To generate enough entropy, generate_canonical() will call g() exactly kk times, where k=max(1,⌈blog2R⌉)k=max(1,⌈blog2R⌉) and b = std::min(Bits, std::size_t {std::numeric_limits<RealType>::digits}), R = g.max() - g.min() + 1. Parameters...
RealType generate_canonical( Generator& g ); (C++11 起) 生成范围 [0, 1) 中的随机浮点值。 为生成足够的熵, generate_canonical() 将准确调用 g() k 次,其中 k = \text{Max}(1, ⌈ b / log2 R ⌉) 且 b = std::min<std::size_t>(bits, std::numeric_limits<RealType>::digits...
为了产生足够的熵,generate_canonical()会打电话g()精确k次,其中k=max%281,b/log 2R%29和。 b =std::min<std::size_t>(bits,std::numeric_limits<RealType>::digits) R = g.max() - g.min() + 1... 参数 g - generator to use to acquire entropy 返回值 浮点值在范围内。[0;1%29。
generate_canonical<> (C++11 起)generate_header (C++11 起)(C++17 中弃用)generate_n<>()generic_category() (C++11 起)geometric_distribution<> (C++11 起)get<>() (std::array) (C++11 起)get<>() (std::pair) (C++11 起)get<>() (std::ranges::subrange) (C++20 起)get<>() (std:...
std::generate_canonical std::geometric_distribution std::geometric_distribution::geometric_distribution std::geometric_distribution::max std::geometric_distribution::min std::geometric_distribution::p std::geometric_distribution::param std::geometric_distribution::reset std::gslice std::gslice_array std:...
std::generate_canonical std::geometric_distribution std::geometric_distribution::geometric_distribution std::geometric_distribution::max std::geometric_distribution::min std::geometric_distribution::p std::geometric_distribution::param std::geometric_distribution::reset std::gslice std::gslice_array std:...
generate_canonical (C++11) seed_seq (C++11) Random number algorithms ranges::generate_random (C++26) C random library rand srand RAND_MAX std::mersenne_twister_engine Member functions mersenne_twister_engine::mersenne_twister_engine (C++11) mersenne_twister_engine::seed (C++11) Generation mersenne...
SYMBOL(generate_canonical, std::, <random>) SYMBOL(generate_n, std::, <algorithm>) SYMBOL(generic_category, std::, <system_error>) SYMBOL(geometric_distribution, std::, <random>) SYMBOL(get_if, std::, <variant>) SYMBOL(get_money, std::, <iomanip>) ...
@mathstufsuggested to write a tool to generate and pass all the needed module files automatically. While I think both the suggestion may be implementable due to the scale of the specific issue, I think the don't necessarily need to be the first step. I feel simpler the method is, the ...
摘要原文 We present a new two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD). The first stage is a bottom-up proposal generation network that uses raw point cloud as input to generate accurate proposals by seeding each point with a new spherical anchor. ...