fix: rename base classes

jina/executors/__init__.py

@@ -128,7 +128,7 @@ def __init__(self, *args, **kwargs):
         self._last_snapshot_ts = datetime.now()
         self._drivers = {}  # type: Dict[str, List['BaseDriver']]
         self._attached_pea = None
-        self._backend = 'tensorflow'
+        self._backend = None
 
     def _post_init_wrapper(self, _metas: Dict = None, _requests: Dict = None, fill_in_metas: bool = True):
         with TimeContext('post initiating, this may take some time', self.logger):
@@ -560,7 +560,7 @@ def __call__(self, req_type, *args, **kwargs):
             raise NoDriverForRequest(req_type)
 
 
-class _BaseFramewordExecutor(BaseExecutor):
+class BaseFramewordExecutor(BaseExecutor):
     def post_init(self):
         super().post_init()
         self.build_model()
@@ -573,7 +573,7 @@ def set_device(self):
         raise NotImplementedError
 
 
-class BaseTorchExecutor(_BaseFramewordExecutor):
+class BaseTorchExecutor(BaseFramewordExecutor):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self._backend = 'pytorch'
@@ -591,7 +591,7 @@ def set_device(self):
         self.model.set_providers(self._device)
 
 
-class BaseTfExecutor(_BaseFramewordExecutor):
+class BaseTfExecutor(BaseFramewordExecutor):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self._backend = 'tensorflow'
@@ -601,7 +601,7 @@ def set_device(self):
         tf.config.experimental.set_visible_devices(self._device)
 
 
-class BasePaddleExecutor(_BaseFramewordExecutor):
+class BasePaddleExecutor(BaseFramewordExecutor):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self._backend = 'paddlepaddle'

jina/executors/encoders/nlp/transformer.py

@@ -8,10 +8,10 @@
 from .. import BaseTextEncoder
 from ..helper import reduce_mean, reduce_max, reduce_min, reduce_cls
 from ...decorators import batching, as_ndarray
-from ... import _BaseFramewordExecutor, BaseTfExecutor, BaseTorchExecutor
+from ... import BaseFramewordExecutor, BaseTfExecutor, BaseTorchExecutor
 
 
-class BaseTransformerEncoder(_BaseFramewordExecutor):
+class BaseTransformerEncoder(BaseFramewordExecutor):
     """
     :class:`TransformerTextEncoder` encodes data from an array of string in size `B` into an ndarray in size `B x D`.
     """