensorSwizzledData(weightTensorInfo.GetNumElements()); + armnnUtils::Permute(weightTensorSwizzledInfo.GetShape(), permutationVector, + weightNode->GetStorage(), weightTensorSwizzledData.data()); + + // Create a weight tensor with the newly swizzled data. + ConstTensor weightTensor(weightTensorSwizzledInfo, weightTensorSwizzledData); + + uint32_t weightHeight = weightTensor.GetShape()[dataLayoutIndexed.GetHeightIndex()]; + uint32_t weightWidth = weightTensor.GetShape()[dataLayoutIndexed.GetWidthIndex()]; bool padding = false; TensorInfo outputInfo; + unsigned int outputHeight = 0; + unsigned int outputWidth = 0; CHECK_PADDING_TYPE(nodeDef, paddingString); if (paddingString == "SAME") { padding = true; - outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0], - weightTensor.GetShape()[0], - static_cast<uint32_t>(ceil( - static_cast<float>(inputHeight) / - static_cast<float>(desc.m_StrideY))), - static_cast<uint32_t>(ceil( - static_cast<float>(inputWidth) / - static_cast<float>(desc.m_StrideX))) - }, DataType::Float32); + + outputHeight = static_cast<uint32_t>(ceil(static_cast<float>(inputHeight) / + static_cast<float>(desc.m_StrideY))); + outputWidth = static_cast<uint32_t>(ceil(static_cast<float>(inputWidth) / + static_cast<float>(desc.m_StrideX))); } else if (paddingString == "VALID") { padding = false; + + outputHeight = static_cast<uint32_t>(ceil(static_cast<float>(inputHeight - weightHeight + 1) / + static_cast<float>(desc.m_StrideY))); + outputWidth = static_cast<uint32_t>(ceil(static_cast<float>(inputWidth - weightWidth + 1) / + static_cast<float>(desc.m_StrideX))); + } + + switch (dataLayout) + { + case DataLayout::NHWC: + outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0], + outputHeight, + outputWidth, + weightTensor.GetShape()[0] }, + DataType::Float32); + break; + case DataLayout::NCHW: + default: outputInfo = TensorInfo({ inputTensorInfo.GetShape()[0], weightTensor.GetShape()[0], - static_cast<uint32_t>(ceil( - static_cast<float>(inputHeight - weightHeight + 1) / - static_cast<float>(desc.m_StrideY))), - static_cast<uint32_t>(ceil( - static_cast<float>(inputWidth - weightWidth + 1) / - static_cast<float>(desc.m_StrideX))) - }, DataType::Float32); + outputHeight, + outputWidth }, + DataType::Float32); + break; } CalcPadding(inputHeight, weightHeight, desc.m_StrideY, desc.m_PadTop, desc.m_PadBottom, padding); @@ -1119,15 +1157,7 @@ ParsedTfOperationPtr TfParser::ParseConv2D(const tensorflow::NodeDef& nodeDef, IConnectableLayer* layer = m_Network->AddConvolution2dLayer(desc, weightTensor, nodeDef.name().c_str()); layer->GetOutputSlot(0).SetTensorInfo(outputInfo); - - if (dataFormat == "NHWC") - { - layer = SwizzleInDeswizzleOut(*m_Network, inputSlot, *layer, nodeDef.name()); - } - else - { - inputSlot.Connect(layer->GetInputSlot(0)); - } + inputSlot.Connect(layer->GetInputSlot(0)); return std::make_unique<SingleLayerParsedTfOperation>(this, nodeDef, layer); } diff --git a/src/armnnTfParser/test/Convolution2d.cpp b/src/armnnTfParser/test/Convolution2d.cpp index cc534df53d..aead1fe965 100644 --- a/src/armnnTfParser/test/Convolution2d.cpp +++ b/src/armnnTfParser/test/Convolution2d.cpp @@ -6,6 +6,8 @@ #include <boost/test/unit_test.hpp> #include "armnnTfParser/ITfParser.hpp" #include "ParserPrototxtFixture.hpp" + +#include <array> #include <string> #include <iostream> @@ -13,15 +15,28 @@ BOOST_AUTO_TEST_SUITE(TensorflowParser) struct Convolution2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> { - explicit Convolution2dFixture(const char* paddingType) - : Convolution2dFixture(paddingType, 1) + explicit Convolution2dFixture(const