PyTorch搭建小实践

import torch
from torch import nn
from torch.nn import Conv2d, MaxPool2d, Flatten, Linear, Sequential
from torch.utils.tensorboard import SummaryWriterclass Model(nn.Module):def __init__(self):super(Model, self).__init__()# self.conv1 = Conv2d(3, 32, 5, padding = 2)# self.maxpool1 = MaxPool2d(2)# self.conv2 = Conv2d(32, 32, 5, padding = 2)# self.maxpool2 = MaxPool2d(2)# self.conv3 = Conv2d(32, 64, 5, padding = 2)# self.maxpool3 = MaxPool2d(2)# self.flatten = Flatten()# self.linear1 = Linear(1024, 64)# self.linear2 = Linear(64, 10)self.model1 = Sequential(Conv2d(3, 32, 5, padding = 2),MaxPool2d(2),Conv2d(32, 32, 5, padding = 2),MaxPool2d(2),Conv2d(32, 64, 5, padding = 2),MaxPool2d(2),Flatten(),Linear(1024, 64),Linear(64, 10))def forward(self, x):# x = self.conv1(x)# x = self.maxpool1(x)# x = self.conv2(x)# x = self.maxpool2(x)# x = self.conv3(x)# x = self.maxpool3(x)# x = self.flatten(x)# x = self.linear1(x)# x = self.linear2(x)x = self.model1(x)return xmodel = Model()
print(model)
input = torch.ones((64, 3, 32, 32))
output = model(input)
print(output.shape)writer = SummaryWriter("logs_seq")
writer.add_graph(model, input)
writer.close()