demo_graph.py

import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
from torch.autograd import Variable
from tensorboardX import SummaryWriter


class Net1(nn.Module):
    def __init__(self):
        super(Net1, 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


class Net2(nn.Module):
    def __init__(self):
        super(Net2, 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)

    def forward(self, x):
        x = F.relu(F.max_pool2d(self.conv1(x), 2))
        x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
        x = x.view(-1, 320)
        x = F.relu(self.fc1(x))
        x = F.dropout(x, training=self.training)
        x = self.fc2(x)
        # x = F.log_softmax(x) no scopename(JIT bug)
        x = F.softmax(x, dim=1)
        return x

dummy_input = Variable(torch.rand(13, 1, 28, 28))

model = Net1()
with SummaryWriter(comment='Net1') as w:
    w.add_graph(model, (dummy_input, ))

model = Net2()
with SummaryWriter(comment='Net2') as w:
    w.add_graph(model, (dummy_input, ))


dummy_input = Variable(torch.rand(1, 3, 224, 224))

with SummaryWriter(comment='alexnet') as w:
    model = torchvision.models.alexnet()
    w.add_graph(model, (dummy_input, ))

with SummaryWriter(comment='vgg19') as w:
    model = torchvision.models.vgg19()
    w.add_graph(model, (dummy_input, ))

with SummaryWriter(comment='densenet121') as w:
    model = torchvision.models.densenet121()
    w.add_graph(model, (dummy_input, ))

with SummaryWriter(comment='resnet18') as w:
    model = torchvision.models.resnet18()
    w.add_graph(model, (dummy_input, ))