/**************************************************************************** * * Copyright (c) 2020 Vivante Corporation * * Permission is hereby granted, free of charge, to any person obtaining a * copy of this software and associated documentation files (the "Software"), * to deal in the Software without restriction, including without limitation * the rights to use, copy, modify, merge, publish, distribute, sublicense, * and/or sell copies of the Software, and to permit persons to whom the * Software is furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER * DEALINGS IN THE SOFTWARE. * *****************************************************************************/ #ifndef TIM_LAYOUT_INFER_ADDN_LAYOUT_INFERENCE_H_ #define TIM_LAYOUT_INFER_ADDN_LAYOUT_INFERENCE_H_ #include "ops/op_layout_inference.h" #include "operation_private.h" #include "tim/vx/ops/addn.h" namespace tim { namespace transform { class AddNLayoutInfer : public OpLayoutInfer { public: AddNLayoutInfer( const std::shared_ptr& op, std::shared_ptr& context) : OpLayoutInfer(op, context) {} void OnInputs( std::vector>& next_tensors) override { auto required_pv = AlignPermuteVectorForMutilInputs(); auto addn = op_->Clone(context_->infer_graph_); for (const auto& i_src : op_->impl()->InputsTensor()) { (*addn).BindInput(context_->GetMapedTensor(i_src)); } auto infer_out = CreateOutputsTensor(required_pv); (*addn).BindOutput(infer_out[0]); context_->SetPermuteVector(op_->impl()->OutputsTensor()[0], required_pv); next_tensors.push_back(op_->impl()->OutputsTensor()[0]); } }; } // namespace transform } // namespace tim #endif