神经网络—卷积层

1.讲解 Conv2d

• out_channels 参数为2时，会生成两个卷积核，分别与输入进行卷积。得到的两个输出为输出

新生成的卷积核和原来的卷积核不一定相同

• in_channels (int) – Number of channels in the input image

• out_channels (int) – Number of channels produced by the convolution

• kernel_size (int or tuple) – Size of the convolving kernel

• stride (int or tuple, optional) – Stride of the convolution. Default:1

• padding (int, tuple or str, optional) – Padding added to all four
  sides of the input. Default: 0

2.代码实现

import torch
import torchvision
from torch import nn
from torch.nn import Conv2d
from torch.utils.data import DataLoader

dataset=torchvision.datasets.CIFAR10("../data",train=