std::string& dataLayout, const std::string& paddingType) + : Convolution2dFixture(dataLayout, paddingType, 1) {} // Dilation: 0 - dilations attribute is not included; // Dilation: >0 - dilations attribute set to [1,v,v,1], where v is the value of the dilation arg - explicit Convolution2dFixture(const char* paddingType, int stride, int dilation = 0) + explicit Convolution2dFixture(const std::string& dataLayout, const std::string& paddingType, + int stride, int dilation = 0) { - std::string strideString = std::to_string(stride); + std::string strideString (" i: 1 \n" + " i: 1 \n"); + if (dataLayout == "NHWC") + { + strideString.append(" i: " + std::to_string(stride) + " \n" + " i: 1 \n"); + } + else // dataLayout == "NCHW" + { + strideString.append(" i: 1 \n" + " i: " + std::to_string(stride) + " \n"); + } + std::string dilationString = std::to_string(dilation); m_Prototext = "node { \n" " name: \"graphInput\" \n" @@ -87,13 +102,15 @@ struct Convolution2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfPa " attr { \n" " key: \"data_format\" \n" " value { \n" - " s: \"NHWC\" \n" - " } \n" - " } \n" - " attr { \n" - " key: \"padding\" \n" - " value { \n" " s: \""; + m_Prototext.append(dataLayout); + m_Prototext.append("\"\n" + " } \n" + " } \n" + " attr { \n" + " key: \"padding\" \n" + " value { \n" + " s: \""); m_Prototext.append(paddingType); m_Prototext.append("\"\n" " } \n" @@ -101,14 +118,10 @@ struct Convolution2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfPa " attr { \n" " key: \"strides\" \n" " value { \n" - " list { \n" - " i: 1 \n" - " i: 1 \n" - " i: "); + " list { \n"); m_Prototext.append(strideString); - m_Prototext.append(" \n" - " i: 1 \n" - " } \n" + + m_Prototext.append(" } \n" " } \n" " } \n"); @@ -139,67 +152,118 @@ struct Convolution2dFixture : public armnnUtils::ParserPrototxtFixture<armnnTfPa "} \n"); // Manual height computation based on stride parameter. - BOOST_ASSERT_MSG(stride == 1 || stride==2, "Add support for strides other than 1 or 2."); - unsigned int dims[] = {1,2,3,1}; - if (stride == 2) + BOOST_ASSERT_MSG(stride == 1 || stride == 2, "Add support for strides other than 1 or 2."); + std::array<unsigned int, 4> dims; + if (dataLayout == "NHWC") { - dims[1]=3; + dims = { 1u, (stride == 2 ? 3u : 2u), 3u, 1u }; + } + else // dataLayout == "NCHW" + { + dims = { 1u, 1u, (stride == 2 ? 3u : 2u), 3u }; } - SetupSingleInputSingleOutput(armnn::TensorShape(4, dims), "graphInput", "potato"); + SetupSingleInputSingleOutput(armnn::TensorShape(4, dims.data()), "graphInput", "potato"); } }; -struct Convolution2dSameFixture : Convolution2dFixture +struct Convolution2dNhwcSameFixture : Convolution2dFixture +{ + Convolution2dNhwcSameFixture() : Convolution2dFixture("NHWC", "SAME", 1){} +}; +BOOST_FIXTURE_TEST_CASE(ParseConv2dNhwcSame, Convolution2dNhwcSameFixture) +{ + RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); +} + +struct Convolution2dNchwSameFixture : Convolution2dFixture { - Convolution2dSameFixture() : Convolution2dFixture("SAME", 1){} + Convolution2dNchwSameFixture() : Convolution2dFixture("NCHW", "SAME", 1){} }; -BOOST_FIXTURE_TEST_CASE(ParseConv2DSame, Convolution2dSameFixture) +BOOST_FIXTURE_TEST_CASE(ParseConv2dNchwSame, Convolution2dNchwSameFixture) { RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); } -struct Convolution2dValidFixture : Convolution2dFixture + +struct Convolution2dNhwcValidFixture : Convolution2dFixture +{ + Convolution2dNhwcValidFixture() : Convolution2dFixture("NHWC", "VALID", 1){} +}; +BOOST_FIXTURE_TEST_CASE(ParseConv2dNhwcValid, Convolution2dNhwcValidFixture) +{ + RunTest<4>({1, 2, 3, 4, 5, 