1104 fix user angle in deep learning (#1105)

* fix user/angle in complete.py
- that had been renamed user/steering in the PR that
  merged the computer vision template.
- Much code in the deep learning pipeline explicitly
  hard-codes the literal `user/angle` so the deep learning
  code needs to continue to use that label.
- This fix uses the Pipe() part to rename 'user/steering'
  to 'user/angle' immediately after it is emitted by the
  controller part.

* pilot/steering -> pilot/angle

* Fix pipe.py and complete.py
- Pipe.py would output a bad tuple if only one argument
  was being passed throught.  Now it explictly checks.
- This caused complete.py to have invalid 'user/angle' values.

donkeycar/parts/pipe.py

@@ -2,12 +2,7 @@ class Pipe:
     """
     Just pipe all inputs to the output, so they can be renamed.
     """
-    def __init__(self):
-        self.running = True
-
     def run(self, *args):
-        if self.running:
-            return args
-
-    def shutdown(self):
-        self.running = False
+        # seems to be a python bug that takes a single argument
+        # return makes it into two element tuple with empty last element.
+        return args if len(args) > 1 else args[0]

donkeycar/templates/complete.py

@@ -40,7 +40,7 @@
 from donkeycar.parts.kinematics import Bicycle, InverseBicycle, BicycleUnnormalizeAngularVelocity
 from donkeycar.parts.explode import ExplodeDict
 from donkeycar.parts.transform import Lambda
-from donkeycar.parts.logger import LoggerPart
+from donkeycar.parts.pipe import Pipe
 from donkeycar.utils import *
 
 logger = logging.getLogger(__name__)
@@ -132,6 +132,11 @@ def drive(cfg, model_path=None, use_joystick=False, model_type=None,
     has_input_controller = hasattr(cfg, "CONTROLLER_TYPE") and cfg.CONTROLLER_TYPE != "mock"
     ctr = add_user_controller(V, cfg, use_joystick)
 
+    #
+    # convert 'user/steering' to 'user/angle' to be backward compatible with deep learning data
+    #
+    V.add(Pipe(), inputs=['user/steering'], outputs=['user/angle'])
+
     #
     # explode the buttons input map into individual output key/values in memory
     #
@@ -387,7 +392,7 @@ def run(self, *components):
         #
         # collect model inference outputs
         #
-        outputs = ['pilot/steering', 'pilot/throttle']
+        outputs = ['pilot/angle', 'pilot/throttle']
 
         if cfg.TRAIN_LOCALIZER:
             outputs.append("pilot/loc")
@@ -437,11 +442,10 @@ def run(self, *components):
     # based on the choice of user or autopilot drive mode
     #
     V.add(DriveMode(cfg.AI_THROTTLE_MULT),
-          inputs=['user/mode', 'user/steering', 'user/throttle',
-                  'pilot/steering', 'pilot/throttle'],
+          inputs=['user/mode', 'user/angle', 'user/throttle',
+                  'pilot/angle', 'pilot/throttle'],
           outputs=['steering', 'throttle'])
 
-    V.add(LoggerPart(['steering', 'throttle']), inputs=['steering', 'throttle'])
 
     if (cfg.CONTROLLER_TYPE != "pigpio_rc") and (cfg.CONTROLLER_TYPE != "MM1"):
         if isinstance(ctr, JoystickController):
@@ -471,10 +475,10 @@ def run(self, *components):
     # add tub to save data
     #
     if cfg.USE_LIDAR:
-        inputs = ['cam/image_array', 'lidar/dist_array', 'user/steering', 'user/throttle', 'user/mode']
+        inputs = ['cam/image_array', 'lidar/dist_array', 'user/angle', 'user/throttle', 'user/mode']
         types = ['image_array', 'nparray','float', 'float', 'str']
     else:
-        inputs=['cam/image_array','user/steering', 'user/throttle', 'user/mode']
+        inputs=['cam/image_array','user/angle', 'user/throttle', 'user/mode']
         types=['image_array','float', 'float','str']
 
     if cfg.HAVE_ODOM:
@@ -512,7 +516,7 @@ def run(self, *components):
             types  += ['nparray']
 
     if cfg.RECORD_DURING_AI:
-        inputs += ['pilot/steering', 'pilot/throttle']
+        inputs += ['pilot/angle', 'pilot/throttle']
         types += ['float', 'float']
 
     if cfg.HAVE_PERFMON: