/**************************************************************************** * * 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_PAD_LAYOUT_INFERENCE_H_ #define TIM_LAYOUT_INFER_PAD_LAYOUT_INFERENCE_H_ #include "tim/vx/ops/pad.h" #include "src/tim/transform/ops/op_layout_inference.h" #include "src/tim/transform/permute_vector.h" #include "src/tim/vx/operation_private.h" namespace tim { namespace transform { class PadLayoutInfer : public OpLayoutInfer { public: PadLayoutInfer( const std::shared_ptr op, std::shared_ptr& context) : OpLayoutInfer(op, context) {} void OnInputs( std::vector>& next_tensors) override { assert(op_->impl()->InputsTensor().size() == 1); auto i_src = op_->impl()->InputsTensor()[0]; auto input_pv = context_->GetPermuteVector(i_src); uint32_t dim_num = op_->impl()->node()->nn_param.pad.dim_num; std::vector front_size(dim_num); std::vector back_size(dim_num); memcpy(front_size.data(), op_->impl()->node()->nn_param.pad.front_size, sizeof(uint32_t) * dim_num); memcpy(back_size.data(), op_->impl()->node()->nn_param.pad.back_size, sizeof(uint32_t) * dim_num); int32_t pad_value = op_->impl()->node()->nn_param.pad.const_val; if (!input_pv->IsAligned()) { front_size = MapPadding(input_pv->AsStdVec(), front_size); back_size = MapPadding(input_pv->AsStdVec(), back_size); } auto pad = context_->infer_graph_->CreateOperation( front_size, back_size, pad_value); auto out_infer = CreateOutputsTensor(input_pv); (*pad).BindInput(context_->GetMapedTensor(i_src)); (*pad).BindOutput(out_infer[0]); context_->SetPermuteVector(op_->impl()->OutputsTensor()[0], input_pv); next_tensors.push_back(op_->impl()->OutputsTensor()[0]); } }; } // namespace transform } // namespace tim #endif