Merge pull request ispras#26 from ispras/QAttack_fix

Fix QAttack

.github/workflows/linter.yaml

@@ -2,7 +2,6 @@ name: Pylint
 
 on:
   push:
-  pull_request:
 
 jobs:
   lint:

src/attacks/QAttack/qattack.py

@@ -59,7 +59,8 @@ def fitness(self, model, gen_dataset):
 
             # Get labels from black-box
             labels = model.gnn.get_answer(dataset.x, dataset.edge_index)
-            labeled_nodes = {n: labels.tolist()[n-1] for n in adj_list.keys()}  # FIXME check order for labels and node id consistency
+            labeled_nodes = dict(enumerate(labels.tolist()))
+            # labeled_nodes = {n: labels.tolist()[n-1] for n in adj_list.keys()}  # FIXME check order for labels and node id consistency
 
             # Calculate modularity
             Q = self.modularity(adj_list, labeled_nodes)
@@ -76,7 +77,7 @@ def fitness_individual(self, model, gen_dataset, gene):
 
         # Get labels from black-box
         labels = model.gnn.get_answer(dataset.x, dataset.edge_index)
-        labeled_nodes = {n: labels.tolist()[n-1] for n in adj_list.keys()}  # FIXME check order for labels and node id consistency
+        labeled_nodes = dict(enumerate(labels.tolist()))
 
         # Calculate modularity
         Q = self.modularity(adj_list, labeled_nodes)
@@ -191,6 +192,7 @@ def mutation(self, gen_dataset):
                     dataset.edge_index = from_adj_list(adj_list)
                     non_isolated_nodes = set(gen_dataset.dataset.edge_index[0].tolist()).union(
                         set(gen_dataset.dataset.edge_index[1].tolist()))
+                    non_drain_nodes = set(gen_dataset.dataset.edge_index[0].tolist())
                     if mut_type == 0:
                         # add mutation
                         connected_nodes = set(self.adj_list[n])
@@ -202,8 +204,8 @@ def mutation(self, gen_dataset):
                         self.population[i][n]['del'] = np.random.choice(list(adj_list[n]), 1)
                     else:
                         selected_nodes = set(self.population[i].keys())
-                        non_selected_nodes = non_isolated_nodes.difference(selected_nodes)
-                        new_node = np.random.choice(list(non_selected_nodes), size=1, replace=False)[0]
+                        non_drain_nodes = non_drain_nodes.difference(selected_nodes)
+                        new_node = np.random.choice(list(non_drain_nodes), size=1, replace=False)[0]
                         self.population[i].pop(n)
                         addition_nodes = non_isolated_nodes.difference(set(self.adj_list[new_node]))
                         self.population[i][new_node] = {}
@@ -236,4 +238,4 @@ def attack(self, model_manager, gen_dataset, mask_tensor):
                 set(adj_list[n]).union(set([int(rewiring[n]['add'])])).difference(set([int(rewiring[n]['del'])])))
 
         gen_dataset.dataset.data.edge_index = from_adj_list(adj_list)
-        return gen_dataset
+        return gen_dataset