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

3 files changed, 7 insertions, 7 deletions

diff --git a/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py b/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
index 2eef60c39f..724bc2c82f 100644
--- a/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
+++ b/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
@@ -147,7 +147,7 @@ class DNNLinearCombinedEstimator(estimator.Estimator):
         if a categorical column is multivalent.  One of "mean", "sqrtn", and
         "sum" -- these are effectively different ways to do example-level
         normalization, which can be useful for bag-of-words features.  For more
-        details, see @{tf.feature_column.linear_model$linear_model}.
+        details, see `tf.feature_column.linear_model`.
 
     Raises:
       ValueError: If both linear_feature_columns and dnn_features_columns are
diff --git a/tensorflow/contrib/estimator/python/estimator/extenders.py b/tensorflow/contrib/estimator/python/estimator/extenders.py
index bf08be09e7..26449b4651 100644
--- a/tensorflow/contrib/estimator/python/estimator/extenders.py
+++ b/tensorflow/contrib/estimator/python/estimator/extenders.py
@@ -34,7 +34,7 @@ _VALID_METRIC_FN_ARGS = set(['features', 'labels', 'predictions', 'config'])
 
 
 def add_metrics(estimator, metric_fn):
-  """Creates a new @{tf.estimator.Estimator} which has given metrics.
+  """Creates a new `tf.estimator.Estimator` which has given metrics.
 
   Example:
 
@@ -61,7 +61,7 @@ def add_metrics(estimator, metric_fn):
   ```
 
   Args:
-    estimator: A @{tf.estimator.Estimator} object.
+    estimator: A `tf.estimator.Estimator` object.
     metric_fn: A function which should obey the following signature:
       - Args: can only have following four arguments in any order:
         * predictions: Predictions `Tensor` or dict of `Tensor` created by given
@@ -79,7 +79,7 @@ def add_metrics(estimator, metric_fn):
          function, namely a `(metric_tensor, update_op)` tuple.
 
   Returns:
-      A new @{tf.estimator.Estimator} which has a union of original metrics with
+      A new `tf.estimator.Estimator` which has a union of original metrics with
         given ones.
   """
   _verify_metric_fn_args(metric_fn)
@@ -165,14 +165,14 @@ def forward_features(estimator, keys=None):
   ```
 
   Args:
-    estimator: A @{tf.estimator.Estimator} object.
+    estimator: A `tf.estimator.Estimator` object.
     keys: a `string` or a `list` of `string`. If it is `None`, all of the
       `features` in `dict` is forwarded to the `predictions`. If it is a
       `string`, only given key is forwarded. If it is a `list` of strings, all
       the given `keys` are forwarded.
 
   Returns:
-      A new @{tf.estimator.Estimator} which forwards features to predictions.
+      A new `tf.estimator.Estimator` which forwards features to predictions.
 
   Raises:
     ValueError:
diff --git a/tensorflow/contrib/estimator/python/estimator/linear.py b/tensorflow/contrib/estimator/python/estimator/linear.py
index 62a37abefb..2b68f24eb2 100644
--- a/tensorflow/contrib/estimator/python/estimator/linear.py
+++ b/tensorflow/contrib/estimator/python/estimator/linear.py
@@ -121,7 +121,7 @@ class LinearEstimator(estimator.Estimator):
         is multivalent.  One of "mean", "sqrtn", and "sum" -- these are
         effectively different ways to do example-level normalization, which can
         be useful for bag-of-words features. for more details, see
-        @{tf.feature_column.linear_model$linear_model}.
+        `tf.feature_column.linear_model`.
     """
     def _model_fn(features, labels, mode, config):
       return linear_lib._linear_model_fn(  # pylint: disable=protected-access