wrong dataset in dorefa

examples/Atari2600/common.py

@@ -54,7 +54,7 @@ def eval_with_funcs(predict_funcs, nr_eval):
         k.start()
     stat = StatCounter()
     try:
-        for _ in tqdm(range(nr_eval)):
+        for _ in tqdm(range(nr_eval), **get_tqdm_kwargs()):
             r = q.get()
             stat.feed(r)
     except:

examples/DoReFa-Net/alexnet-dorefa.py

@@ -155,9 +155,7 @@ class Model(ModelDesc):
 
 def get_data(dataset_name):
     isTrain = dataset_name == 'train'
-    #ds = dataset.ILSVRC12(args.data, dataset_name,
-            #shuffle=True if isTrain else False)
-    ds = dataset.ILSVRC12('/home/wyx/data/fake_ilsvrc', dataset_name,
+    ds = dataset.ILSVRC12(args.data, dataset_name,
             shuffle=True if isTrain else False)
 
     meta = dataset.ILSVRCMeta()

examples/mnist-convnet.py

@@ -9,7 +9,6 @@ import os, sys
 import argparse
 
 from tensorpack import *
-from tensorpack.tfutils.summary import add_moving_summary
 
 """
 MNIST ConvNet example.
@@ -52,13 +51,13 @@ class Model(ModelDesc):
         wrong = symbolic_functions.prediction_incorrect(logits, label)
         nr_wrong = tf.reduce_sum(wrong, name='wrong')
         # monitor training error
-        add_moving_summary(tf.reduce_mean(wrong, name='train_error'))
+        summary.add_moving_summary(tf.reduce_mean(wrong, name='train_error'))
 
         # weight decay on all W of fc layers
         wd_cost = tf.mul(1e-5,
                          regularize_cost('fc.*/W', tf.nn.l2_loss),
                          name='regularize_loss')
-        add_moving_summary(cost, wd_cost)
+        summary.add_moving_summary(cost, wd_cost)
 
         summary.add_param_summary([('.*/W', ['histogram'])])   # monitor histogram of all W
         self.cost = tf.add_n([wd_cost, cost], name='cost')

tensorpack/models/nonlin.py

@@ -14,7 +14,7 @@ __all__ = ['Maxout', 'PReLU', 'LeakyReLU', 'BNReLU', 'NonLinearity']
 @layer_register(log_shape=False)
 def Maxout(x, num_unit):
     """
-    Maxout networks as in `Maxout Networks <http://arxiv.org/abs/1302.4389>`_.
+    Maxout as in `Maxout Networks <http://arxiv.org/abs/1302.4389>`_.
 
     :param input: a NHWC or NC tensor.
     :param num_unit: a int. must be divisible by C.