diff options
author | Sadik Armagan <sadik.armagan@arm.com> | 2021-02-03 09:29:30 +0000 |
---|---|---|
committer | Sadik Armagan <sadik.armagan@arm.com> | 2021-02-03 09:29:47 +0000 |
commit | 0c3ea5b8ac5ad8ca516930a0491afb1d1074e45b (patch) | |
tree | 47ff1e9c1c70a3b134c1e9063dada66d70a7c963 /src/armnnTfLiteParser | |
parent | 84f41eb74765bd93307f3c6b334354c486dc746d (diff) | |
download | armnn-0c3ea5b8ac5ad8ca516930a0491afb1d1074e45b.tar.gz |
backends/reference: Add ReduceSum operation support
This patch addes ReduceSum operation support for reference backend,
which computes the sum of elements across dimensions of a tensor.
Changelog v1:
- Fix file header descriptions.
Chagelog v2:
- Fix line limit issue.
- Fix type conversion issue.
Changelog v3:
- Remove tabs.
- Modify newly added file headers.
Changelog v4:
- Symbol on header isn't allowed so drop it from newly added file headers.
Changelog v5:
- Remove tabs, fix the use of brackets and align lines correctly.
Changelog v6:
- Add serializer and deserializer support.
Changelog v7:
- Fix build error add missed code.
Changelog v8:
- Rename ReduceSumDecriptor to ReduceDescriptor
- Update m_KeepDims field data type to bool on ReduceDescriptor
- Add ReduceOperation field to ReduceDescriptor
- Rename ReduceSumLayer to ReduceLayer
- Update ReduceLayer to use ReduceDescriptor
- Update ReduceLayer::ValidateTensorShapesFromInputs() function
- Rename RefReduceSumWokload to RefReduceWorkload
- Update workload to use ReduceDescriptor
- Update workload to use Decoders and Encoders
- Remove ReduceSum.hpp and ReduceSum.cpp
- Added Reduce.hpp and Reduce.cpp
- Move Mean.cpp (which is implementing REDUCE_MEAN) functionality to Reduce.cpp
- Update RefMeanWorkload to call Reduce function with ReduceOperation::Mean argument
- Remove Mean.hpp and Mean.cpp
- Update the Serializer/Deserializer ArmnnSchema.fbs for ReduceLayer, ReduceDescriptor, and ReduceOperation
- Update Serializer and Deserializer for serializing/parsing ReduceLayer
- Added TfLiter parser Sum test for REDUCE_SUM operator
- Make corresponding changes on front-end and Ref backend to support REDUCE_SUM operator
Changelog v9:
- Fixed build errors.
Change-Id: I8c8e034f3df73f9565b3c18eff51ecca6c542195
Signed-off-by: Inki Dae <inki.dae@samsung.com>
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Diffstat (limited to 'src/armnnTfLiteParser')
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 54 | ||||
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.hpp | 1 | ||||
-rw-r--r-- | src/armnnTfLiteParser/test/Sum.cpp | 110 |
3 files changed, 165 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 1a1e854395..db60224999 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -10,6 +10,7 @@ #include <armnn/Exceptions.hpp> #include <armnn/Logging.hpp> #include <armnn/Tensor.hpp> +#include <armnnUtils/TensorUtils.hpp> #include <armnn/TypesUtils.hpp> #include <armnn/utility/Assert.hpp> #include <armnn/utility/IgnoreUnused.hpp> @@ -580,6 +581,7 @@ TfLiteParser::TfLiteParser(const Optional<ITfLiteParser::TfLiteParserOptions>& o 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_SUM] = &TfLiteParser::ParseSum; m_ParserFunctions[tflite::BuiltinOperator_TANH] = &TfLiteParser::ParseTanH; m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE] = &TfLiteParser::ParseTranspose; m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE_CONV] = &TfLiteParser::ParseTransposeConv; @@ -2994,6 +2996,58 @@ void TfLiteParser::ParseDepthToSpace(size_t subgraphIndex, size_t operatorIndex) RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); } +void TfLiteParser::ParseSum(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.AsReducerOptions(); + + 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(), 1); + + auto layerName = fmt::format("Sum:{}:{}", subgraphIndex, operatorIndex); + + armnn::TensorInfo inputTensorInfo0 = ToTensorInfo(inputs[0]); + armnn::TensorInfo inputTensorInfo1 = ToTensorInfo(inputs[1]); + TensorShape input0Shape = inputTensorInfo0.GetShape(); + + ReduceDescriptor desc; + + BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[1]->buffer); + // Get const axis value from model and set it to descriptor. + if (axisBufferPtr != nullptr) + { + for (uint32_t i = 0; i < inputTensorInfo1.GetNumElements(); ++i) + { + desc.m_vAxis.push_back(armnnUtils::GetUnsignedAxis(inputTensorInfo0.GetNumDimensions(), + axisBufferPtr->data.data()[i])); + } + } + + desc.m_TargetHeight = input0Shape[1]; + desc.m_TargetWidth = input0Shape[2]; + desc.m_KeepDims = options->keep_dims; + desc.m_ReduceOperation = armnn::ReduceOperation::Sum; + + // Register a new layer object, Sum. + IConnectableLayer *layer = m_Network->AddReduceLayer(desc, layerName.c_str()); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + // Register input tensor to the layer. + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); + + // Register output tensor to the layer. + 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 418180fd25..5f180603f0 100644 --- a/src/armnnTfLiteParser/TfLiteParser.hpp +++ b/src/armnnTfLiteParser/TfLiteParser.hpp @@ -135,6 +135,7 @@ private: 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 ParseSum(size_t subgraphIndex, size_t operatorIndex); void ParseDiv(size_t subgraphIndex, size_t operatorIndex); void ParseTanH(size_t subgraphIndex, size_t operatorIndex); void ParseTranspose(size_t subgraphIndex, size_t operatorIndex); diff --git a/src/armnnTfLiteParser/test/Sum.cpp b/src/armnnTfLiteParser/test/Sum.cpp new file mode 100644 index 0000000000..22b19ae058 --- /dev/null +++ b/src/armnnTfLiteParser/test/Sum.cpp @@ -0,0 +1,110 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. 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 SumFixture : public ParserFlatbuffersFixture +{ + explicit SumFixture(const std::string& inputShape, + const std::string& outputShape, + const std::string& axisShape, + const std::string& axisData) + { + m_JsonString = R"( + { + "version": 3, + "operator_codes": [ { "builtin_code": "SUM" } ], + "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": "FLOAT32", + "buffer": 1, + "name": "outputTensor", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + }, + { + "shape": )" + axisShape + R"( , + "type": "INT32", + "buffer": 2, + "name": "axis", + "quantization": { + "min": [ 0.0 ], + "max": [ 255.0 ], + "scale": [ 1.0 ], + "zero_point": [ 0 ], + } + } + ], + "inputs": [ 0 ], + "outputs": [ 1 ], + "operators": [ + { + "opcode_index": 0, + "inputs": [ 0 , 2 ], + "outputs": [ 1 ], + "builtin_options_type": "ReducerOptions", + "builtin_options": { + "keep_dims": true, + }, + "custom_options_format": "FLEXBUFFERS" + } + ], + } ], + "buffers" : [ + { }, + { }, + { "data": )" + axisData + R"(, }, + ] + } + )"; + SetupSingleInputSingleOutput("inputTensor", "outputTensor"); + } +}; + +struct SimpleSumFixture : public SumFixture +{ + SimpleSumFixture() : SumFixture("[ 1, 3, 2, 4 ]", "[ 1, 1, 1, 4 ]", "[ 2 ]", "[ 1, 2 ]") {} +}; + +BOOST_FIXTURE_TEST_CASE(ParseSum, SimpleSumFixture) +{ + RunTest<4, armnn::DataType::Float32, armnn::DataType::Float32> + (0, {{ "inputTensor", { 1.0f, 2.0f, 3.0f, 4.0f, + 5.0f, 6.0f, 7.0f, 8.0f, + + 10.0f, 20.0f, 30.0f, 40.0f, + 50.0f, 60.0f, 70.0f, 80.0f, + + 100.0f, 200.0f, 300.0f, 400.0f, + 500.0f, 600.0f, 700.0f, 800.0f } } }, + {{ "outputTensor", { 666.0f, 888.0f, 1110.0f, 1332.0f } } }); +} + +BOOST_AUTO_TEST_SUITE_END() |