fix(encoder): add batching mode

jina/executors/encoders/image/onnx.py

@@ -3,6 +3,7 @@
 
 import re
 from .. import BaseImageEncoder
+from ...decorators import batching, as_ndarray
 
 
 class OnnxImageEncoder(BaseImageEncoder):
@@ -58,6 +59,8 @@ def _append_outputs(input_fn, outputs_name_to_append, output_fn):
         model.graph.output.append(feature_map)
         onnx.save(model, output_fn)
 
+    @batching
+    @as_ndarray
     def encode(self, data: 'np.ndarray', *args, **kwargs) -> 'np.ndarray':
         """
 

jina/executors/encoders/nlp/char.py

@@ -1,6 +1,7 @@
 import numpy as np
 
 from .. import BaseTextEncoder
+from ...decorators import batching, as_ndarray
 
 
 class OneHotTextEncoder(BaseTextEncoder):
@@ -28,6 +29,8 @@ def post_init(self):
         self.embeddings = np.eye(self.dim) * self.on_value + \
                           (np.ones((self.dim, self.dim)) - np.eye(self.dim)) * self.off_value
 
+    @batching
+    @as_ndarray
     def encode(self, data: 'np.ndarray', *args, **kwargs) -> 'np.ndarray':
         """
 

jina/executors/encoders/nlp/flair.py

@@ -3,6 +3,7 @@
 import numpy as np
 
 from .. import BaseTextEncoder
+from ...decorators import batching, as_ndarray
 
 
 class FlairTextEncoder(BaseTextEncoder):
@@ -59,6 +60,8 @@ def post_init(self):
             self.model = DocumentPoolEmbeddings(embeddings_list, pooling=self.pooling_strategy)
             self.logger.info('initialize flair encoder with embeddings: {}'.format(self.embeddings))
 
+    @batching
+    @as_ndarray
     def encode(self, data: 'np.ndarray', *args, **kwargs) -> 'np.ndarray':
         """
 

jina/executors/encoders/numeric/pca.py

@@ -1,5 +1,4 @@
 import numpy as np
-import os
 from ...decorators import batching, require_train
 
 from .. import BaseNumericEncoder