Remove usage of magic-api-link syntax from source files.

Back-ticks are now converted to links in the api_docs generator. With the new docs repo we're moving to simplify the docs pipeline, and make everything more readable.

By doing this we no longer get test failures for symbols that don't exist (`tf.does_not_exist`  will not get a link).

There is also no way, not to set custom link text. That's okay.

This is the result of the following regex replacement (+ a couple of manual edits.):

re: @\{([^$].*?)(\$.+?)?}
sub: `\1`

Which does the following replacements:

"@{tf.symbol}" --> "`tf.symbol`"
"@{tf.symbol$link_text}" --> "`tf.symbol`"

PiperOrigin-RevId: 208042358

4 files changed, 12 insertions, 12 deletions

diff --git a/tensorflow/contrib/learn/python/learn/estimators/kmeans.py b/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
index 66ebcfd1d8..21f7dcc5e4 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/kmeans.py
@@ -15,9 +15,9 @@
 """Implementation of k-means clustering on top of `Estimator` API (deprecated).
 
 This module is deprecated. Please use
-@{tf.contrib.factorization.KMeansClustering} instead of
-@{tf.contrib.learn.KMeansClustering}. It has a similar interface, but uses the
-@{tf.estimator.Estimator} API instead of @{tf.contrib.learn.Estimator}.
+`tf.contrib.factorization.KMeansClustering` instead of
+`tf.contrib.learn.KMeansClustering`. It has a similar interface, but uses the
+`tf.estimator.Estimator` API instead of `tf.contrib.learn.Estimator`.
 """
 
 from __future__ import absolute_import
diff --git a/tensorflow/contrib/learn/python/learn/estimators/run_config.py b/tensorflow/contrib/learn/python/learn/estimators/run_config.py
index c36879e048..08f23aa223 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/run_config.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/run_config.py
@@ -221,7 +221,7 @@ class ClusterConfig(object):
 class RunConfig(ClusterConfig, core_run_config.RunConfig):
   """This class specifies the configurations for an `Estimator` run.
 
-  This class is a deprecated implementation of @{tf.estimator.RunConfig}
+  This class is a deprecated implementation of `tf.estimator.RunConfig`
   interface.
   """
   _USE_DEFAULT = 0
diff --git a/tensorflow/contrib/learn/python/learn/experiment.py b/tensorflow/contrib/learn/python/learn/experiment.py
index 08e907a608..4e64efdd95 100644
--- a/tensorflow/contrib/learn/python/learn/experiment.py
+++ b/tensorflow/contrib/learn/python/learn/experiment.py
@@ -162,16 +162,16 @@ class Experiment(object):
 
     Args:
       estimator: Object implementing Estimator interface, which could be a
-        combination of @{tf.contrib.learn.Trainable} and
-        @{tf.contrib.learn.Evaluable} (deprecated), or
-        @{tf.estimator.Estimator}.
+        combination of `tf.contrib.learn.Trainable` and
+        `tf.contrib.learn.Evaluable` (deprecated), or
+        `tf.estimator.Estimator`.
       train_input_fn: function, returns features and labels for training.
       eval_input_fn: function, returns features and labels for evaluation. If
         `eval_steps` is `None`, this should be configured only to produce for a
         finite number of batches (generally, 1 epoch over the evaluation data).
       eval_metrics: `dict` of string, metric function. If `None`, default set
         is used. This should be `None` if the `estimator` is
-        @{tf.estimator.Estimator}. If metrics are provided they will be
+        `tf.estimator.Estimator`. If metrics are provided they will be
         *appended* to the default set.
       train_steps: Perform this many steps of training. `None`, the default,
         means train forever.
diff --git a/tensorflow/contrib/learn/python/learn/utils/saved_model_export_utils.py b/tensorflow/contrib/learn/python/learn/utils/saved_model_export_utils.py
index 66af6833da..4f22054af3 100644
--- a/tensorflow/contrib/learn/python/learn/utils/saved_model_export_utils.py
+++ b/tensorflow/contrib/learn/python/learn/utils/saved_model_export_utils.py
@@ -415,7 +415,7 @@ def make_export_strategy(serving_input_fn,
       `InputFnOps`.
     default_output_alternative_key: the name of the head to serve when an
       incoming serving request does not explicitly request a specific head.
-      Must be `None` if the estimator inherits from @{tf.estimator.Estimator}
+      Must be `None` if the estimator inherits from `tf.estimator.Estimator`
       or for single-headed models.
     assets_extra: A dict specifying how to populate the assets.extra directory
       within the exported SavedModel.  Each key should give the destination
@@ -453,7 +453,7 @@ def make_export_strategy(serving_input_fn,
       The string path to the exported directory.
 
     Raises:
-      ValueError: If `estimator` is a @{tf.estimator.Estimator} instance
+      ValueError: If `estimator` is a `tf.estimator.Estimator` instance
         and `default_output_alternative_key` was specified.
     """
     if isinstance(estimator, core_estimator.Estimator):
@@ -504,7 +504,7 @@ def make_parsing_export_strategy(feature_columns,
       that must be provided at serving time (excluding labels!).
     default_output_alternative_key: the name of the head to serve when an
       incoming serving request does not explicitly request a specific head.
-      Must be `None` if the estimator inherits from @{tf.estimator.Estimator}
+      Must be `None` if the estimator inherits from `tf.estimator.Estimator`
       or for single-headed models.
     assets_extra: A dict specifying how to populate the assets.extra directory
       within the exported SavedModel.  Each key should give the destination
@@ -767,7 +767,7 @@ def extend_export_strategy(base_export_strategy,
       The string path to the SavedModel indicated by post_export_fn.
 
     Raises:
-      ValueError: If `estimator` is a @{tf.estimator.Estimator} instance
+      ValueError: If `estimator` is a `tf.estimator.Estimator` instance
         and `default_output_alternative_key` was specified or if post_export_fn
         does not return a valid directory.
       RuntimeError: If unable to create temporary or final export directory.