* Bump version -> 4.2.1 (#881)

* Revert to passing full path to model in training call which got accidentally broken in 4.2 master.

donkeycar/__init__.py

@@ -1,7 +1,7 @@
 import sys
 from pyfiglet import Figlet
 
-__version__ = '4.2.0'
+__version__ = '4.2.1'
 f = Figlet(font='speed')
 
 print(f.renderText('Donkey Car'))

donkeycar/pipeline/database.py

@@ -33,8 +33,8 @@ def generate_model_name(self) -> Tuple[str, int]:
         else:
             this_num = 0
         date = time.strftime('%y-%m-%d')
-        name = 'pilot_' + date + '_' + str(this_num)
-        return name, this_num
+        name = f'pilot_{date}_{this_num}.h5'
+        return os.path.join(self.cfg.MODELS_PATH, name), this_num
 
     def to_df(self) -> pd.DataFrame:
         if self.entries:

donkeycar/pipeline/training.py

@@ -81,6 +81,15 @@ def create_tf_data(self) -> tf.data.Dataset:
 def get_model_train_details(cfg: Config, database: PilotDatabase,
                             model: str = None, model_type: str = None) \
         -> Tuple[str, int, str, bool]:
+    """
+    Returns automatic model name if none is given
+    :param cfg:         donkey config
+    :param database:    model database with existing training data
+    :param model:       model path
+    :param model_type:  type of model, like 'linear', 'tflite_linear', etc
+    :return:            tuple of model path, number, training type, and if
+                        tflite is requested
+    """
     if not model_type:
         model_type = cfg.DEFAULT_MODEL_TYPE
     train_type = model_type
@@ -90,12 +99,13 @@ def get_model_train_details(cfg: Config, database: PilotDatabase,
         is_tflite = True
     model_num = 0
     if not model:
-        model_name, model_num = database.generate_model_name()
+        model_path, model_num = database.generate_model_name()
     else:
-        model_name, model_ext = os.path.splitext(model)
+        _, model_ext = os.path.splitext(model)
+        model_path = model
         is_tflite = model_ext == '.tflite'
 
-    return model_name, model_num, train_type, is_tflite
+    return model_path, model_num, train_type, is_tflite
 
 
 def train(cfg: Config, tub_paths: str, model: str = None,
@@ -105,10 +115,9 @@ def train(cfg: Config, tub_paths: str, model: str = None,
     Train the model
     """
     database = PilotDatabase(cfg)
-    model_name, model_num, train_type, is_tflite = \
+    model_path, model_num, train_type, is_tflite = \
         get_model_train_details(cfg, database, model, model_type)
 
-    output_path = os.path.join(cfg.MODELS_PATH, model_name + '.h5')
     kl = get_model_by_type(train_type, cfg)
     if transfer:
         kl.load(transfer)
@@ -135,7 +144,7 @@ def train(cfg: Config, tub_paths: str, model: str = None,
     assert val_size > 0, "Not enough validation data, decrease the batch " \
                          "size or add more data."
 
-    history = kl.train(model_path=output_path,
+    history = kl.train(model_path=model_path,
                        train_data=dataset_train,
                        train_steps=train_size,
                        batch_size=cfg.BATCH_SIZE,
@@ -146,14 +155,14 @@ def train(cfg: Config, tub_paths: str, model: str = None,
                        min_delta=cfg.MIN_DELTA,
                        patience=cfg.EARLY_STOP_PATIENCE,
                        show_plot=cfg.SHOW_PLOT)
-
+    base_path = os.path.splitext(model_path)[0]
     if is_tflite:
-        tf_lite_model_path = f'{os.path.splitext(output_path)[0]}.tflite'
-        keras_model_to_tflite(output_path, tf_lite_model_path)
+        tf_lite_model_path = f'{base_path}.tflite'
+        keras_model_to_tflite(model_path, tf_lite_model_path)
 
     database_entry = {
         'Number': model_num,
-        'Name': model_name,
+        'Name': os.path.basename(base_path),
         'Type': str(kl),
         'Tubs': tub_paths,
         'Time': time(),

setup.py

@@ -24,7 +24,7 @@ def package_files(directory, strip_leading):
     long_description = fh.read()
 
 setup(name='donkeycar',
-      version='4.2.0',
+      version='4.2.1',
       long_description=long_description,
       description='Self driving library for python.',
       url='https://github.com/autorope/donkeycar',