6}, {4, 10}); +} + +struct Convolution2dNchwValidFixture : Convolution2dFixture { - Convolution2dValidFixture() : Convolution2dFixture("VALID", 1){} + Convolution2dNchwValidFixture() : Convolution2dFixture("NCHW", "VALID", 1){} }; -BOOST_FIXTURE_TEST_CASE(ParseConv2DValid, Convolution2dValidFixture) +BOOST_FIXTURE_TEST_CASE(ParseConv2dNchwValid, Convolution2dNchwValidFixture) { RunTest<4>({1, 2, 3, 4, 5, 6}, {4, 10}); } -struct Convolution2dStride2SameFixture : Convolution2dFixture +struct Convolution2dStride2NhwcSameFixture : Convolution2dFixture { - Convolution2dStride2SameFixture() : Convolution2dFixture("SAME", 2){} + Convolution2dStride2NhwcSameFixture() : Convolution2dFixture("NHWC", "SAME", 2){} }; -BOOST_FIXTURE_TEST_CASE(ParseConv2DStride2Same, Convolution2dStride2SameFixture) +BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NhwcSame, Convolution2dStride2NhwcSameFixture) +{ + RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {2, 4, 6.5, 8.5, 11, 13}); +} + +struct Convolution2dStride2NchwSameFixture : Convolution2dFixture +{ + Convolution2dStride2NchwSameFixture() : Convolution2dFixture("NCHW", "SAME", 2){} +}; +BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NchwSame, Convolution2dStride2NchwSameFixture) { RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {2, 4, 6.5, 8.5, 11, 13}); } -struct Convolution2dStride2ValidFixture : Convolution2dFixture +struct Convolution2dStride2NhwcValidFixture : Convolution2dFixture { - Convolution2dStride2ValidFixture() : Convolution2dFixture("VALID", 2){} + Convolution2dStride2NhwcValidFixture() : Convolution2dFixture("NHWC", "VALID", 2){} }; -BOOST_FIXTURE_TEST_CASE(ParseConv2DStride2Valid, Convolution2dStride2ValidFixture) +BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NhwcValid, Convolution2dStride2NhwcValidFixture) { RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {4, 10, 16}); } +struct Convolution2dStride2NchwValidFixture : Convolution2dFixture +{ + Convolution2dStride2NchwValidFixture() : Convolution2dFixture("NCHW", "VALID", 2){} +}; +BOOST_FIXTURE_TEST_CASE(ParseConv2dStride2NchwValid, Convolution2dStride2NchwValidFixture) +{ + RunTest<4>({1, 2, 3, 4, 5, 6, 7, 8, 9}, {4, 10, 16}); +} + + +struct Convolution2dDilation1NhwcFixture : Convolution2dFixture +{ + Convolution2dDilation1NhwcFixture() : Convolution2dFixture("NHWC", "SAME", 1, 1){} +}; +BOOST_FIXTURE_TEST_CASE(ParseConv2dDilation1Nhwc, Convolution2dDilation1NhwcFixture) +{ + RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); +} -struct Convolution2dDilation1Fixture : Convolution2dFixture +struct Convolution2dDilation1NchwFixture : Convolution2dFixture { - Convolution2dDilation1Fixture() : Convolution2dFixture("SAME", 1, 1){} + Convolution2dDilation1NchwFixture() : Convolution2dFixture("NCHW", "SAME", 1, 1){} }; -BOOST_FIXTURE_TEST_CASE(ParseConv2DDilation1, Convolution2dDilation1Fixture) +BOOST_FIXTURE_TEST_CASE(ParseConv2dDilation1Nchw, Convolution2dDilation1NchwFixture) { RunTest<4>({1, 2, 3, 4, 5, 6}, {2, 4, 4, 6.5f, 10 , 8.5f}); } -BOOST_AUTO_TEST_CASE(ParseConv2DDilation2) + +BOOST_AUTO_TEST_CASE(ParseConv2dDilation2) { const char* prototext = "" "node {\n" @@ -309,8 +373,7 @@ BOOST_AUTO_TEST_CASE(ParseConv2DDilation2) armnn::TensorShape tensorShape = { 1, 3, 3, 1 }; inputShapes["graphInput"] = tensorShape; armnnTfParser::ITfParserPtr parser = armnnTfParser::ITfParser::Create(); - BOOST_CHECK_THROW(parser->CreateNetworkFromString(prototext, inputShapes, { "potato" }), - armnn::ParseException); + BOOST_CHECK_THROW(parser->CreateNetworkFromString(prototext, inputShapes, { "potato" }), armnn::ParseException); } |