池化层pytorch最大池化练习

神经网络构建

class Tudui(nn.Module):def __init__(self):super(Tudui, self).__init__()self.maxpool1 = MaxPool2d(kernel_size=3, ceil_mode=False)def forward(self, input):output = self.maxpool1(input)return output

Tensorboard 处理

writer = SummaryWriter("./logs_maxpool")
step = 0for data in dataloader:imgs, targets = datawriter.add_images("input", imgs, step)output = tudui(imgs)writer.add_images("output", output, step)step = step + 1

Padding 层

将输入图像进行填充

非线性激活：

Relu:

inplace值：0，1影响

非线性激活代码试写Sigmoid：

import torch
import torchvision
from torch import nn
from torch.nn import  Sigmoid
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriterdataset = torchvision.datasets.CIFAR10("./data", train=False, download=True,transform=torchvision.transforms.ToTensor())dataloader = DataLoader(dataset, batch_size=64)class Tudui(nn.Module):def __init__(self):super(Tudui, self).__init__()self.Sigmoid1 = Sigmoid()def forward(self, input):output = self.Sigmoid1(input)return outputtudui = Tudui()writer = SummaryWriter("./Sigmoidtest")
step = 0for data in dataloader:imgs, targets = datawriter.add_images("input", imgs, step)output = tudui(imgs)writer.add_images("output", output, step)step = step + 1writer.close()