| import torch.nn as nn | |
| class SmallNN(nn.Module): | |
| def __init__(self): | |
| super().__init__() | |
| self.encoder = nn.Sequential(nn.Linear(8, 64), nn.ReLU()) | |
| self.classifier = nn.Linear(64, 4) | |
| def forward(self, x): | |
| return self.classifier(self.encoder(x)) | |
| import torch.nn as nn | |
| class SmallNN(nn.Module): | |
| def __init__(self): | |
| super().__init__() | |
| self.encoder = nn.Sequential(nn.Linear(8, 64), nn.ReLU()) | |
| self.classifier = nn.Linear(64, 4) | |
| def forward(self, x): | |
| return self.classifier(self.encoder(x)) | |