/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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 "paddle/framework/op_registry.h" #include "paddle/memory/memcpy.h" namespace paddle { namespace operators { using LoDTensor = framework::LoDTensor; template using vector = framework::Vector; vector repeat_lod(vector data, vector starts, vector times, bool is_first) { vector result; result.push_back(data[0]); size_t p = 0, start = 0, end = 0; if (is_first == true) { for (size_t i = 0; i < times.size(); ++i) { result.push_back(data.back() + times[i] * (data[i + 1] - data[i])); } } else { for (size_t i = 0; i < times.size(); ++i) { while (starts[i] != data[p] && p < data.size()) { ++p; } start = p; while (starts[i + 1] != data[p] && p < data.size()) { ++p; } end = p + 1; for (size_t j = 0; j < times[i]; ++j) { for (size_t index = start; index < end - 1; ++index) { result.push_back(result.back() + data[index + 1] - data[index]); } } } } return result; } template void repeat_data(const T* src, T* dst, size_t size, vector starts, vector times, Place place) { const T* src_p = src; T* dst_p = dst; size_t count = 0; for (size_t i = 0; i < times.size(); ++i) { count = size * (starts[i + 1] - starts[i]); for (size_t j = 0; j < times[i]; ++j) { memory::Copy(place, dst_p, place, src_p, sizeof(T) * count); dst_p += count; } src_p += count; } } template class SeqExpandKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { auto* x = context.Input("X"); auto* out = context.Output("Out"); const T* x_data = x->data(); auto x_dims = x->dims(); auto x_lod = x->lod(); if (x_lod.size() == 0) { vector level; for (int i = 0; i < x->dims()[0] + 1; ++i) { level.push_back(i); } x_lod.push_back(level); } else { x_lod.insert(x_lod.begin(), x_lod[0]); } size_t repeat = static_cast(context.Attr("repeat")); vector repeats; if (repeat != 0) { for (int i = 0; i < x_lod[0].size() - 1; ++i) { repeats.push_back(repeat); } std::vector dims = framework::vectorize(x->dims()); dims[0] = dims[0] * repeat; auto out_dims = framework::make_ddim(dims); out->Resize(out_dims); } else { auto* y = context.Input("Y"); auto y_lod = y->lod(); for (int i = 0; i < y_lod[0].size() - 1; ++i) { repeats.push_back((y_lod[0][i + 1] - y_lod[0][i]) / (x_lod[0][i + 1] - x_lod[0][i])); } out->Resize(x_dims); } framework::LoD out_lod; auto level0 = repeat_lod(x_lod[0], x_lod[0], repeats, true); out_lod.push_back(level0); for (int i = 1; i < x_lod.size(); ++i) { out_lod.push_back(repeat_lod(x_lod[i], x_lod[0], repeats, false)); } size_t element_len = framework::product(x_dims) / x_dims[0]; T* out_data = out->mutable_data(context.GetPlace()); Place place = boost::get(context.GetPlace()); repeat_data(x_data, out_data, element_len, x_lod[0], repeats, place); out->set_lod(out_lod); } }; template class SeqExpandGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { // auto* d_out = context.Input(framework::GradVarName("Out")); // auto* d_x = context.Output(framework::GradVarName("X")); // d_x->mutable_data(context.GetPlace()); } }; } // namespace operators } // namespace paddle