均匀分布nn.init.uniform(tensor,a=0,b=1)tensor -n维的torch.Tensora 均匀分布的下界,默认值为0b 均匀分布的上界,默认值为1 正态分布torcn.nn.init.normal(tensor,mean=0,std=1)tensor n维的torch.Tensormean 正太分布的均值std 正太分布的标准差 import torch import torch.nn as nn import warnings warnings.filterwar…

radom radom模块提供了随机生成对象的方法 Help on module random: NAME random - Random variable generators. FILE /usr/local/lib/python2.7/random.py MODULE DOCS http://docs.python.org/library/random DESCRIPTION integers -------- uniform within range sequences --------…

"""Random variable generators. integers -------- uniform within range sequences --------- pick random element pick random sample pick weighted random sample generate random permutation distributions on the real line: -----------------------…

radom模块提供了随机生成对象的方法 Help on module random: NAME random - Random variable generators. FILE /usr/local/lib/python2.7/random.py MODULE DOCS http://docs.python.org/library/random DESCRIPTION integers -------- uniform within range sequences --------- pick…

Python中本身带有很多实用的工具,如pydoc.pydoc模块主要用来从Python模块中提取信息并生成文档. 使用方法 在Windows和Linux下的使用方法有些区别. Windows python -m pydoc <modulename> 如: C:\>python -m pydoc module_test NB:module_test是自定义的模块,不要添加文件后缀. Linux pydoc <modulename> 如: $ pydoc module_test…

目录 1. random模块 1.1 设置随机种子 1.2 random模块中的方法 1.3 使用:生成整形随机数 1.3 使用:生成序列随机数 1.4 使用:生成随机实值分布 2. numpy.random 2.1 Utility functions:实用方法 2.2 Compatibility functions:兼容方法 Reference   今天在一个公众号上看到了一篇有关Python基础的文章,其中提到了Numpy模块中有关生成随机数的使用:这才联想到,自己对这一块也不熟悉,每次想要…

本文内容:1. Xavier 初始化2. nn.init 中各种初始化函数3. He 初始化 torch.init https://pytorch.org/docs/stable/nn.html#torch-nn-init 1. 均匀分布torch.nn.init.uniform_(tensor, a=0, b=1)服从~U(a,b) U(a, b)U(a,b) 2. 正太分布torch.nn.init.normal_(tensor, mean=0, std=1)服从~N(mean,std) N…

Basics of Probability Probability density function (pdf). Let X be a continuous random variable. Then a probability distribution or probability density function (pdf) of X is a function f(x) such that any two numbers a and b with That is, the probabi…

The Central Limit Theorem (CLT), and the concept of the sampling distribution, are critical for understanding why statistical inference works. There are at least a handful of problems that require you to invoke the Central Limit Theorem on every ASQ…

http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.normal.html #np.random.normal,产生制定分布的数集#http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.normal.html# mean and standard deviation# 均值的物理意义mu,Mean (“centre”) of the distr…