Delete gnn_predictor.py

gnn_predictor.py

@@ -1,40 +0,0 @@
-"""
-PyTorch Geometric model for failure propagation prediction.
-Falls back to dummy linear model if PyG not available.
-"""
-import torch
-import torch.nn.functional as F
-
-try:
-    from torch_geometric.nn import GCNConv
-    TORCH_GEOMETRIC_AVAILABLE = True
-except ImportError:
-    TORCH_GEOMETRIC_AVAILABLE = False
-
-class FailureGNN(torch.nn.Module):
-    def __init__(self, num_features=5, hidden=16, num_classes=2):
-        super().__init__()
-        self.num_features = num_features
-        self.hidden = hidden
-        self.num_classes = num_classes
-        
-        if TORCH_GEOMETRIC_AVAILABLE:
-            self.conv1 = GCNConv(num_features, hidden)
-            self.conv2 = GCNConv(hidden, num_classes)
-        else:
-            # Fallback linear model (no graph structure)
-            self.fc = torch.nn.Linear(num_features, num_classes)
-    
-    def forward(self, x, edge_index=None):
-        """
-        x: node features [num_nodes, num_features]
-        edge_index: graph connectivity [2, num_edges] (optional)
-        """
-        if TORCH_GEOMETRIC_AVAILABLE and edge_index is not None:
-            x = self.conv1(x, edge_index)
-            x = F.relu(x)
-            x = F.dropout(x, training=self.training)
-            x = self.conv2(x, edge_index)
-        else:
-            x = self.fc(x)  # ignore graph structure
-        return F.log_softmax(x, dim=1)