From f528b17102c08a7e5eb3227887ed5313f2e0f17d Mon Sep 17 00:00:00 2001
From: Jeroen Oudshoorn <oudshoorn.jeroen@gmail.com>
Date: Sun, 17 Sep 2023 22:14:09 +0200
Subject: [PATCH] v2.4.1

Signed-off-by: Jeroen Oudshoorn <oudshoorn.jeroen@gmail.com>
---
 pwnagotchi/ai/train.py                     | 20 ++++++++++----------
 pwnagotchi/plugins/default/fix_services.py |  2 ++
 2 files changed, 12 insertions(+), 10 deletions(-)

diff --git a/pwnagotchi/ai/train.py b/pwnagotchi/ai/train.py
index c007230f..58758d6f 100644
--- a/pwnagotchi/ai/train.py
+++ b/pwnagotchi/ai/train.py
@@ -54,7 +54,7 @@ class Stats(object):
     def load(self):
         with self._lock:
             if os.path.exists(self.path) and os.path.getsize(self.path) > 0:
-                logging.info("[ai] loading %s" % self.path)
+                logging.info("[AI] loading %s" % self.path)
                 with open(self.path, 'rt') as fp:
                     obj = json.load(fp)
 
@@ -64,7 +64,7 @@ class Stats(object):
 
     def save(self):
         with self._lock:
-            logging.info("[ai] saving %s" % self.path)
+            logging.info("[AI] saving %s" % self.path)
 
             data = json.dumps({
                 'born_at': self.born_at,
@@ -114,7 +114,7 @@ class AsyncTrainer(object):
         _thread.start_new_thread(self._ai_worker, ())
 
     def _save_ai(self):
-        logging.info("[ai] saving model to %s ..." % self._nn_path)
+        logging.info("[AI] saving model to %s ..." % self._nn_path)
         temp = "%s.tmp" % self._nn_path
         self._model.save(temp)
         os.replace(temp, self._nn_path)
@@ -133,15 +133,15 @@ class AsyncTrainer(object):
 
     def on_ai_policy(self, new_params):
         plugins.on('ai_policy', self, new_params)
-        logging.info("[ai] setting new policy:")
+        logging.info("[AI] setting new policy:")
         for name, value in new_params.items():
             if name in self._config['personality']:
                 curr_value = self._config['personality'][name]
                 if curr_value != value:
-                    logging.info("[ai] ! %s: %s -> %s" % (name, curr_value, value))
+                    logging.info("[AI] ! %s: %s -> %s" % (name, curr_value, value))
                     self._config['personality'][name] = value
             else:
-                logging.error("[ai] param %s not in personality configuration!" % name)
+                logging.error("[AI] param %s not in personality configuration!" % name)
 
         self.run('set wifi.ap.ttl %d' % self._config['personality']['ap_ttl'])
         self.run('set wifi.sta.ttl %d' % self._config['personality']['sta_ttl'])
@@ -152,12 +152,12 @@ class AsyncTrainer(object):
         plugins.on('ai_ready', self)
 
     def on_ai_best_reward(self, r):
-        logging.info("[ai] best reward so far: %s" % r)
+        logging.info("[AI] best reward so far: %s" % r)
         self._view.on_motivated(r)
         plugins.on('ai_best_reward', self, r)
 
     def on_ai_worst_reward(self, r):
-        logging.info("[ai] worst reward so far: %s" % r)
+        logging.info("[AI] worst reward so far: %s" % r)
         self._view.on_demotivated(r)
         plugins.on('ai_worst_reward', self, r)
 
@@ -174,7 +174,7 @@ class AsyncTrainer(object):
                 self._model.env.render()
                 # enter in training mode?
                 if random.random() > self._config['ai']['laziness']:
-                    logging.info("[ai] learning for %d epochs ..." % epochs_per_episode)
+                    logging.info("[AI] learning for %d epochs ..." % epochs_per_episode)
                     try:
                         self.set_training(True, epochs_per_episode)
                         # back up brain file before starting new training set
@@ -184,7 +184,7 @@ class AsyncTrainer(object):
                         self._view.set("mode", "  AI")
                         self._model.learn(total_timesteps=epochs_per_episode, callback=self.on_ai_training_step)
                     except Exception as e:
-                        logging.exception("[ai] error while training (%s)", e)
+                        logging.exception("[AI] error while training (%s)", e)
                     finally:
                         self.set_training(False)
                         obs = self._model.env.reset()
diff --git a/pwnagotchi/plugins/default/fix_services.py b/pwnagotchi/plugins/default/fix_services.py
index c7886697..ed06d3d2 100644
--- a/pwnagotchi/plugins/default/fix_services.py
+++ b/pwnagotchi/plugins/default/fix_services.py
@@ -348,6 +348,8 @@ class FixServices(plugins.Plugin):
                     logging.info("[Fix_Services] wlan0mon didn't make it. trying again")
                     if not display:
                         print(" wlan0mon didn't make it. trying again")
+                else:
+                    pwnagotchi.reboot()
 
             # exited the loop, so hopefully it loaded
             if tries < 3: