| 9 | |
| 10 | #Load model |
| 11 | class MLP(nn.Module): |
| 12 | def __init__(self, in_dim=21, h1=64, h2=32): |
| 13 | super().__init__() |
| 14 | self.net = nn.Sequential( |
| 15 | nn.Linear(in_dim, h1), |
| 16 | nn.ReLU(), |
| 17 | nn.Linear(h1, h2), |
| 18 | nn.ReLU(), |
| 19 | nn.Linear(h2, 1) |
| 20 | ) |
| 21 | def forward(self, x): |
| 22 | return self.net(x) |
| 23 | |
| 24 | |
| 25 | device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |