Source code for distil.utils.models.cifar10net

import torch.nn as nn
import torch.nn.functional as F


[docs]class CifarNet(nn.Module): def __init__(self): super(CifarNet, self).__init__() self.conv1 = nn.Conv2d(3, 64, 3) self.conv2 = nn.Conv2d(64, 128, 3) self.conv3 = nn.Conv2d(128, 256, 3) self.pool = nn.MaxPool2d(2, 2) self.fc1 = nn.Linear(64 * 4 * 4, 128) self.fc2 = nn.Linear(128, 256) self.fc3 = nn.Linear(256, 10)
[docs] def forward(self, x, last=False): x = self.pool(F.relu(self.conv1(x))) x = self.pool(F.relu(self.conv2(x))) x = self.pool(F.relu(self.conv3(x))) x = x.view(-1, 64 * 4 * 4) x = F.relu(self.fc1(x)) x = F.relu(self.fc2(x)) output = self.fc3(x) if last: return output, x else: return output
[docs] def get_embedding_dim(self): return 256