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| import torch.nn as nn | |
| from torchvision import models | |
| # Custom ResNet model for monkey classification | |
| class MonkeyResNet(nn.Module): | |
| def __init__(self, num_classes): | |
| super(MonkeyResNet, self).__init__() | |
| # Load pretrained ResNet18 model from torchvision | |
| self.model = models.resnet18(pretrained=False) | |
| # Replace the final fully connected layer to match number of classes | |
| in_features = self.model.fc.in_features | |
| self.model.fc = nn.Linear(in_features, num_classes) | |
| def forward(self, x): | |
| return self.model(x) # run input through the model | |