fix(image encoder): define use_cuda variable via args

gnes/encoder/image/base.py

@@ -27,15 +27,16 @@ class BasePytorchEncoder(BaseImageEncoder):
     def __init__(self, model_name: str,
                  layers: List[str],
                  model_dir: str,
-                 batch_size: int = 64, *args, **kwargs):
+                 batch_size: int = 64,
+                 use_cuda: bool = False,
+                 *args, **kwargs):
         super().__init__(*args, **kwargs)
 
         self.batch_size = batch_size
         self.model_dir = model_dir
         self.model_name = model_name
         self.layers = layers
-        self.is_trained = True
-        self._use_cuda = False
+        self._use_cuda = use_cuda
 
     def post_init(self):
         import torch

gnes/encoder/image/inception.py

@@ -26,14 +26,14 @@ class TFInceptionEncoder(BaseImageEncoder):
     def __init__(self, model_dir: str,
                  batch_size: int = 64,
                  select_layer: str = 'PreLogitsFlatten',
-                 use_gpu: bool = True,
+                 use_cuda: bool = False,
                  *args, **kwargs):
         super().__init__(*args, **kwargs)
 
         self.model_dir = model_dir
         self.batch_size = batch_size
         self.select_layer = select_layer
-        self.use_gpu = use_gpu
+        self._use_cuda = use_cuda
         self.inception_size_x = 299
         self.inception_size_y = 299
 
@@ -54,7 +54,7 @@ def post_init(self):
                                                         dropout_keep_prob=1.0)
 
         config = tf.ConfigProto(log_device_placement=False)
-        if self.use_gpu:
+        if self._use_cuda:
             config.gpu_options.allow_growth = True
         self.sess = tf.Session(config=config)
         self.saver = tf.train.Saver()