/* Copyright (c) 2017 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/eigen.h" #include "paddle/framework/tensor.h" #include "paddle/platform/device_context.h" namespace paddle { namespace operators { namespace math { /** * return the 1-based index of the highest bit set * * for x > 0: * \f[ * findLastSet(x) = 1 + \floor*{\log_{2}x} * \f] */ inline constexpr size_t FindLastSet(size_t x) { return std::is_same::value ? (x ? 8 * sizeof(x) - __builtin_clz(x) : 0) : (std::is_same::value // NOLINT ? (x ? 8 * sizeof(x) - __builtin_clzl(x) : 0) : (x ? 8 * sizeof(x) - __builtin_clzll(x) : 0)); } struct SimpleCode { SimpleCode(size_t code, size_t num_classes) : c_(code + num_classes) {} inline size_t calc_index(int bit) const { return (c_ >> (bit + 1)) - 1; } inline bool calc_bit(int bit) const { return c_ & (1 << bit); } inline int get_length() const { return FindLastSet(c_) - 1; } private: size_t c_; }; struct SimpleCodeTable { explicit SimpleCodeTable(size_t num_classes) : num_classes_(num_classes) {} SimpleCode operator()(size_t code) const { return SimpleCode(code, num_classes_); } size_t size() const { return num_classes_; } int get_max_code_length() const { return FindLastSet(num_classes_ - 1); } private: size_t num_classes_; int max_code_length_; }; template class MatrixBitCodeFunctor { public: explicit MatrixBitCodeFunctor(size_t num_classes, const int64_t* ids) : num_classes_(num_classes), ids_(ids) {} /* For j < code_length tmat(i, j) += vec(0, index(i, j)) */ void Add(framework::Tensor& tmat, const framework::Tensor& vec); /* For j < code_length vec(0, index(i, j)) += tmat(i, j) */ void AddGrad(framework::Tensor& tmat, framework::Tensor& vec); /* For j < code_length sum(i, 0) = \sum_j bit(i, j) * tmat(i, j) */ void Sum(framework::Tensor& tmat, framework::Tensor& sum, T scale_sum); /* For j < code_length tmat(i, j) -= bit(i, j) */ void Sub(framework::Tensor& tmat); /* For j < code_length input.row(i) += tmat(i, j) * weight.row(index(i, j)) */ void Mul(framework::Tensor& tmat, const framework::Tensor& weight, const framework::Tensor& input); /* For index(i, j) >= 0: weight.row(index(i, j)) += tmat(i, j) * input.row(i) */ void MulGradWeight(const framework::Tensor& tmat, framework::Tensor& weight, const framework::Tensor& input); /* For j < code_length input.row(i) += tmat(i, j) * weight.row(index(i, j)) */ void MulGradError(const framework::Tensor& tmat, const framework::Tensor& weight, framework::Tensor& input); size_t num_classes_; const int64_t* ids_; }; } // namespace math } // namespace operators } // namespace paddle