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author | Chunseok Lee <chunseok.lee@samsung.com> | 2020-12-14 14:43:04 +0900 |
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committer | Chunseok Lee <chunseok.lee@samsung.com> | 2020-12-14 14:43:04 +0900 |
commit | 12d88feea8573f8490629cf62fc342b152e57d65 (patch) | |
tree | 3c734cc4d629834d2d523f4575ef84cd64684e57 /runtime/onert/backend/cpu/ops/AddNLayer.cc | |
parent | d6b371e095d737922187a518b8faba1ef6f3a2b1 (diff) | |
download | nnfw-12d88feea8573f8490629cf62fc342b152e57d65.tar.gz nnfw-12d88feea8573f8490629cf62fc342b152e57d65.tar.bz2 nnfw-12d88feea8573f8490629cf62fc342b152e57d65.zip |
Imported Upstream version 1.11.0upstream/1.11.0
Diffstat (limited to 'runtime/onert/backend/cpu/ops/AddNLayer.cc')
-rw-r--r-- | runtime/onert/backend/cpu/ops/AddNLayer.cc | 71 |
1 files changed, 71 insertions, 0 deletions
diff --git a/runtime/onert/backend/cpu/ops/AddNLayer.cc b/runtime/onert/backend/cpu/ops/AddNLayer.cc new file mode 100644 index 000000000..5c0395dcc --- /dev/null +++ b/runtime/onert/backend/cpu/ops/AddNLayer.cc @@ -0,0 +1,71 @@ +/* + * Copyright (c) 2020 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 "AddNLayer.h" + +#include "OperationUtils.h" + +#include <cker/operation/AddN.h> +#include <assert.h> + +namespace onert +{ +namespace backend +{ +namespace cpu +{ +namespace ops +{ + +void AddNLayer::configure(std::vector<const IPortableTensor *> &&inputs, IPortableTensor *output) +{ + _inputs = std::move(inputs); + _output = output; +} + +void AddNLayer::run() +{ + size_t input_size = _inputs.size(); + if (_output->data_type() == ir::DataType::INT32) + { + std::vector<const int32_t *> input_buffers(input_size); + for (size_t i = 0; i < input_size; i++) + { + input_buffers[i] = reinterpret_cast<int32_t *>(_inputs[i]->buffer()); + } + AddN(getTensorShape(_inputs[0]), input_size, input_buffers.data(), + reinterpret_cast<int32_t *>(_output->buffer())); + } + else if (_output->data_type() == ir::DataType::FLOAT32) + { + std::vector<const float *> input_buffers(input_size); + for (size_t i = 0; i < input_size; i++) + { + input_buffers[i] = reinterpret_cast<float *>(_inputs[i]->buffer()); + } + AddN(getTensorShape(_inputs[0]), input_size, input_buffers.data(), + reinterpret_cast<float *>(_output->buffer())); + } + else + { + throw std::runtime_error("AddN: unsupported data type"); + } +} + +} // namespace ops +} // namespace cpu +} // namespace backend +} // namespace onert |