// Copyright (c) 2019 PaddlePaddle Authors. 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. #pragma once #include #include "lite/backends/x86/math/sequence_padding.h" #include "lite/core/kernel.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace x86 { namespace math = paddle::lite::x86::math; template class SequenceUnpadCompute : public KernelLite { public: using param_t = operators::SequenceUnpadParam; void Run() override { auto& param = this->template Param(); auto& ctx = this->ctx_->template As(); auto x_dims = param.X->dims(); auto len_dims = param.Length->dims(); auto* seq_len_ptr = param.Length->template data(); int64_t batch_size = len_dims[0]; std::vector out_lod0(batch_size + 1, 0); for (int64_t i = 0; i < batch_size; ++i) { out_lod0[i + 1] = out_lod0[i] + seq_len_ptr[i]; } paddle::lite::LoD out_lod; out_lod.push_back(out_lod0); int64_t out_dim0 = out_lod0.back(); std::vector out_dims{out_dim0}; if (x_dims.size() == 2) { out_dims.push_back(1); } else { for (size_t i = 2; i < x_dims.size(); ++i) { out_dims.push_back(x_dims[i]); } } param.Out->Resize(out_dims); param.Out->set_lod(out_lod); param.Out->template mutable_data(); int64_t padded_length = param.X->dims()[1]; math::UnpaddingLoDTensorFunctor()( ctx, *param.X, param.Out, padded_length, 0, false, math::kBatchLengthWidth); } virtual ~SequenceUnpadCompute() = default; }; } // namespace x86 } // namespace kernels } // namespace lite } // namespace paddle