replace `FLAGS.batch_size` by `images.get_shape()[0]`

We can directly get `batch_size` by `images.get_shape()[0]` in `inference` method, since maybe we will not use `cifar.inputs` method to build the input.

tutorials/image/cifar10/cifar10.py

@@ -240,7 +240,7 @@ def inference(images):
   # local3
   with tf.variable_scope('local3') as scope:
     # Move everything into depth so we can perform a single matrix multiply.
-    reshape = tf.reshape(pool2, [FLAGS.batch_size, -1])
+    reshape = tf.reshape(pool2, [images.get_shape()[0], -1])
     dim = reshape.get_shape()[1].value
     weights = _variable_with_weight_decay('weights', shape=[dim, 384],
                                           stddev=0.04, wd=0.004)