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Diffstat (limited to 'runtime/onert/backend/cpu/kernel/PadLayer.cc')
-rw-r--r-- | runtime/onert/backend/cpu/kernel/PadLayer.cc | 70 |
1 files changed, 70 insertions, 0 deletions
diff --git a/runtime/onert/backend/cpu/kernel/PadLayer.cc b/runtime/onert/backend/cpu/kernel/PadLayer.cc new file mode 100644 index 000000000..393856178 --- /dev/null +++ b/runtime/onert/backend/cpu/kernel/PadLayer.cc @@ -0,0 +1,70 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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 "PadLayer.h" + +#include <cker/operation/Pad.h> + +namespace onert +{ +namespace backend +{ +namespace cpu +{ +namespace kernel +{ + +PadLayer::PadLayer() + : _input(nullptr), _output(nullptr), _padData(), _padRank(), _constantValueData() +{ + // DO NOTHING +} + +void PadLayer::padFloat32() +{ + nnfw::cker::Pad(_padData, _padRank, convertTensorToCkerShape(_input), + reinterpret_cast<const float *>(_input->buffer()), + convertTensorToCkerShape(_output), reinterpret_cast<float *>(_output->buffer()), + _constantValueData.f); +} +void PadLayer::padQuant8() { throw std::runtime_error("Quantized Pad isn't supported NYI"); } + +void PadLayer::configure(const operand::Tensor *input, operand::Tensor *output, + const int32_t *padData, int32_t padRank, uint8_t *constantValueData) +{ + _input = input; + _output = output; + _padData = padData; + _padRank = padRank; + _constantValueData.u8 = constantValueData; +} + +void PadLayer::run() +{ + if (_input->data_type() == OperandType::FLOAT32) + { + padFloat32(); + } + else if (_input->data_type() == OperandType::QUANT8_ASYMM) + { + padQuant8(); + } +} + +} // namespace kernel +} // namespace cpu +} // namespace backend +} // namespace onert |