Fixed lint and flag issues

official/resnet/keras/keras_cifar_benchmark.py

@@ -52,7 +52,7 @@ class KerasCifar10BenchmarkTests(object):
   def keras_resnet56_no_dist_strat_1_gpu(self):
     """Test keras based model with Keras fit but not distribution strategies."""
     self._setup()
-    flags.FLAGS.dist_strat_off = True
+    flags.FLAGS.turn_off_distribution_strategy = True
     flags.FLAGS.num_gpus = 1
     flags.FLAGS.data_dir = DATA_DIR
     flags.FLAGS.batch_size = 128

official/resnet/keras/keras_cifar_main.py

@@ -39,7 +39,7 @@ def learning_rate_schedule(current_epoch,
                            current_batch,
                            batches_per_epoch,
                            batch_size):
-  """Handles linear scaling rule, gradual warmup, and LR decay.
+  """Handles linear scaling rule and LR decay.
 
   Scale learning rate at epoch boundaries provided in LR_SCHEDULE by the
   provided scaling factor.

official/resnet/keras/resnet_cifar_model.py

@@ -180,12 +180,12 @@ def resnet56(classes=100, training=None):
   """Instantiates the ResNet56 architecture.
 
   Arguments:
-      classes: optional number of classes to classify images into
-      training: Only used if training keras model with Estimator.  In other
-      scenarios it is handled automatically.
+    classes: optional number of classes to classify images into
+    training: Only used if training keras model with Estimator.  In other
+    scenarios it is handled automatically.
 
   Returns:
-      A Keras model instance.
+    A Keras model instance.
   """
   # Determine proper input shape
   if backend.image_data_format() == 'channels_first':

official/utils/misc/distribution_utils.py

@@ -32,7 +32,7 @@ def get_distribution_strategy(num_gpus,
       See tf.contrib.distribute.AllReduceCrossDeviceOps for available
       algorithms. If None, DistributionStrategy will choose based on device
       topology.
-      turn_off_distribution_strategy: when set to True, do not use any
+    turn_off_distribution_strategy: when set to True, do not use any
       distribution strategy. Note that when it is True, and num_gpus is
       larger than 1, it will raise a ValueError.