1 files changed, 69 insertions, 69 deletions
diff --git a/tensorflow/docs_src/api_guides/python/train.md b/tensorflow/docs_src/api_guides/python/train.md
index cbc5052946..a118123665 100644
--- a/tensorflow/docs_src/api_guides/python/train.md
+++ b/tensorflow/docs_src/api_guides/python/train.md
@@ -1,7 +1,7 @@
 # Training
 [TOC]
 
-@{tf.train} provides a set of classes and functions that help train models.
+`tf.train` provides a set of classes and functions that help train models.
 
 ## Optimizers
 
@@ -12,19 +12,19 @@ optimization algorithms such as GradientDescent and Adagrad.
 You never instantiate the Optimizer class itself, but instead instantiate one
 of the subclasses.
 
-*   @{tf.train.Optimizer}
-*   @{tf.train.GradientDescentOptimizer}
-*   @{tf.train.AdadeltaOptimizer}
-*   @{tf.train.AdagradOptimizer}
-*   @{tf.train.AdagradDAOptimizer}
-*   @{tf.train.MomentumOptimizer}
-*   @{tf.train.AdamOptimizer}
-*   @{tf.train.FtrlOptimizer}
-*   @{tf.train.ProximalGradientDescentOptimizer}
-*   @{tf.train.ProximalAdagradOptimizer}
-*   @{tf.train.RMSPropOptimizer}
+*   `tf.train.Optimizer`
+*   `tf.train.GradientDescentOptimizer`
+*   `tf.train.AdadeltaOptimizer`
+*   `tf.train.AdagradOptimizer`
+*   `tf.train.AdagradDAOptimizer`
+*   `tf.train.MomentumOptimizer`
+*   `tf.train.AdamOptimizer`
+*   `tf.train.FtrlOptimizer`
+*   `tf.train.ProximalGradientDescentOptimizer`
+*   `tf.train.ProximalAdagradOptimizer`
+*   `tf.train.RMSPropOptimizer`
 
-See @{tf.contrib.opt} for more optimizers.
+See `tf.contrib.opt` for more optimizers.
 
 ## Gradient Computation
 
@@ -34,10 +34,10 @@ optimizer classes automatically compute derivatives on your graph, but
 creators of new Optimizers or expert users can call the lower-level
 functions below.
 
-*   @{tf.gradients}
-*   @{tf.AggregationMethod}
-*   @{tf.stop_gradient}
-*   @{tf.hessians}
+*   `tf.gradients`
+*   `tf.AggregationMethod`
+*   `tf.stop_gradient`
+*   `tf.hessians`
 
 
 ## Gradient Clipping
@@ -47,22 +47,22 @@ functions to your graph. You can use these functions to perform general data
 clipping, but they're particularly useful for handling exploding or vanishing
 gradients.
 
-*   @{tf.clip_by_value}
-*   @{tf.clip_by_norm}
-*   @{tf.clip_by_average_norm}
-*   @{tf.clip_by_global_norm}
-*   @{tf.global_norm}
+*   `tf.clip_by_value`
+*   `tf.clip_by_norm`
+*   `tf.clip_by_average_norm`
+*   `tf.clip_by_global_norm`
+*   `tf.global_norm`
 
 ## Decaying the learning rate
 
-*   @{tf.train.exponential_decay}
-*   @{tf.train.inverse_time_decay}
-*   @{tf.train.natural_exp_decay}
-*   @{tf.train.piecewise_constant}
-*   @{tf.train.polynomial_decay}
-*   @{tf.train.cosine_decay}
-*   @{tf.train.linear_cosine_decay}
-*   @{tf.train.noisy_linear_cosine_decay}
+*   `tf.train.exponential_decay`
+*   `tf.train.inverse_time_decay`
+*   `tf.train.natural_exp_decay`
+*   `tf.train.piecewise_constant`
+*   `tf.train.polynomial_decay`
+*   `tf.train.cosine_decay`
+*   `tf.train.linear_cosine_decay`
+*   `tf.train.noisy_linear_cosine_decay`
 
 ## Moving Averages
 
@@ -70,7 +70,7 @@ Some training algorithms, such as GradientDescent and Momentum often benefit
 from maintaining a moving average of variables during optimization.  Using the
 moving averages for evaluations often improve results significantly.
 
