lenet.py

'''LeNet in PyTorch.'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable

class LeNet(nn.Module):
    def __init__(self):
        super(LeNet, self).__init__()
        self.conv1 = nn.Conv2d(1, 32, 5)
        self.conv2 = nn.Conv2d(32, 64, 5)
        self.conv3 = nn.Conv2d(64, 64, 5)
        self.fc1   = nn.Linear(256, 120)
        self.fc2   = nn.Linear(120, 84)
        self.fc3   = nn.Linear(84, 10)

    def forward(self, x):
        out = F.relu(self.conv1(x))
        out = F.max_pool2d(out, 2)
        out = F.relu(self.conv2(out))
        out = F.max_pool2d(out, 2)
        out = F.relu(self.conv3(out))
        out = F.max_pool2d(out, 2)
        out = out.view(out.size(0), -1)
        out = F.relu(self.fc1(out))
        out = F.relu(self.fc2(out))
        out = self.fc3(out)
        return out

def test():
    net = LeNet()
    x = torch.randn(1,1,45,45)
    y = net(Variable(x))
    print(y.size())

if __name__ == '__main__':
    test()