import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from tensorboardX import SummaryWriter
# 构建神经网络
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.conv2_drop = nn.Dropout2d()
self.fc1 = nn.Linear(320, 50)
self.fc2 = nn.Linear(50, 10)
self.bn = nn.BatchNorm2d(20)
def forward(self, x):
x = F.max_pool2d(self.conv1(x), 2)
x = F.relu(x)+F.relu(-x)
x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
x = self.bn(x)
x = x.view(-1, 320)
x = F.relu(self.fc1(x))
x = F.dropout(x, training=self.training)
x = self.fc2(x)
x = F.softmax(x, dim=1)
return x
# 把模型保存为graph
# 定义输入
input = torch.rand(32, 1, 28, 28)
# 实例化神经网络
model = Net()
# 将model保存为graph
with SummaryWriter(comment='Net') as w:
w.add_graph(model, (input,))
然后在cmd中
(torch1.4) D:\pycharm_workspace\dream\chapter4>tensorboard --logdir runs
Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all
TensorBoard 2.1.0 at http://localhost:6006/ (Press CTRL+C to quit)
最后显示
