/**************************************************************************** * * Copyright (c) 2020-2023 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_BIDIRECTIONAL_RNN_LAYOUT_INFERENCE_H_ #define TIM_LAYOUT_INFER_BIDIRECTIONAL_RNN_LAYOUT_INFERENCE_H_ #include "tim/vx/ops/reshape.h" #include "tim/vx/ops/nbg.h" #include "tim/vx/ops/transpose.h" #include "tim/vx/ops/batchnorm.h" #include "tim/vx/ops/clip.h" #include "ops/op_layout_inference.h" #include "permute_vector.h" #include "builtin_op_impl.h" namespace tim { namespace transform { class BidirectionalRnnLayoutInfer : public OpLayoutInfer { public: BidirectionalRnnLayoutInfer( const std::shared_ptr op, std::shared_ptr& context) : OpLayoutInfer(op, context) {} // reverse any applied permute on it's input tensor void OnInputs( std::vector>& next_tensors) override { ReverseInputsPermuteVector(); auto cloned_op = op_->Clone(context_->infer_graph_); for (const auto& i_src : op_->impl()->InputsTensor()) { std::shared_ptr infer_tensor; std::shared_ptr required_pv; if ((i_src->IsConstTensor() && !(i_src->GetSpec().attr_ & vx::TensorAttribute::INPUT))) { infer_tensor = context_->infer_graph_->CreateTensor( i_src->GetSpec(), i_src->GetDataRef()); context_->UpdateTensorMap(i_src, infer_tensor); } if (i_src->GetId() == (uint32_t)-1) { infer_tensor = context_->infer_graph_->CreateTensorPlaceHolder(); context_->UpdateTensorMap(i_src, infer_tensor); } required_pv = MakeShared(i_src->GetShape().size()); context_->SetPermuteVector(i_src, required_pv); } for (const auto& i_src : op_->impl()->InputsTensor()) { (*cloned_op).BindInput(context_->GetMapedTensor(i_src)); } std::vector> required_pv_lst; for (auto out_tensor : op_->impl()->OutputsTensor()) { std::shared_ptr infer_tensor; if (out_tensor->GetId() == (uint32_t)-1) { out_tensor = context_->infer_graph_->CreateTensorPlaceHolder(); } required_pv_lst.push_back(MakeShared(out_tensor->GetShape().size())); } auto out_infer = CreateOutputsTensor(required_pv_lst); (*cloned_op).BindOutputs(out_infer); uint32_t i = 0; for (auto out_tensor : op_->impl()->OutputsTensor()) { context_->SetPermuteVector(out_tensor, required_pv_lst[i++]); next_tensors.push_back(out_tensor); } } }; } // namespace transform } // namespace tim #endif