V1 optimizer fix (#6350)

* optimizer back to compat.v1

* add doc string to fix lint

official/resnet/resnet_run_loop.py

@@ -266,8 +266,6 @@ def learning_rate_with_decay(
                      false_fn=lambda: lr)
     return lr
 
-
-
   def poly_rate_fn(global_step):
     """Handles linear scaling rule, gradual warmup, and LR decay.
 
@@ -277,10 +275,10 @@ def learning_rate_with_decay(
     decay schedule with power 2.0.
 
     Args:
-    global_step: the current global_step
+      global_step: the current global_step
 
     Returns:
-    returns the current learning rate
+      returns the current learning rate
     """
 
     # Learning rate schedule for LARS polynomial schedule
@@ -318,7 +316,6 @@ def learning_rate_with_decay(
   if flags.FLAGS.enable_lars:
     return poly_rate_fn
 
-
   return learning_rate_fn
 
 
@@ -360,6 +357,7 @@ def resnet_model_fn(features, labels, mode, model_class,
       from the loss.
     dtype: the TensorFlow dtype to use for calculations.
     fine_tune: If True only train the dense layers(final layers).
+    label_smoothing: If greater than 0 then smooth the labels.
 
   Returns:
     EstimatorSpec parameterized according to the input params and the
@@ -402,7 +400,7 @@ def resnet_model_fn(features, labels, mode, model_class,
         logits=logits, onehot_labels=one_hot_labels,
         label_smoothing=label_smoothing)
   else:
-    cross_entropy = tf.losses.sparse_softmax_cross_entropy(
+    cross_entropy = tf.compat.v1.losses.sparse_softmax_cross_entropy(
         logits=logits, labels=labels)
 
   # Create a tensor named cross_entropy for logging purposes.