/* Copyright (c) 2016 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. */ #ifdef PADDLE_WITH_XPU #include "paddle/fluid/operators/beam_search_decode_op_xpu.h" #include "paddle/fluid/framework/op_registry.h" namespace paddle { namespace operators { template class BeamSearchDecodeXPUKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { const LoDTensorArray* ids = context.Input("Ids"); const LoDTensorArray* scores = context.Input("Scores"); const size_t step_num = ids->size(); PADDLE_ENFORCE_GT( step_num, 0UL, platform::errors::InvalidArgument( "beam search steps, which is the" "size of Input(Ids) LoDTensorArray. beam search steps should " "be larger than 0, but received %d. ", step_num)); const size_t source_num = ids->at(0).lod().at(0).size() - 1; PADDLE_ENFORCE_GT( source_num, 0UL, platform::errors::InvalidArgument( "source_num is the sequence number of the" "first decoding step, indicating by Input(Ids)[0].lod[0].size. " "The number of source_num should be larger than" "0, but received %d. ", source_num)); for (size_t i = 0; i < step_num; ++i) { PADDLE_ENFORCE_EQ( ids->at(i).lod().size(), 2UL, platform::errors::InvalidArgument( "For the i step in beam search steps," "the size of Input(Ids)[i].lod() should larger than 2," "but received %d. ", ids->at(i).lod().size())); } size_t beam_size = context.Attr("beam_size"); int end_id = context.Attr("end_id"); // prepare output LoDTensor* sentenceIds = nullptr; LoDTensor* sentenceScores = nullptr; LoDTensor* sentenceIds_temp = context.Output("SentenceIds"); LoDTensor* sentenceScores_temp = context.Output("SentenceScores"); if (platform::is_xpu_place(ids->at(0).place())) { sentenceIds = new LoDTensor(); sentenceIds->set_lod(sentenceIds_temp->lod()); } if (platform::is_xpu_place(ids->at(0).place())) { sentenceScores = new LoDTensor(); sentenceScores->set_lod(sentenceScores_temp->lod()); } BeamSearchDecodeXPUFunctor bs_xpu( *ids, *scores, sentenceIds, sentenceScores, beam_size, end_id); bs_xpu.apply_xpu(); if (platform::is_xpu_place(ids->at(0).place())) { int r = 0; r = CopyTensorByXPU( *sentenceIds, sentenceIds_temp, 1, ids->at(0).place()); PADDLE_ENFORCE_EQ( r, xpu::Error_t::SUCCESS, platform::errors::External( "Execute function CopyTensorByXPU failed by [%d]", r)); r = CopyTensorByType( *sentenceScores, sentenceScores_temp, 1, ids->at(0).place()); PADDLE_ENFORCE_EQ( r, xpu::Error_t::SUCCESS, platform::errors::External( "Execute function CopyTensorByXPU failed by [%d]", r)); } } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_XPU_KERNEL( beam_search_decode, ops::BeamSearchDecodeXPUKernel, ops::BeamSearchDecodeXPUKernel, ops::BeamSearchDecodeXPUKernel, ops::BeamSearchDecodeXPUKernel, ops::BeamSearchDecodeXPUKernel); #endif