From 73919673f7d31938cd60b4a24dd3dcaf38f8b1b7 Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Sat, 22 Jun 2019 12:20:40 -0500
Subject: [PATCH] minor test of multi speed implementation
---
torch_training/training_navigation.py | 27 +++++++++++++++++----------
1 file changed, 17 insertions(+), 10 deletions(-)
diff --git a/torch_training/training_navigation.py b/torch_training/training_navigation.py
index c043372..634db69 100644
--- a/torch_training/training_navigation.py
+++ b/torch_training/training_navigation.py
@@ -40,21 +40,22 @@ env = RailEnv(width=15,
rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=10, min_dist=10, max_dist=99999, seed=0),
number_of_agents=1)
-
+"""
env = RailEnv(width=10,
height=20, obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()))
env.load("./railway/complex_scene.pkl")
+file_load = True
"""
-env = RailEnv(width=12,
- height=12,
- rail_generator=complex_rail_generator(nr_start_goal=5, nr_extra=5, min_dist=10, max_dist=99999, seed=0),
+env = RailEnv(width=20,
+ height=20,
+ rail_generator=complex_rail_generator(nr_start_goal=20, nr_extra=5, min_dist=10, max_dist=99999, seed=0),
obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()),
- number_of_agents=5)
-
+ number_of_agents=15)
+file_load = False
env.reset(True, True)
-
-env_renderer = RenderTool(env, gl="PILSVG")
+"""
+env_renderer = RenderTool(env, gl="PILSVG",)
handle = env.get_agent_handles()
state_size = 168 * 2
@@ -78,6 +79,7 @@ agent = Agent(state_size, action_size, "FC", 0)
agent.qnetwork_local.load_state_dict(torch.load('./Nets/avoid_checkpoint15000.pth'))
demo = True
+record_images = False
def max_lt(seq, val):
"""
@@ -129,7 +131,10 @@ def norm_obs_clip(obs, clip_min=-1, clip_max=1):
for trials in range(1, n_trials + 1):
# Reset environment
- obs = env.reset(True, True)
+ if file_load :
+ obs = env.reset(False, False)
+ else:
+ obs = env.reset(True, True)
if demo:
env_renderer.set_new_rail()
final_obs = obs.copy()
@@ -154,13 +159,15 @@ for trials in range(1, n_trials + 1):
for step in range(max_steps):
if demo:
env_renderer.renderEnv(show=True, show_observations=False)
+ if record_images:
+ env_renderer.gl.saveImage("./Images/frame_{:04d}.bmp".format(step))
# print(step)
# Action
for a in range(env.get_num_agents()):
if demo:
eps = 0
# action = agent.act(np.array(obs[a]), eps=eps)
- action = agent.act(agent_obs[a], eps=eps)
+ action = 2 #agent.act(agent_obs[a], eps=eps)
action_prob[action] += 1
action_dict.update({a: action})
# Environment step
--
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