From 9b16819fc590cc7f33101f456384c7e6e027a7a0 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Sun, 1 Sep 2019 14:09:35 -0400
Subject: [PATCH] fixed bug where all values are infinite
---
torch_training/render_agent_behavior.py | 3 +--
utils/observation_utils.py | 2 ++
2 files changed, 3 insertions(+), 2 deletions(-)
diff --git a/torch_training/render_agent_behavior.py b/torch_training/render_agent_behavior.py
index 651ec3e..f41cbb9 100644
--- a/torch_training/render_agent_behavior.py
+++ b/torch_training/render_agent_behavior.py
@@ -96,14 +96,13 @@ action_dict = dict()
final_action_dict = dict()
scores_window = deque(maxlen=100)
done_window = deque(maxlen=100)
-time_obs = deque(maxlen=2)
scores = []
dones_list = []
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, "navigator_checkpoint500.pth") as file_in:
+with path(torch_training.Nets, "navigator_checkpoint1100.pth") as file_in:
agent.qnetwork_local.load_state_dict(torch.load(file_in))
record_images = False
diff --git a/utils/observation_utils.py b/utils/observation_utils.py
index 7352601..be66a41 100644
--- a/utils/observation_utils.py
+++ b/utils/observation_utils.py
@@ -45,6 +45,8 @@ def norm_obs_clip(obs, clip_min=-1, clip_max=1, fixed_radius=0, normalize_to_ran
min_obs = 0 # min(max_obs, min_gt(obs, 0))
if normalize_to_range:
min_obs = min_gt(obs, 0)
+ if min_obs > max_obs:
+ min_obs = max_obs
if max_obs == min_obs:
return np.clip(np.array(obs) / max_obs, clip_min, clip_max)
norm = np.abs(max_obs - min_obs)
--
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