+ imgs = torch.cat((imgs, c_predicted_paths.unsqueeze(1)), 1)
+
+ if score_paths is not None:
+ score_paths = score_paths.cpu()
+ c_score_paths = score_paths.unsqueeze(1).expand(-1, 3, -1, -1)
+ c_score_paths = (
+ c_score_paths * colors[4].reshape(1, 3, 1, 1)
+ + (1 - c_score_paths) * colors[0].reshape(1, 3, 1, 1)
+ ).long()
+ c_score_paths = c_score_paths * (mazes.unsqueeze(1) == v_empty) + c_mazes * (
+ mazes.unsqueeze(1) != v_empty
+ )
+ imgs = torch.cat((imgs, c_score_paths.unsqueeze(1)), 1)