#### GCN Policy
state = dc(init_state)
if cuda_flag:
state.g.ndata['x'] = state.g.ndata['x'].cuda()
sum_r = 0
T1 = time.time()
[idx1, idx2] = mvc.get_ilegal_actions(state)
while done == False:
G = state.g
[pi, val] = NN(G)
pi = pi.squeeze()
pi[idx1] = -float('Inf')
pi = F.softmax(pi, dim=0)
dist = torch.distributions.categorical.Categorical(pi)
action = dist.sample()
new_state, reward, done = mvc.step(state, action)
[idx1, idx2] = mvc.get_ilegal_actions(new_state)
state = new_state
sum_r += reward
T2 = time.time()
node_tag = state.g.ndata['x'][:, 0].cpu().squeeze().numpy().tolist()
nx.draw(state.g.to_networkx(), pos, node_color=node_tag, with_labels=True)
plt.show()
### Heuristic Policy
state = dc(init_state)
done = False
sum_r2 = 0
T1 = time.time()
[idx1, idx2] = mvc.get_ilegal_actions(state)
