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author | Nina Drozd <nindro01@e112888-lin.galway.arm.com> | 2019-04-08 10:52:10 +0100 |
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committer | Nina Drozd <nina.drozd@arm.com> | 2019-04-08 15:28:19 +0100 |
commit | 0324f48e64edb99a5c8d819394545d97e0c2ae97 (patch) | |
tree | becfb745cc292c583703bea59536fdf49ea182c9 /src/armnnTfLiteParser | |
parent | 1b63d6c138f9d7c772c7dc325467018b557ff9ed (diff) | |
download | armnn-0324f48e64edb99a5c8d819394545d97e0c2ae97.tar.gz |
IVGCVSW-2844: Add TfLite Parser support for Split layer
* Added ParseSplit method
* New Unit test Split.cpp
* Updated TensorflowLiteSupport.md with new supported operator
Change-Id: Iec80ba9ad7b48db8e86589ebae77bd7d8ed38fb2
Signed-off-by: Nina Drozd <nina.drozd@arm.com>
Diffstat (limited to 'src/armnnTfLiteParser')
-rw-r--r-- | src/armnnTfLiteParser/TensorFlowLiteSupport.md | 2 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 89 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.hpp | 2 | ||||
-rw-r--r-- | src/armnnTfLiteParser/test/Split.cpp | 137 |
4 files changed, 229 insertions, 1 deletions
diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md index 84734c51b6..afbe2cec06 100644 --- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md +++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md @@ -48,6 +48,8 @@ The Arm NN SDK TensorFlow Lite parser currently supports the following operators * SPACE_TO_BATCH +* SPLIT + * SQUEEZE * STRIDED_SLICE diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index b9a3522736..c00c2188a9 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -464,6 +464,7 @@ TfLiteParser::TfLiteParser() m_ParserFunctions[tflite::BuiltinOperator_MUL] = &TfLiteParser::ParseMul; m_ParserFunctions[tflite::BuiltinOperator_MEAN] = &TfLiteParser::ParseMean; m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParser::ParsePad; + m_ParserFunctions[tflite::BuiltinOperator_SPLIT] = &TfLiteParser::ParseSplit; } void TfLiteParser::ResetParser() @@ -1851,6 +1852,94 @@ void TfLiteParser::ParseDetectionPostProcess(size_t subgraphIndex, size_t operat outputTensorIndexes[3]}); } +void TfLiteParser::ParseSplit(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.AsSplitOptions(); + + const unsigned int numSplits = CHECKED_NON_NEGATIVE(options->num_splits); + + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 2); + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), numSplits); + + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[1]); + + // This splitDim indicates the data format: 3 is the NHWC, 1 is the NCHW. + const unsigned int splitDim = static_cast<unsigned int>(axisTensorInfo.GetShape()[0]); + + // Armnn supports split along the channel dimension for data formats NHWC and NCHW. + if (splitDim == 0 || splitDim == 2) + { + throw ParseException( + boost::str( + boost::format( + "Dimension %1% for split is not supported by Armnn. %2%") + % splitDim + % CHECK_LOCATION().AsString())); + } + + auto inputDimSize = inputTensorInfo.GetNumDimensions(); + if (inputDimSize != MaxNumOfTensorDimensions) + { + throw ParseException( + boost::str( + boost::format( + "The number of dimensions: %1% for input tensors of the " + "split op should be %2% %3%") + % inputTensorInfo.GetNumDimensions() + % MaxNumOfTensorDimensions + % CHECK_LOCATION().AsString())); + } + + std::vector<unsigned int> splitterDimSizes(inputDimSize); + + // Add current input shape to splitterDimSizes + for (unsigned int i = 0; i < inputDimSize; ++i) + { + splitterDimSizes[i] = inputTensorInfo.GetShape()[i]; + } + + if (splitterDimSizes[splitDim] % numSplits != 0) + { + throw ParseException("Number of splits must evenly divide the dimension"); + } + splitterDimSizes[splitDim] /= numSplits; + + SplitterDescriptor splitDesc(numSplits); + for (unsigned int j = 0; j < numSplits; ++j) + { + // Set the size of the views. + for (unsigned int dimIdx = 0; dimIdx < splitterDimSizes.size(); ++dimIdx) + { + splitDesc.SetViewSize(j, dimIdx, splitterDimSizes[dimIdx]); + } + splitDesc.SetViewOriginCoord(j, splitDim, splitterDimSizes[splitDim] * j); + } + + auto layerName = boost::str(boost::format("Split:%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>(splitterDimSizes.size()), + splitterDimSizes.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); +} + armnn::IConnectableLayer* TfLiteParser::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer, unsigned int outputSlot, tflite::ActivationFunctionType activationType) diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp index 2895487214..e166dd5d8c 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -115,8 +115,8 @@ private: 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 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/Split.cpp b/src/armnnTfLiteParser/test/Split.cpp new file mode 100644 index 0000000000..774a416750 --- /dev/null +++ b/src/armnnTfLiteParser/test/Split.cpp @@ -0,0 +1,137 @@ +// +// 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 SplitFixture : public ParserFlatbuffersFixture +{ + explicit SplitFixture(const std::string & inputShape, + const std::string & axisShape, + const std::string & numSplits, + const std::string & outputShape1, + const std::string & outputShape2) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "SPLIT" } ], + "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": )" + axisShape + R"(, + "type": "INT32", + "buffer": 1, + "name": "axis", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + outputShape1 + R"( , + "type": "FLOAT32", + "buffer": 2, + "name": "outputTensor1", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + outputShape2 + R"( , + "type": "FLOAT32", + "buffer": 3, + "name": "outputTensor2", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + } + ], + "inputs": [ 0, 1 ], + "outputs": [ 2, 3 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0, 1 ], + "outputs": [ 2, 3 ], + "builtin_options_type": "SplitOptions", + "builtin_options": { + "num_splits": )" + numSplits + R"( + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ {}, {} ] + } + )"; + + Setup(); + } +}; + + +struct SimpleSplitFixture : SplitFixture +{ + SimpleSplitFixture() : SplitFixture( "[ 2, 2, 2, 2 ]", "[ 1 ]", "2", + "[ 2, 1, 2, 2 ]", "[ 2, 1, 2, 2 ]") + {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseAxisOneSplitTwo, SimpleSplitFixture) +{ + + RunTest<4, 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 } } }, + { {"outputTensor1", { 1.0f, 2.0f, 3.0f, 4.0f, 9.0f, 10.0f, 11.0f, 12.0f }}, + {"outputTensor2", { 5.0f, 6.0f, 7.0f, 8.0f, 13.0f, 14.0f, 15.0f, 16.0f }}}); +} + +struct SimpleSplitAxisThreeFixture : SplitFixture +{ + SimpleSplitAxisThreeFixture() : SplitFixture( "[ 2, 2, 2, 2 ]", "[ 3 ]", "2", + "[ 2, 2, 2, 1 ]", "[ 2, 2, 2, 1 ]") + {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseAxisThreeSplitTwo, SimpleSplitAxisThreeFixture) +{ + RunTest<4, 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 } } }, + { {"outputTensor1", { 1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f, 15.0f }}, + {"outputTensor2", { 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 16.0f } } } ); +} + +BOOST_AUTO_TEST_SUITE_END()
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