fix more issues.

Author: luomai

tensorlayer/layers/convolution.py

@@ -508,7 +508,7 @@ def __init__(
         else:
             raise Exception("Donot support shape %s" % self.inputs.get_shape())
         logging.info("UpSampling2dLayer %s: is_scale:%s size:%s method:%d align_corners:%s" % (name, is_scale, size, method, align_corners))
-        with tf.variable_scope(name) as vs:
+        with tf.variable_scope(name):
             try:
                 self.outputs = tf.image.resize_images(self.inputs, size=size, method=method, align_corners=align_corners)
             except Exception:  # for TF 0.10

tensorlayer/layers/recurrent.py

@@ -1311,7 +1311,7 @@ def __init__(
 
             # Apply dropout
             if dropout:
-                if type(dropout) in [tuple, list]:
+                if isinstance(dropout, (tuple, list)):
                     in_keep_prob = dropout[0]
                     out_keep_prob = dropout[1]
                 elif isinstance(dropout, float):

tensorlayer/prepro.py

@@ -2794,7 +2794,7 @@ def _get_coord(coord):
 
     coords_new = list()
     classes_new = list()
-    for i in range(len(coords)):
+    for i, _ in enumerate(coords):
         coord = coords[i]
         assert len(coord) == 4, "coordinate should be 4 values : [x, y, w, h]"
         if is_rescale:
@@ -3041,7 +3041,7 @@ def sequences_add_end_id(sequences, end_id=888):
 
     """
     sequences_out = [[] for _ in range(len(sequences))]  #[[]] * len(sequences)
-    for i in range(len(sequences)):
+    for i, _ in enumerate(sequences):
         sequences_out[i] = sequences[i] + [end_id]
     return sequences_out