diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/armnnTfLiteParser/TensorFlowLiteSupport.md | 2 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 84 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.hpp | 13 | ||||
-rw-r--r-- | src/armnnTfLiteParser/test/Unpack.cpp | 119 |
4 files changed, 212 insertions, 6 deletions
diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 821aecc9ec..dc163340aa 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -58,6 +58,8 @@ The Arm NN SDK TensorFlow Lite parser currently supports the following operators * TANH +* UNPACK + ## Custom Operator * TFLite_Detection_PostProcess diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index f689deedf6..86688add9d 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -468,6 +468,7 @@ TfLiteParser::TfLiteParser() 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_UNPACK] = &TfLiteParser::ParseUnpack; } void TfLiteParser::ResetParser() @@ -1867,6 +1868,83 @@ void TfLiteParser::ParseDetectionPostProcess(size_t subgraphIndex, size_t operat outputTensorIndexes[3]}); } +void TfLiteParser::ParseUnpack(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.AsUnpackOptions(); + + // This unpackAxis indicates the axis to unpack + const unsigned int unpackAxis = CHECKED_NON_NEGATIVE(options->axis); + + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + unsigned int unpackNum = CHECKED_NON_NEGATIVE(options->num); + // If num is not defined, automatically infer from the length of the dimension axis. + if(unpackNum == 0) + { + unpackNum = inputTensorInfo.GetShape()[unpackAxis]; + } + + // If unpack number cannot be inferred and is still zero, throw ParseException. + if(unpackNum == 0) + { + throw ParseException("Number to unpack must greater than zero."); + } + + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), unpackNum); + + auto inputDimSize = inputTensorInfo.GetNumDimensions(); + std::vector<unsigned int> unpackDimSizes(inputDimSize); + + // Add current input shape to unpackDimSizes + for (unsigned int i = 0; i < inputDimSize; ++i) + { + unpackDimSizes[i] = inputTensorInfo.GetShape()[i]; + } + + if (unpackDimSizes[unpackAxis] != unpackNum) + { + throw ParseException("Number to unpack must be the same as length of the dimension to " + "unpack along."); + } + + unpackDimSizes[unpackAxis] /= unpackNum; + + SplitterDescriptor splitDesc(unpackNum, static_cast<unsigned int>(unpackDimSizes.size())); + for (unsigned int j = 0; j < unpackNum; ++j) + { + // Set the size of the views. + for (unsigned int dimIdx = 0; dimIdx < unpackDimSizes.size(); ++dimIdx) + { + splitDesc.SetViewSize(j, dimIdx, unpackDimSizes[dimIdx]); + } + splitDesc.SetViewOriginCoord(j, unpackAxis, unpackDimSizes[unpackAxis] * j); + } + + auto layerName = boost::str(boost::format("Unpack:%1%:%2%") % subgraphIndex % operatorIndex); + IConnectableLayer* layer = m_Network->AddSplitterLayer(splitDesc, layerName.c_str()); + + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); + + TensorShape outShape = TensorShape(static_cast<unsigned int>(unpackDimSizes.size()), + unpackDimSizes.data()); + + for (unsigned int k = 0; k < layer->GetNumOutputSlots(); ++k) + { + layer->GetOutputSlot(k).SetTensorInfo(armnn::TensorInfo(outShape, + inputTensorInfo.GetDataType())); + } + + auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes); +} + void TfLiteParser::ParseSplit(size_t subgraphIndex, size_t operatorIndex) { CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); @@ -1876,6 +1954,12 @@ void TfLiteParser::ParseSplit(size_t subgraphIndex, size_t operatorIndex) const unsigned int numSplits = CHECKED_NON_NEGATIVE(options->num_splits); + // If number of splits cannot be inferred and is zero, throw ParseException. + if(numSplits == 0) + { + throw ParseException("Number to splits must greater than zero."); + } + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); CHECK_VALID_SIZE(inputs.size(), 2); auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index a3ef22fa7e..929af1f0db 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -91,6 +91,7 @@ private: void ParseUnsupportedOperator(size_t subgraphIndex, size_t operatorIndex); void ParseActivation(size_t subgraphIndex, size_t operatorIndex, armnn::ActivationFunction activationType); + void ParseAdd(size_t subgraphIndex, size_t operatorIndex); void ParseAveragePool2D(size_t subgraphIndex, size_t operatorIndex); void ParseBatchToSpaceND(size_t subgraphIndex, size_t operatorIndex); void ParseConcatenation(size_t subgraphIndex, size_t operatorIndex); @@ -101,23 +102,23 @@ private: void ParseLogistic(size_t subgraphIndex, size_t operatorIndex); void ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex); void ParseMaximum(size_t subgraphIndex, size_t operatorIndex); + void ParseMean(size_t subgraphIndex, size_t operatorIndex); void ParseMinimum(size_t subgraphIndex, size_t operatorIndex); + void ParseMul(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 ParseRelu(size_t subgraphIndex, size_t operatorIndex); void ParseRelu6(size_t subgraphIndex, size_t operatorIndex); void ParseReshape(size_t subgraphIndex, size_t operatorIndex); void ParseResizeBilinear(size_t subgraphIndex, size_t operatorIndex); void ParseSoftmax(size_t subgraphIndex, size_t operatorIndex); void ParseSpaceToBatchND(size_t subgraphIndex, size_t operatorIndex); + void ParseSplit(size_t subgraphIndex, size_t operatorIndex); void ParseSqueeze(size_t subgraphIndex, size_t operatorIndex); void ParseStridedSlice(size_t subgraphIndex, size_t operatorIndex); void ParseSub(size_t subgraphIndex, size_t operatorIndex); - void ParseAdd(size_t subgraphIndex, size_t operatorIndex); - void ParseMul(size_t subgraphIndex, size_t operatorIndex); - void ParseMean(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 ParseSplit(size_t subgraphIndex, size_t operatorIndex); void ParseTanH(size_t subgraphIndex, size_t operatorIndex); + void ParseUnpack(size_t subgraphIndex, size_t operatorIndex); void RegisterProducerOfTensor(size_t subgraphIndex, size_t tensorIndex, armnn::IOutputSlot* slot); void RegisterConsumerOfTensor(size_t subgraphIndex, size_t tensorIndex, armnn::IInputSlot* slot); diff --git a/src/armnnTfLiteParser/test/Unpack.cpp b/src/armnnTfLiteParser/test/Unpack.cpp new file mode 100644 index 0000000000..10e682e36a --- /dev/null +++ b/src/armnnTfLiteParser/test/Unpack.cpp @@ -0,0 +1,119 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include <boost/test/unit_test.hpp> +#include "ParserFlatbuffersFixture.hpp" +#include "../TfLiteParser.hpp" + +#include <string> +#include <iostream> + +BOOST_AUTO_TEST_SUITE(TensorflowLiteParser) + +struct UnpackFixture : public ParserFlatbuffersFixture +{ + explicit UnpackFixture(const std::string & inputShape, + const unsigned int numberOfOutputs, + const std::string & outputShape, + const std::string & axis, + const std::string & num) + { + // As input index is 0, output indexes start at 1 + std::string outputIndexes = "1"; + for(unsigned int i = 1; i < numberOfOutputs; i++) + { + outputIndexes += ", " + std::to_string(i+1); + } + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "UNPACK" } ], + "subgraphs": [ { + "tensors": [ + { + "shape": )" + inputShape + R"(, + "type": "FLOAT32", + "buffer": 0, + "name": "inputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + },)"; + // Append the required number of outputs for this UnpackFixture. + // As input index is 0, output indexes start at 1. + for(unsigned int i = 0; i < numberOfOutputs; i++) + { + m_JsonString += R"( + { + "shape": )" + outputShape + R"( , + "type": "FLOAT32", + "buffer": )" + std::to_string(i + 1) + R"(, + "name": "outputTensor)" + std::to_string(i + 1) + R"(", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + },)"; + } + m_JsonString += R"( + ], + "inputs": [ 0 ], + "outputs": [ )" + outputIndexes + R"( ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0 ], + "outputs": [ )" + outputIndexes + R"( ], + "builtin_options_type": "UnpackOptions", + "builtin_options": { + "axis": )" + axis; + + if(!num.empty()) + { + m_JsonString += R"(, + "num" : )" + num; + } + + m_JsonString += R"( + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { }, + { } + ] + } + )"; + Setup(); + } +}; + +struct DefaultUnpackAxisZeroFixture : UnpackFixture +{ + DefaultUnpackAxisZeroFixture() : UnpackFixture("[ 4, 1, 6 ]", 4, "[ 1, 6 ]", "0", "") {} +}; + +BOOST_FIXTURE_TEST_CASE(UnpackAxisZeroNumIsDefaultNotSpecified, DefaultUnpackAxisZeroFixture) +{ + RunTest<2, armnn::DataType::Float32>( + 0, + { {"inputTensor", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, + 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, + 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, + 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } } }, + { {"outputTensor1", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }}, + {"outputTensor2", { 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }}, + {"outputTensor3", { 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f }}, + {"outputTensor4", { 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }} }); +} + +BOOST_AUTO_TEST_SUITE_END() |