Small fixes

tutorials/image/cifar10_estimator/cifar10_main.py

@@ -72,9 +72,9 @@ tf.flags.DEFINE_float('weight_decay', 1e-4, 'Weight decay for convolutions.')
 tf.flags.DEFINE_boolean('use_distortion_for_training', True,
                         'If doing image distortion for training.')
 tf.flags.DEFINE_boolean('run_experiment', False,
-                        "If True will run an experiment,"
-                        "otherwise will run training and evaluation"
-                        "using the estimator interface")
+                        'If True will run an experiment,'
+                        'otherwise will run training and evaluation'
+                        'using the estimator interface')
 
 # Perf flags
 tf.flags.DEFINE_integer('num_intra_threads', 1,
@@ -363,9 +363,11 @@ def input_fn(subset, num_shards):
     label_shards = [tf.parallel_stack(x) for x in label_shards]
     return feature_shards, label_shards
 
+
 # create experiment
 def get_experiment_fn(train_input_fn, eval_input_fn, train_steps, eval_steps):
   def _experiment_fn(run_config, hparams):
+    del hparams  # unused arg
     # create estimator
     classifier = tf.estimator.Estimator(model_fn=_resnet_model_fn,
                                         config=run_config)
@@ -413,7 +415,7 @@ def main(unused_argv):
                                      num_shards=FLAGS.num_gpus)
 
   eval_input_fn = functools.partial(input_fn, subset='eval',
-                                   num_shards=FLAGS.num_gpus)
+                                    num_shards=FLAGS.num_gpus)
 
   train_steps = FLAGS.train_steps
   eval_steps = num_eval_examples // FLAGS.eval_batch_size