From 66dedc700b2e2723f7c18f171739432fa92f0a33 Mon Sep 17 00:00:00 2001 From: Sadik Armagan Date: Tue, 10 Dec 2019 16:32:07 +0000 Subject: IVGCVSW-4193 Add QUANTIZE to the TfLite parser Signed-off-by: Sadik Armagan Change-Id: I53431c70edb64c9283ae556407cc07e54469d8cc --- src/armnnTfLiteParser/TfLiteParser.cpp | 41 ++++++++--- src/armnnTfLiteParser/TfLiteParser.hpp | 1 + src/armnnTfLiteParser/test/Quantize.cpp | 121 ++++++++++++++++++++++++++++++++ 3 files changed, 155 insertions(+), 8 deletions(-) create mode 100644 src/armnnTfLiteParser/test/Quantize.cpp diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 22d65645a3..69bd59a21f 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -442,36 +442,37 @@ TfLiteParser::TfLiteParser(const Optional& o , m_ParserFunctions(tflite::BuiltinOperator_MAX+1, &TfLiteParser::ParseUnsupportedOperator) { // register supported operators + m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParser::ParseAdd; m_ParserFunctions[tflite::BuiltinOperator_AVERAGE_POOL_2D] = &TfLiteParser::ParseAveragePool2D; m_ParserFunctions[tflite::BuiltinOperator_BATCH_TO_SPACE_ND] = &TfLiteParser::ParseBatchToSpaceND; m_ParserFunctions[tflite::BuiltinOperator_CONCATENATION] = &TfLiteParser::ParseConcatenation; m_ParserFunctions[tflite::BuiltinOperator_CONV_2D] = &TfLiteParser::ParseConv2D; + m_ParserFunctions[tflite::BuiltinOperator_CUSTOM] = &TfLiteParser::ParseCustomOperator; m_ParserFunctions[tflite::BuiltinOperator_DEPTHWISE_CONV_2D] = &TfLiteParser::ParseDepthwiseConv2D; m_ParserFunctions[tflite::BuiltinOperator_DEQUANTIZE] = &TfLiteParser::ParseDequantize; - m_ParserFunctions[tflite::BuiltinOperator_CUSTOM] = &TfLiteParser::ParseCustomOperator; m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED] = &TfLiteParser::ParseFullyConnected; m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC] = &TfLiteParser::ParseLogistic; m_ParserFunctions[tflite::BuiltinOperator_L2_NORMALIZATION] = &TfLiteParser::ParseL2Normalization; m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D] = &TfLiteParser::ParseMaxPool2D; m_ParserFunctions[tflite::BuiltinOperator_MAXIMUM] = &TfLiteParser::ParseMaximum; + m_ParserFunctions[tflite::BuiltinOperator_MEAN] = &TfLiteParser::ParseMean; m_ParserFunctions[tflite::BuiltinOperator_MINIMUM] = &TfLiteParser::ParseMinimum; + m_ParserFunctions[tflite::BuiltinOperator_MUL] = &TfLiteParser::ParseMul; + m_ParserFunctions[tflite::BuiltinOperator_PACK] = &TfLiteParser::ParsePack; + m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParser::ParsePad; + m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE] = &TfLiteParser::ParseQuantize; m_ParserFunctions[tflite::BuiltinOperator_RELU] = &TfLiteParser::ParseRelu; m_ParserFunctions[tflite::BuiltinOperator_RELU6] = &TfLiteParser::ParseRelu6; m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParser::ParseReshape; m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR] = &TfLiteParser::ParseResizeBilinear; m_ParserFunctions[tflite::BuiltinOperator_RESIZE_NEAREST_NEIGHBOR] = &TfLiteParser::ParseResizeNearestNeighbor; + m_ParserFunctions[tflite::BuiltinOperator_SLICE] = &TfLiteParser::ParseSlice; m_ParserFunctions[tflite::BuiltinOperator_SOFTMAX] = &TfLiteParser::ParseSoftmax; m_ParserFunctions[tflite::BuiltinOperator_SPACE_TO_BATCH_ND] = &TfLiteParser::ParseSpaceToBatchND; + m_ParserFunctions[tflite::BuiltinOperator_SPLIT] = &TfLiteParser::ParseSplit; m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE] = &TfLiteParser::ParseSqueeze; m_ParserFunctions[tflite::BuiltinOperator_STRIDED_SLICE] = &TfLiteParser::ParseStridedSlice; m_ParserFunctions[tflite::BuiltinOperator_SUB] = &TfLiteParser::ParseSub; - m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParser::ParseAdd; - m_ParserFunctions[tflite::BuiltinOperator_MUL] = &TfLiteParser::ParseMul; - m_ParserFunctions[tflite::BuiltinOperator_MEAN] = &TfLiteParser::ParseMean; - m_ParserFunctions[tflite::BuiltinOperator_PACK] = &TfLiteParser::ParsePack; - m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParser::ParsePad; - m_ParserFunctions[tflite::BuiltinOperator_SLICE] = &TfLiteParser::ParseSlice; - m_ParserFunctions[tflite::BuiltinOperator_SPLIT] = &TfLiteParser::ParseSplit; m_ParserFunctions[tflite::BuiltinOperator_TANH] = &TfLiteParser::ParseTanH; m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE] = &TfLiteParser::ParseTranspose; m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE_CONV] = &TfLiteParser::ParseTransposeConv; @@ -1746,6 +1747,30 @@ void TfLiteParser::ParsePad(size_t subgraphIndex, size_t operatorIndex) RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); } +void TfLiteParser::ParseQuantize(size_t subgraphIndex, size_t operatorIndex) +{ + CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); + + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto layerName = boost::str(boost::format("Quantize:%1%:%2%") % subgraphIndex % operatorIndex); + + IConnectableLayer* layer = m_Network->AddQuantizeLayer(layerName.c_str()); + BOOST_ASSERT(layer != nullptr); + + TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + 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); +} void TfLiteParser::ParseRelu(size_t subgraphIndex, size_t operatorIndex) { diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index a8241f6650..42ea1a0372 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -113,6 +113,7 @@ private: void ParsePack(size_t subgraphIndex, size_t operatorIndex); void ParsePad(size_t subgraphIndex, size_t operatorIndex); void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm); + void ParseQuantize(size_t subgraphIndex, size_t operatorIndex); void ParseRelu(size_t subgraphIndex, size_t operatorIndex); void ParseRelu6(size_t subgraphIndex, size_t operatorIndex); void ParseReshape(size_t subgraphIndex, size_t operatorIndex); diff --git a/src/armnnTfLiteParser/test/Quantize.cpp b/src/armnnTfLiteParser/test/Quantize.cpp new file mode 100644 index 0000000000..ca5e6d5091 --- /dev/null +++ b/src/armnnTfLiteParser/test/Quantize.cpp @@ -0,0 +1,121 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +#include +#include + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + + struct QuantizeFixture : public ParserFlatbuffersFixture + { + explicit QuantizeFixture(const std::string & inputShape, + const std::string & outputShape, + const std::string & dataType) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "QUANTIZE" } ], + "subgraphs": [ { + "tensors": [ + { + "shape": )" + inputShape + R"(, + "type": "FLOAT32", + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + outputShape + R"( , + "type": )" + dataType + R"(, + "buffer": 1, + "name": "outputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.5 ], + "zero_point": [ 0 ], + } + } + ], + "inputs": [ 0 ], + "outputs": [ 1 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0 ], + "outputs": [ 1 ], + "builtin_options_type": "QuantizeOptions", + "builtin_options": { + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { }, + { }, + ] + } + )"; + SetupSingleInputSingleOutput("inputTensor", "outputTensor"); + } + }; + + struct SimpleQuantizeFixtureQAsymm8 : QuantizeFixture + { + SimpleQuantizeFixtureQAsymm8() : QuantizeFixture("[ 1, 6 ]", + "[ 1, 6 ]", + "UINT8") {} + }; + + BOOST_FIXTURE_TEST_CASE(SimpleQuantizeQAsymm8, SimpleQuantizeFixtureQAsymm8) + { + RunTest<2, armnn::DataType::Float32, armnn::DataType::QuantisedAsymm8>( + 0, + {{"inputTensor", { 0.0f, 1.5f, 7.5f, 150.0f, 300.0f, 382.5f }}}, + {{"outputTensor", { 0u, 1u, 5u, 100u, 200u, 255u }}}); + } + + struct SimpleQuantizeFixtureQSymm16 : QuantizeFixture + { + SimpleQuantizeFixtureQSymm16() : QuantizeFixture("[ 1, 6 ]", + "[ 1, 6 ]", + "INT16") {} + }; + + BOOST_FIXTURE_TEST_CASE(SimpleQuantizeQsymm16, SimpleQuantizeFixtureQSymm16) + { + RunTest<2, armnn::DataType::Float32, armnn::DataType::QuantisedSymm16>( + 0, + {{"inputTensor", { 0.0f, 1.5f, 7.5f, 49150.5f, -1.5f,-49152.0f }}}, + {{"outputTensor", { 0, 1, 5, 32767, -1, -32768 }}}); + } + + struct SimpleQuantizeFixtureQSymmS8 : QuantizeFixture + { + SimpleQuantizeFixtureQSymmS8() : QuantizeFixture("[ 1, 6 ]", + "[ 1, 6 ]", + "INT8") {} + }; + + BOOST_FIXTURE_TEST_CASE(SimpleQuantizeQSymmS8, SimpleQuantizeFixtureQSymmS8) + { + RunTest<2, armnn::DataType::Float32, armnn::DataType::QSymmS8>( + 0, + {{"inputTensor", { 0.0f, 1.5f, 7.5f, 190.5f, -192.0f, -1.5f }}}, + {{"outputTensor", { 0, 1, 5, 127, -128, -1 }}}); + } + +BOOST_AUTO_TEST_SUITE_END() -- cgit v1.2.1