add LogPhysEncoder

ThermalSolver/model/diffusion_net.py

@@ -4,6 +4,27 @@ from torch_geometric.nn import MessagePassing
 from torch.nn.utils import spectral_norm
 
 
+class LogPhysEncoder(nn.Module):
+    """
+    Processes 1/dx in log-space to handle multiple scales of geometry
+    (from micro-meshes to macro-meshes) without numerical instability.
+    """
+
+    def __init__(self, hidden_dim):
+        super().__init__()
+        self.mlp = nn.Sequential(
+            spectral_norm(nn.Linear(1, hidden_dim)),
+            nn.GELU(),
+            spectral_norm(nn.Linear(hidden_dim, 1)),
+            nn.Softplus(),  # Physical conductance must be positive
+        )
+
+    def forward(self, inv_dx):
+        # We use log(1/dx) to linearize the scale of different geometries
+        log_inv_dx = torch.log(inv_dx + 1e-9)
+        return self.mlp(log_inv_dx)
+
+
 class DiffusionLayer(MessagePassing):
     """
     Modella: T_new = T_old + dt * Divergenza(Flusso)
@@ -22,12 +43,7 @@ class DiffusionLayer(MessagePassing):
             spectral_norm(nn.Linear(channels, channels, bias=False)),
         )
 
-        self.phys_encoder = nn.Sequential(
-            spectral_norm(nn.Linear(1, 8, bias=True)),
-            nn.Tanh(),
-            spectral_norm(nn.Linear(8, 1, bias=True)),
-            nn.Softplus(),
-        )
+        self.phys_encoder = LogPhysEncoder(hidden_dim=channels)
 
         self.alpha_param = nn.Parameter(torch.tensor(1e-2))