diff --git a/research/slim/deployment/model_deploy.py b/research/slim/deployment/model_deploy.py
index a12455784a8e2e461c736ad60fc85be867dac959..c6820769dcb60a70436b706c176749e2a64d706b 100644
--- a/research/slim/deployment/model_deploy.py
+++ b/research/slim/deployment/model_deploy.py
@@ -103,8 +103,6 @@ import collections
 
 import tensorflow as tf
 
-from tensorflow.python.eager import context
-
 slim = tf.contrib.slim
 
 
@@ -344,13 +342,7 @@ def deploy(config,
   Returns:
     A `DeployedModel` namedtuple.
 
-  Raises:
-    RuntimeError: If eager execution is enabled.
   """
-  if context.in_eager_mode():
-    raise RuntimeError(
-        'slim.deploy is not supported when eager execution is enabled.')
-
   # Gather initial summaries.
   summaries = set(tf.get_collection(tf.GraphKeys.SUMMARIES))
 
diff --git a/research/slim/nets/nasnet/README.md b/research/slim/nets/nasnet/README.md
index ea9e88c2a27c20f79baa3a632ceefd1a1695b25d..98dd02ba26f790a26408f0c702c3146737286689 100644
--- a/research/slim/nets/nasnet/README.md
+++ b/research/slim/nets/nasnet/README.md
@@ -29,7 +29,7 @@ More information on integrating NASNet Models into your project can be found at
 
 To get started running models on-device go to [TensorFlow Mobile](https://www.tensorflow.org/mobile/).
 
-###Sample Commands for using NASNet-A Mobile and Large Checkpoints for Inference
+## Sample Commands for using NASNet-A Mobile and Large Checkpoints for Inference
 -------
 Run eval with the NASNet-A mobile ImageNet model
 
@@ -45,7 +45,7 @@ python tensorflow_models/research/slim/eval_image_classifier \
 --dataset_split_name=validation \
 --model_name=nasnet_mobile \
 --eval_image_size=224 \
---moving_average_decay=0.9999 \
+--moving_average_decay=0.9999
 ```
 
 Run eval with the NASNet-A large ImageNet model
@@ -62,5 +62,5 @@ python tensorflow_models/research/slim/eval_image_classifier \
 --dataset_split_name=validation \
 --model_name=nasnet_large \
 --eval_image_size=331 \
---moving_average_decay=0.9999 \
+--moving_average_decay=0.9999
 ```