Fix review comments

tutorials/image/cifar10_estimator/cifar10_main.py

@@ -143,7 +143,6 @@ def _resnet_model_fn(features, labels, mode, params):
     with tf.device(consolidation_device):
       # Suggested learning rate scheduling from
       # https://github.com/ppwwyyxx/tensorpack/blob/master/examples/ResNet/cifar10-resnet.py#L155
-      # users could apply other scheduling.
       num_batches_per_epoch = cifar10.Cifar10DataSet.num_examples_per_epoch(
           'train') // (params['train_batch_size'] * num_workers)
       boundaries = [
@@ -485,13 +484,11 @@ def main(job_dir,
   parser.add_argument(
       '--num-intra-threads',
       type=int,
-      default=1,
+      default=0,
       help="""\
-      Number of threads to use for intra-op parallelism. If set to 0, the
-      system will pick an appropriate number. The default is 1 since in this
-      example CPU only handles the input pipeline and gradient aggregation
-      (when --is-cpu-ps). Ops that could potentially benefit from intra-op
-      parallelism are scheduled to run on GPUs.\
+      Number of threads to use for intra-op parallelism. When training on CPU
+      set to 0 to have the system pick the appropriate number or alternatively
+      set it to the number of physical CPU cores.\
       """
   )
   parser.add_argument(
@@ -525,15 +522,16 @@ def main(job_dir,
 
   if args.num_gpus < 0:
     raise ValueError(
-        'Invalid GPU count: \"num_gpus\" must be 0 or a positive integer.')
+        'Invalid GPU count: \"--num-gpus\" must be 0 or a positive integer.')
   if args.num_gpus == 0 and args.variable_strategy == 'GPU':
     raise ValueError(
-        'No GPU available for use, must use CPU to average gradients.')
+        'num-gpus=0, CPU must be used as parameter server. Set'
+        '--variable-strategy=CPU.')
   if (args.num_layers - 2) % 6 != 0:
-    raise ValueError('Invalid num_layers parameter.')
+    raise ValueError('Invalid --num-layers parameter.')
   if args.num_gpus != 0 and args.train_batch_size % args.num_gpus != 0:
-    raise ValueError('train_batch_size must be multiple of num_gpus.')
+    raise ValueError('--train-batch-size must be multiple of --num-gpus.')
   if args.num_gpus != 0 and args.eval_batch_size % args.num_gpus != 0:
-    raise ValueError('eval_batch_size must be multiple of num_gpus.')
+    raise ValueError('--eval-batch-size must be multiple of --num-gpus.')
 
   main(**vars(args))

tutorials/image/cifar10_estimator/cifar10_utils.py

@@ -1,5 +1,8 @@
+import collections
 import six
 
+import tensorflow as tf
+
 from tensorflow.python.platform import tf_logging as logging
 
 from tensorflow.core.framework import node_def_pb2