import torchvision
from torch.nn import MaxPool2d
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import torch.nn as nn
dataset_transform = torchvision.transforms.Compose([
torchvision.transforms.ToTensor()
])
test_data = torchvision.datasets.CIFAR10(root="./test10_dataset", train=False, transform=dataset_transform)
test_loader = DataLoader(dataset=test_data, batch_size=64)
class MyNet(nn.Module):
def __init__(self):
super(MyNet, self).__init__()
self.maxpool1 = MaxPool2d(kernel_size=2)
def forward(self, input):
output = self.maxpool1(input)
return output
MyNet = MyNet()
writer = SummaryWriter("CIFAR10")
step = 0
for data in test_loader:
imgs, target = data
output = MyNet(imgs)
writer.add_images("input", imgs, step)
writer.add_images("output", output, step)
step = step + 1
writer.close()
池化层
MaxPool2d(kernel_size=2)
卷积核大小为2
在terminal中使用:
tensorboard --logdir=CIFAR10
tensorboard :
输入:
输出: