From 653126fe437e72bb8425bf533494ccb104197a1b Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Thu, 24 Oct 2019 17:12:19 -0400
Subject: [PATCH] catchin error with None observation
---
torch_training/render_agent_behavior.py | 6 ++++--
torch_training/training_navigation.py | 8 +++++---
2 files changed, 9 insertions(+), 5 deletions(-)
diff --git a/torch_training/render_agent_behavior.py b/torch_training/render_agent_behavior.py
index 62cfa49..dd81bea 100644
--- a/torch_training/render_agent_behavior.py
+++ b/torch_training/render_agent_behavior.py
@@ -64,7 +64,7 @@ env = RailEnv(width=x_dim,
number_of_agents=n_agents,
stochastic_data=stochastic_data, # Malfunction data generator
obs_builder_object=TreeObservation)
-env.reset(True, True)
+env.reset()
env_renderer = RenderTool(env, gl="PILSVG", )
num_features_per_node = env.obs_builder.observation_dim
@@ -126,10 +126,12 @@ for trials in range(1, n_trials + 1):
action_dict.update({a: action})
# Environment step
obs, all_rewards, done, _ = env.step(action_dict)
+
env_renderer.render_env(show=True, show_predictions=True, show_observations=False)
# Build agent specific observations and normalize
for a in range(env.get_num_agents()):
- agent_obs[a] = normalize_observation(obs[a], tree_depth, observation_radius=10)
+ if obs[a]:
+ agent_obs[a] = normalize_observation(obs[a], tree_depth, observation_radius=10)
if done['__all__']:
diff --git a/torch_training/training_navigation.py b/torch_training/training_navigation.py
index 3358494..daac62d 100644
--- a/torch_training/training_navigation.py
+++ b/torch_training/training_navigation.py
@@ -117,8 +117,9 @@ def main(argv):
env_renderer.reset()
# Build agent specific observations
for a in range(env.get_num_agents()):
- agent_obs[a] = normalize_observation(obs[a], tree_depth, observation_radius=10)
- agent_obs_buffer[a] = agent_obs[a].copy()
+ if obs[a]:
+ agent_obs[a] = normalize_observation(obs[a], tree_depth, observation_radius=10)
+ agent_obs_buffer[a] = agent_obs[a].copy()
# Reset score and done
score = 0
@@ -150,7 +151,8 @@ def main(argv):
agent_obs_buffer[a] = agent_obs[a].copy()
agent_action_buffer[a] = action_dict[a]
- agent_obs[a] = normalize_observation(next_obs[a], tree_depth, observation_radius=10)
+ if next_obs[a]:
+ agent_obs[a] = normalize_observation(next_obs[a], tree_depth, observation_radius=10)
score += all_rewards[a] / env.get_num_agents()
--
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