Pytorch nn.Dropout的用法示例详解_开发_开发者

Pytorch nn.Dropout的用法示例详解

开发者 https://www.devze.com 2023-04-07 09:31 出处：网络作者：马里亚纳Mariana

目录1.nn.Dropout用法一2.nn.Dropout用法二补充：torch.nn.dropout和torch.nn.dropout2d的区别1.nn.Dropout用法一

1.nn.Dropout用法一

一句话总结：Dropout的是为了防止过拟合而设置

详解部分：

1.Dropout是为了防止过拟合而设置的

2.Dropout顾名思义有丢掉的意思

3.nn.Dropout(p = 0.3) # 表示每个神经元有0.3的可能性不被激活

4.Dropout只能用在训练部分而编程客栈不能用在测试部分

5.Dropout一般用在全连接神经网络映射层之后，如代码的nn.Linear(20, 30)之后

Pytorch nn.Dropout的用法示例详解

代码部分：

class Dropout(nn.Module):
	def __init__(self):
		super(Dropout, self).__init__()
		self.linear = nn.Linear(20, 40)
		self.dropout = nn.Dropout(p = 0.3www.devze.com) # p=0.3表编程客栈示下图（a）中的神经元有p = 0.3的概率不被激活

	defandroid forward(self, inputs):
		out = self.linear(inputs)
		out = self.dropoutphp(out)
		return out

net = Dropout()
# Dropout只能用在train而不能用在test

2.nn.Dropout用法二

以代码为例

import torch
import torch.nn as nn
a = torch.randn(4, 4)
print(a)
"""
tensor([[ 1.2615, -0.6423, -0.4142,  1.2982],
        [ 0.2615,  1.3260, -1.1333, -1.6835],
        [ 0.0370, -1.0904,  0.5964, -0.1530],
        [ 1.1799, -0.3718,  1.7287, -1.5651]])
"""
dropout = nn.Dropout()
b = dropout(a)
print(b)
"""
tensor([[ 2.5230, -0.0000, -0.0000,  2.5964],
        [ 0.0000,  0.0000, -0.0000, -0.0000],
        [ 0.0000, -0.0000,  1.1928, -0.3060],
        [ 0.0000, -0.7436,  0.0000, -3.1303]])
"""

由以上代码可知Dropout还可以将部分tensor中的值置为0

补充：torch.nn.dropout和torch.nn.dropout2d的区别

import torch
import torch.nn as nn
import torch.autograd as autograd

m = nn.Dropout(p=0.5)
n = nn.Dropout2d(p=0.5)
input = autograd.Variable(torch.randn(1, 2, 6, 3)) ## 对dim=1维进行随机置为0

print(m(input))
print('****************************************************')
print(n(input))

Pytorch nn.Dropout的用法示例详解

下面的都是错误解释和错误示范，没有删除的原因是留下来进行对比，希望不要犯这类错误

# -*- coding: utf-8 -*-
import torch
import torch.nn as nn
import torch.autograd as autograd

m = nn.Dropout(p=0.5)
n = nn.Dropout2d(p=0.5)
input = autograd.Variable(torch.randn(2, 6, 3)) ## 对dim=1维进行随机置为0

print(m(input))
print('****************************************************')
print(n(input))

结果是：

Pytorch nn.Dropout的用法示例详解