fix docs and naming

docs/conf.py

@@ -34,7 +34,7 @@ import mock
                 #', '.join(map(str, args)) + ', ' \
                 #+ ', '.join(["{}={}".format(k,v) for k,v in kwargs.items()]) + ')'
 
-MOCK_MODULES = ['numpy', 'scipy', 'tensorflow', 'scipy.misc', 'h5py', 'nltk',
+MOCK_MODULES = ['scipy', 'tensorflow', 'scipy.misc', 'h5py', 'nltk',
                 'cv2', 'scipy.io', 'dill', 'zmq', 'subprocess32', 'lmdb', 'tornado.concurrent',
                 'tornado', 'msgpack', 'msgpack_numpy', 'ale_python_interface']
 for mod_name in MOCK_MODULES:

docs/requirements.txt

 termcolor
+numpy
 tqdm
 nltk
 decorator

examples/DoReFa-Net/alexnet-dorefa.py

@@ -144,10 +144,10 @@ class Model(ModelDesc):
 
         wrong = prediction_incorrect(logits, label, 1)
         nr_wrong = tf.reduce_sum(wrong, name='wrong-top1')
-        add_moving_summary(tf.reduce_mean(wrong, name='train_error_top1'))
+        add_moving_summary(tf.reduce_mean(wrong, name='train-error-top1'))
         wrong = prediction_incorrect(logits, label, 5)
         nr_wrong = tf.reduce_sum(wrong, name='wrong-top5')
-        add_moving_summary(tf.reduce_mean(wrong, name='train_error_top5'))
+        add_moving_summary(tf.reduce_mean(wrong, name='train-error-top5'))
 
         # weight decay on all W of fc layers
         wd_cost = regularize_cost('fc.*/W', l2_regularizer(5e-6))
@@ -235,8 +235,8 @@ def get_config():
                 'learning_rate', [(56, 2e-5), (64, 4e-6)]),
             InferenceRunner(data_test,
                 [ScalarStats('cost'),
-                 ClassificationError('wrong-top1', 'val-top1-error'),
-                 ClassificationError('wrong-top5', 'val-top5-error')])
+                 ClassificationError('wrong-top1', 'val-error-top1'),
+                 ClassificationError('wrong-top5', 'val-error-top1')])
         ]),
         model=Model(),
         step_per_epoch=10000,