import torchvision.datasets
from tensorflow.python.ops import nn
from torch.nn import MaxPool2d
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
dataset=torchvision.datasets.CIFAR10("../data",train=False,download=True,transform=torchvision.transforms.ToTensor())
dataloader=DataLoader(dataset,batch_size=64)
class Tudui(nn.Module):
def __int__(self):
super(Tudui,self).__init__()
self.maxpool1=MaxPool2d(kernel_size=3,ceil_mode=False)
def forward(self,input):
output=self.maxpool1(input)
return output
tudui=Tudui()
writer=SummaryWriter("../logs_maxpool")
step=0
for data in dataloader:
imgs,targets=data
writer.add_images("input",imgs,step)
output=tudui(imgs)
writer.add_images("output",output,step)
step=step+1
writer.close()
from tensorflow.python.ops import nn
from torch.nn import MaxPool2d
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
dataset=torchvision.datasets.CIFAR10("../data",train=False,download=True,transform=torchvision.transforms.ToTensor())
dataloader=DataLoader(dataset,batch_size=64)
class Tudui(nn.Module):
def __int__(self):
super(Tudui,self).__init__()
self.maxpool1=MaxPool2d(kernel_size=3,ceil_mode=False)
def forward(self,input):
output=self.maxpool1(input)
return output
tudui=Tudui()
writer=SummaryWriter("../logs_maxpool")
step=0
for data in dataloader:
imgs,targets=data
writer.add_images("input",imgs,step)
output=tudui(imgs)
writer.add_images("output",output,step)
step=step+1
writer.close()
