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Diffstat (limited to 'runtimes/neurun/src/kernel/cpu/ConcatLayer.cc')
-rw-r--r-- | runtimes/neurun/src/kernel/cpu/ConcatLayer.cc | 109 |
1 files changed, 109 insertions, 0 deletions
diff --git a/runtimes/neurun/src/kernel/cpu/ConcatLayer.cc b/runtimes/neurun/src/kernel/cpu/ConcatLayer.cc new file mode 100644 index 000000000..5fe5e3993 --- /dev/null +++ b/runtimes/neurun/src/kernel/cpu/ConcatLayer.cc @@ -0,0 +1,109 @@ +/* + * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright (C) 2017 The Android Open Source Project + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include "ConcatLayer.h" + +#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h" +#include "kernel/cpu/OperationUtils.h" + +namespace neurun +{ +namespace kernel +{ +namespace cpu +{ + +ConcatLayer::ConcatLayer() + : _inputDataPtrs(), _outputData(nullptr), _axis(0), _inputShapes(), _outputShape(), + _inputType(OperandType::SCALAR_FLOAT32) +{ + // DO NOTHING +} + +bool ConcatLayer::concatenationFloat32() +{ + int num_inputs = _inputShapes.size(); + std::vector<::tflite::Dims<4> *> inputDimsPtr(num_inputs); + std::vector<::tflite::Dims<4>> inputDims(num_inputs); + for (int i = 0; i < num_inputs; i++) + { + inputDims[i] = convertShapeToDims(_inputShapes[i]); + inputDimsPtr[i] = &inputDims[i]; + } + + std::vector<const float *> inputFloatPtrs; + + for (auto ptr : _inputDataPtrs) + { + inputFloatPtrs.emplace_back(reinterpret_cast<const float *>(ptr)); + } + + ::tflite::optimized_ops::Concatenation<::tflite::FusedActivationFunctionType::kNone, float>( + getNumberOfDimensions(_outputShape) - _axis - 1, inputFloatPtrs.data(), inputDimsPtr.data(), + num_inputs, reinterpret_cast<float *>(_outputData), convertShapeToDims(_outputShape)); + return true; +} +bool ConcatLayer::concatenationQuant8() +{ + int num_inputs = _inputShapes.size(); + std::vector<::tflite::Dims<4> *> inputDimsPtr(num_inputs); + std::vector<::tflite::Dims<4>> inputDims(num_inputs); + for (int i = 0; i < num_inputs; i++) + { + inputDims[i] = convertShapeToDims(_inputShapes[i]); + inputDimsPtr[i] = &inputDims[i]; + } + ::tflite::optimized_ops::Concatenation<::tflite::FusedActivationFunctionType::kNone, uint8_t>( + getNumberOfDimensions(_outputShape) - _axis - 1, _inputDataPtrs.data(), inputDimsPtr.data(), + num_inputs, _outputData, convertShapeToDims(_outputShape)); + return true; +} + +void ConcatLayer::configure(const std::vector<const uint8_t *> &inputDataPtrs, + const std::vector<Shape> &inputShapes, int32_t axis, + uint8_t *outputData, const Shape outputShape) +{ + _inputDataPtrs = inputDataPtrs; + + for (auto shape : inputShapes) + { + _inputShapes.emplace_back(shape); + _inputType = shape.type; + } + + _axis = axis; + + _outputData = outputData; + _outputShape = outputShape; +} + +void ConcatLayer::run() +{ + if (_inputType == OperandType::TENSOR_FLOAT32) + { + concatenationFloat32(); + } + else if (_inputType == OperandType::TENSOR_QUANT8_ASYMM) + { + throw std::runtime_error{"ConcatLayer : Not tested for TENSOR_QUANT8_ASYMM"}; + // concatenationQuant8(); + } +} + +} // namespace cpu +} // namespace kernel +} // namespace neurun |