Fix undefined_variable lint errors in examples (#12052)

* Fix lint errors in dqn example

* Fix lint error in gluon example

* Fix undefined error in autoencoder example

example/autoencoder/model.py

@@ -22,7 +22,7 @@
 import numpy as np
 try:
     import cPickle as pickle
-except ModuleNotFoundError:
+except ImportError:
     import pickle
 
 

example/gluon/image_classification.py

@@ -30,7 +30,8 @@
 from mxnet.metric import Accuracy, TopKAccuracy, CompositeEvalMetric
 import numpy as np
 
-from data import *
+from data import (get_cifar10_iterator, get_imagenet_iterator,
+                  get_caltech101_iterator, dummy_iterator)
 
 # logging
 logging.basicConfig(level=logging.INFO)

example/reinforcement-learning/dqn/atari_game.py

@@ -22,7 +22,7 @@
 import cv2
 import logging
 import os
-from utils import *
+from utils import get_numpy_rng
 from replay_memory import ReplayMemory
 from game import Game
 from game import DEFAULT_MAX_EPISODE_STEP

example/reinforcement-learning/dqn/base.py

@@ -23,8 +23,9 @@
 import os
 import pickle
 from collections import OrderedDict
+from utils import (get_bucket_key, save_params,
+                   save_misc, load_params)
 import logging
-from utils import *
 
 logger = logging.getLogger(__name__)
 

example/reinforcement-learning/dqn/dqn_demo.py

@@ -23,9 +23,11 @@
 from base import Base
 from operators import *
 from atari_game import AtariGame
-from utils import *
+from utils import get_numpy_rng, parse_ctx
 import logging
 import argparse
+import sys
+import time
 
 root = logging.getLogger()
 root.setLevel(logging.DEBUG)

example/reinforcement-learning/dqn/dqn_run_test.py

@@ -28,7 +28,7 @@
 import sys
 from base import Base
 from atari_game import AtariGame
-from utils import *
+from utils import get_numpy_rng
 from operators import *
 
 root = logging.getLogger()

example/reinforcement-learning/dqn/replay_memory.py

@@ -21,7 +21,7 @@
 import mxnet.ndarray as nd
 import numpy
 import copy
-from utils import *
+from utils import get_numpy_rng
 
 
 class ReplayMemory(object):