From 2e05cbe1dd86794a3f4bb4e669371f6388749904 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Wed, 3 Jul 2019 14:57:41 -0400
Subject: [PATCH] using new utility functions
---
torch_training/training_navigation.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/torch_training/training_navigation.py b/torch_training/training_navigation.py
index a6ee613..0e5ad18 100644
--- a/torch_training/training_navigation.py
+++ b/torch_training/training_navigation.py
@@ -43,7 +43,7 @@ env = RailEnv(width=15,
"""
env = RailEnv(width=10,
height=20, obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()))
-env.load("./railway/flatland.pkl")
+env.load("./railway/complex_scene.pkl")
file_load = True
"""
@@ -80,7 +80,7 @@ agent = Agent(state_size, action_size, "FC", 0)
agent.qnetwork_local.load_state_dict(torch.load('./Nets/avoid_checkpoint15000.pth'))
demo = True
-record_images = True
+record_images = False
@@ -129,15 +129,15 @@ for trials in range(1, n_trials + 1):
if demo:
eps = 0
# action = agent.act(np.array(obs[a]), eps=eps)
- action = 2 #agent.act(agent_obs[a], eps=eps)
+ action = agent.act(agent_obs[a], eps=eps)
action_prob[action] += 1
action_dict.update({a: action})
# Environment step
next_obs, all_rewards, done, _ = env.step(action_dict)
for a in range(env.get_num_agents()):
- data, distance, agent_data = env.obs_builder.split_tree(tree=np.array(next_obs[a]), num_features_per_node=8,
- current_depth=0)
+ data, distance, agent_data = split_tree(tree=np.array(next_obs[a]), num_features_per_node=8,
+ current_depth=0)
data = norm_obs_clip(data)
distance = norm_obs_clip(distance)
agent_data = np.clip(agent_data, -1, 1)
--
GitLab