Merge pull request #60 from aws-deepracer-community/log-new-field

Add fix to the new obstacle_crash_counter field in log file

Author: larsll

deepracer/logs/log.py

@@ -39,8 +39,8 @@ class DeepRacerLog:
         "episode_status",
         "pause_duration"
     ]
-    # TODO Column names as a workaround for an excess comma in the CSV file
-    _COL_NAMES_WORKAROUND = [
+    # Additional obstacle_crash_counter column is added to the CSV file.
+    _COL_NAMES_NEW = [
         "episode",
         "steps",
         "x",
@@ -49,7 +49,6 @@ class DeepRacerLog:
         "steering_angle",
         "speed",
         "action",
-        "action_b",
         "reward",
         "done",
         "all_wheels_on_track",
@@ -58,7 +57,8 @@ class DeepRacerLog:
         "track_len",
         "tstamp",
         "episode_status",
-        "pause_duration"
+        "pause_duration",
+        "obstacle_crash_counter"
     ]
     _HYPERPARAM_KEYS = [
         "batch_size",
@@ -120,10 +120,10 @@ def __init__(self, model_folder: str = None, filehandler: FileHandler = None,
     def _read_csv(self, path: str, splitRegex, type: LogType = LogType.TRAINING):
         try:
             csv_bytes = self.fh.get_file(path)
-            # TODO: this is a workaround and should be removed when logs are fixed
+            # Work also with a new column
             df = pd.read_csv(BytesIO(csv_bytes), encoding='utf8',
-                             names=self._COL_NAMES_WORKAROUND, header=0)
-            df = df.drop("action_b", axis=1)
+                             names=self._COL_NAMES_NEW, header=0)
+            df = df.drop("obstacle_crash_counter", axis=1)
         except pd.errors.ParserError:
             try:
                 df = pd.read_csv(BytesIO(csv_bytes), names=self._COL_NAMES, header=0)

deepracer/logs/log_utils.py

@@ -143,10 +143,6 @@ def convert_to_pandas(data, episodes_per_iteration=20, stream=None):
 
         for d in data[:]:
             parts = d.rstrip().split(",")
-            # TODO: this is a workaround and should be removed when logs are fixed
-            parts_workaround = 0
-            if len(parts) > 17:
-                parts_workaround = 1
             episode = int(parts[0])
             steps = int(parts[1])
             x = float(parts[2])
@@ -158,16 +154,16 @@ def convert_to_pandas(data, episodes_per_iteration=20, stream=None):
                 action = int(parts[7])
             except ValueError as e:
                 action = -1
-            reward = float(parts[8+parts_workaround])
-            done = 0 if 'False' in parts[9+parts_workaround] else 1
-            all_wheels_on_track = parts[10+parts_workaround]
-            progress = float(parts[11+parts_workaround])
-            closest_waypoint = int(parts[12+parts_workaround])
-            track_len = float(parts[13+parts_workaround])
-            tstamp = Decimal(parts[14+parts_workaround])
-            episode_status = parts[15+parts_workaround]
-            if len(parts) > 16+parts_workaround:
-                pause_duration = float(parts[16+parts_workaround])
+            reward = float(parts[8])
+            done = 0 if 'False' in parts[9] else 1
+            all_wheels_on_track = parts[10]
+            progress = float(parts[11])
+            closest_waypoint = int(parts[12])
+            track_len = float(parts[13])
+            tstamp = Decimal(parts[14])
+            episode_status = parts[15]
+            if len(parts) > 16:
+                pause_duration = float(parts[16])
             else:
                 pause_duration = 0.0