5. 线性层及其他层

5.1 神经网络结构

5.2 线性拉平

import torch
import torchvision
from torch import nn 
from torch.nn import ReLU
from torch.nn import Sigmoid
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriterdataset = torchvision.datasets.CIFAR10("./dataset",train=False,transform=torchvision.transforms.ToTensor(),download=True)       
dataloader = DataLoader(dataset, batch_size=64)for data in dataloader:imgs, targets = dataprint(imgs.shape)output = torch.reshape(imgs,(1,1,1,-1))print(output.shape)

结果：

5.3 线性层

import torch
import torchvision
from torch import nn 
from torch.nn import Linear
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriterdataset = torchvision.datasets.CIFAR10("./dataset",train=False,transform=torchvision.transforms.ToTensor(),download=True)       
dataloader = DataLoader(dataset, batch_size=64,drop_last=True)class Tudui(nn.Module):def __init__(self):super(Tudui, self).__init__()self.linear1 = Linear(196608,10)def forward(self, input):output = self.linear1(input)return outputtudui = Tudui()
writer = SummaryWriter("logs")
step = 0for data in dataloader:imgs, targets = dataprint(imgs.shape)writer.add_images("input", imgs, step)output = torch.reshape(imgs,(1,1,1,-1)) # 方法一：拉平#output = torch.flatten(imgs)  # 方法二：拉平。展开为一维print(output.shape)output = tudui(output)print(output.shape)writer.add_images("output", output, step)step = step + 1

操作：

① 在 Anaconda 终端里面，激活py3.6.3环境，再输入 tensorboard --logdir=C:\Users\wangy\Desktop\03CV\logs 命令，将网址赋值浏览器的网址栏，回车，即可查看tensorboard显示日志情况。