| from __future__ import annotations | |
| import torch | |
| import torch.nn as nn | |
| from .grad_reverse import GradientReversalLayer | |
| class SensorDiscriminator(nn.Module): | |
| """Adversarial sensor classifier attached to shared features.""" | |
| def __init__(self, in_dim: int, num_sensors: int, lambda_grl: float = 0.3): | |
| super().__init__() | |
| self.grl = GradientReversalLayer(lambda_=lambda_grl) | |
| self.mlp = nn.Sequential( | |
| nn.Linear(in_dim, 64), | |
| nn.ReLU(inplace=True), | |
| nn.Linear(64, num_sensors), | |
| ) | |
| def set_grl_lambda(self, value: float) -> None: | |
| """Update GRL lambda dynamically (DANN warm-up).""" | |
| self.grl.set_lambda(value) | |
| def forward(self, features: torch.Tensor) -> torch.Tensor: | |
| return self.mlp(self.grl(features)) | |