diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..5c98b428844d9f7d529e2b6fb918d15bf072f3df
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,2 @@
+# Default ignored files
+/workspace.xml
\ No newline at end of file
diff --git a/torch_training/multi_agent_inference.py b/torch_training/multi_agent_inference.py
index 718ce3a63aec6d13d7b2d48cd222d09b4a3ff604..b310e95f19e6284cfd6fed6f195d9807551875b8 100644
--- a/torch_training/multi_agent_inference.py
+++ b/torch_training/multi_agent_inference.py
@@ -3,13 +3,13 @@ from collections import deque
 
 import numpy as np
 import torch
-from flatland.envs.generators import rail_from_file, complex_rail_generator
-from observation_builders.observations import TreeObsForRailEnv
-from predictors.predictions import ShortestPathPredictorForRailEnv
+from flatland.envs.generators import rail_from_file
 from flatland.envs.rail_env import RailEnv
 from flatland.utils.rendertools import RenderTool
 from importlib_resources import path
-import time
+from observation_builders.observations import TreeObsForRailEnv
+from predictors.predictions import ShortestPathPredictorForRailEnv
+
 import torch_training.Nets
 from torch_training.dueling_double_dqn import Agent
 from utils.observation_utils import normalize_observation
@@ -73,7 +73,7 @@ action_prob = [0] * action_size
 agent_obs = [None] * env.get_num_agents()
 agent_next_obs = [None] * env.get_num_agents()
 agent = Agent(state_size, action_size, "FC", 0)
-with path(torch_training.Nets, "avoid_checkpoint59900.pth") as file_in:
+with path(torch_training.Nets, "avoid_checkpoint60000.pth") as file_in:
     agent.qnetwork_local.load_state_dict(torch.load(file_in))
 
 record_images = False
diff --git a/torch_training/training_navigation.py b/torch_training/training_navigation.py
index 2b836087611f5a5a0b01e47d6d91b78c16da9d42..5cc7305563076e54e25a3fb2d890e276bcbf9a38 100644
--- a/torch_training/training_navigation.py
+++ b/torch_training/training_navigation.py
@@ -118,7 +118,7 @@ def main(argv):
 
             # Only render when not triaing
             if not Training:
-                env_renderer.renderEnv(show=True, show_observations=True)
+                env_renderer.render_env(show=True, show_observations=True)
 
             # Chose the actions
             for a in range(env.get_num_agents()):
@@ -210,7 +210,7 @@ def main(argv):
 
     # Run episode
     for step in range(max_steps):
-        env_renderer.renderEnv(show=True, show_observations=False)
+        env_renderer.render_env(show=True, show_observations=False)
 
         # Chose the actions
         for a in range(env.get_num_agents()):