-*   @{tf.train.ExponentialMovingAverage}
+*   `tf.train.ExponentialMovingAverage`
 
 ## Coordinator and QueueRunner
 
@@ -79,61 +79,61 @@ for how to use threads and queues.  For documentation on the Queue API,
 see @{$python/io_ops#queues$Queues}.
 
 
-*   @{tf.train.Coordinator}
-*   @{tf.train.QueueRunner}
-*   @{tf.train.LooperThread}
-*   @{tf.train.add_queue_runner}
-*   @{tf.train.start_queue_runners}
+*   `tf.train.Coordinator`
+*   `tf.train.QueueRunner`
+*   `tf.train.LooperThread`
+*   `tf.train.add_queue_runner`
+*   `tf.train.start_queue_runners`
 
 ## Distributed execution
 
 See @{$distributed$Distributed TensorFlow} for
 more information about how to configure a distributed TensorFlow program.
 
-*   @{tf.train.Server}
-*   @{tf.train.Supervisor}
-*   @{tf.train.SessionManager}
-*   @{tf.train.ClusterSpec}
-*   @{tf.train.replica_device_setter}
-*   @{tf.train.MonitoredTrainingSession}
-*   @{tf.train.MonitoredSession}
-*   @{tf.train.SingularMonitoredSession}
-*   @{tf.train.Scaffold}
-*   @{tf.train.SessionCreator}
-*   @{tf.train.ChiefSessionCreator}
-*   @{tf.train.WorkerSessionCreator}
+*   `tf.train.Server`
+*   `tf.train.Supervisor`
+*   `tf.train.SessionManager`
+*   `tf.train.ClusterSpec`
+*   `tf.train.replica_device_setter`
+*   `tf.train.MonitoredTrainingSession`
+*   `tf.train.MonitoredSession`
+*   `tf.train.SingularMonitoredSession`
+*   `tf.train.Scaffold`
+*   `tf.train.SessionCreator`
+*   `tf.train.ChiefSessionCreator`
+*   `tf.train.WorkerSessionCreator`
 
 ## Reading Summaries from Event Files
 
 See @{$summaries_and_tensorboard$Summaries and TensorBoard} for an
 overview of summaries, event files, and visualization in TensorBoard.
 
-*   @{tf.train.summary_iterator}
+*   `tf.train.summary_iterator`
 
 ## Training Hooks
 
 Hooks are tools that run in the process of training/evaluation of the model.
 
-*   @{tf.train.SessionRunHook}
-*   @{tf.train.SessionRunArgs}
-*   @{tf.train.SessionRunContext}
-*   @{tf.train.SessionRunValues}
-*   @{tf.train.LoggingTensorHook}
-*   @{tf.train.StopAtStepHook}
-*   @{tf.train.CheckpointSaverHook}
-*   @{tf.train.NewCheckpointReader}
-*   @{tf.train.StepCounterHook}
-*   @{tf.train.NanLossDuringTrainingError}
-*   @{tf.train.NanTensorHook}
-*   @{tf.train.SummarySaverHook}
-*   @{tf.train.GlobalStepWaiterHook}
-*   @{tf.train.FinalOpsHook}
-*   @{tf.train.FeedFnHook}
+*   `tf.train.SessionRunHook`
+*   `tf.train.SessionRunArgs`
+*   `tf.train.SessionRunContext`
+*   `tf.train.SessionRunValues`
+*   `tf.train.LoggingTensorHook`
+*   `tf.train.StopAtStepHook`
+*   `tf.train.CheckpointSaverHook`
+*   `tf.train.NewCheckpointReader`
+*   `tf.train.StepCounterHook`
+*   `tf.train.NanLossDuringTrainingError`
+*   `tf.train.NanTensorHook`
+*   `tf.train.SummarySaverHook`
+*   `tf.train.GlobalStepWaiterHook`
+*   `tf.train.FinalOpsHook`
+*   `tf.train.FeedFnHook`
 
 ## Training Utilities
 
-*   @{tf.train.global_step}
-*   @{tf.train.basic_train_loop}
-*   @{tf.train.get_global_step}
-*   @{tf.train.assert_global_step}
-*   @{tf.train.write_graph}
+*   `tf.train.global_step`
+*   `tf.train.basic_train_loop`
+*   `tf.train.get_global_step`
+*   `tf.train.assert_global_step`
+*   `tf.train.write_graph`