small cleanups

examples/ImageNetModels/vgg16.py

@@ -22,7 +22,7 @@ def GroupNorm(x, group, gamma_initializer=tf.constant_initializer(1.)):
     """
     shape = x.get_shape().as_list()
     ndims = len(shape)
-    assert ndims in [2, 4]
+    assert ndims == 4, shape
     chan = shape[1]
     assert chan % group == 0, chan
     group_size = chan // group
@@ -61,8 +61,7 @@ class Model(ImageNetModel):
     weight_decay = 5e-4
 
     def get_logits(self, image):
-        with argscope(Conv2D, kernel_size=3,
-                      kernel_initializer=tf.variance_scaling_initializer(scale=2.)), \
+        with argscope(Conv2D, kernel_initializer=tf.variance_scaling_initializer(scale=2.)), \
                 argscope([Conv2D, MaxPooling, BatchNorm], data_format='channels_first'):
             logits = (LinearWrap(image)
                       .apply(convnormrelu, 'conv1_1', 64)
@@ -104,7 +103,6 @@ class Model(ImageNetModel):
 
 def get_data(name, batch):
     isTrain = name == 'train'
-    global args
     augmentors = fbresnet_augmentor(isTrain)
     return get_imagenet_dataflow(args.data, name, batch, augmentors)