From c528e652f2fa570b12d4ed9c3fed2f72f4f803bb Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Tue, 23 Apr 2019 08:54:19 +0200
Subject: [PATCH] minor bugfixes in training script
---
examples/training_navigation.py | 40 +++++++++------------------------
1 file changed, 11 insertions(+), 29 deletions(-)
diff --git a/examples/training_navigation.py b/examples/training_navigation.py
index 3797d1cf..7b35cb21 100644
--- a/examples/training_navigation.py
+++ b/examples/training_navigation.py
@@ -3,7 +3,7 @@ from flatland.core.env_observation_builder import TreeObsForRailEnv
from flatland.utils.rendertools import *
from flatland.baselines.dueling_double_dqn import Agent
from collections import deque
-import torch
+import torch,random
random.seed(1)
np.random.seed(1)
@@ -18,22 +18,22 @@ transition_probability = [1.0, # empty cell - Case 0
1.0, # Case 6 - symmetrical
1.0] # Case 7 - dead end
"""
+# Example generate a rail given a manual specification,
+# a map of tuples (cell_type, rotation)
transition_probability = [1.0, # empty cell - Case 0
1.0, # Case 1 - straight
- 0.5, # Case 2 - simple switch
- 0.2, # Case 3 - diamond drossing
+ 1.0, # Case 2 - simple switch
+ 0.3, # Case 3 - diamond drossing
0.5, # Case 4 - single slip
- 0.1, # Case 5 - double slip
+ 0.5, # Case 5 - double slip
0.2, # Case 6 - symmetrical
- 0.01] # Case 7 - dead end
+ 0.0] # Case 7 - dead end
# Example generate a random rail
-env = RailEnv(width=20,
- height=20,
+env = RailEnv(width=7,
+ height=7,
rail_generator=random_rail_generator(cell_type_relative_proportion=transition_probability),
- number_of_agents=10)
-env.reset()
-
+ number_of_agents=1)
env_renderer = RenderTool(env)
handle = env.get_agent_handles()
@@ -51,28 +51,10 @@ dones_list = []
agent = Agent(state_size, action_size, "FC", 0)
-# Example generate a rail given a manual specification,
-# a map of tuples (cell_type, rotation)
-specs = [[(0, 0), (0, 0), (0, 0), (0, 0), (7, 0), (0, 0)],
- [(7, 270), (1, 90), (1, 90), (1, 90), (2, 90), (7, 90)]]
-
-env = RailEnv(width=6,
- height=2,
- rail_generator=rail_from_manual_specifications_generator(specs),
- number_of_agents=1,
- obs_builder_object=TreeObsForRailEnv(max_depth=2))
-
-env.agents_position[0] = [1, 4]
-env.agents_target[0] = [1, 1]
-env.agents_direction[0] = 1
-# TODO: watch out: if these variables are overridden, the obs_builder object has to be reset, too!
-env.obs_builder.reset()
-
-
for trials in range(1, n_trials + 1):
# Reset environment
- obs, all_rewards, done, _ = env.step({0: 0})
+ obs = env.reset()
# env.obs_builder.util_print_obs_subtree(tree=obs[0], num_elements_per_node=5)
--
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