Merge changes from github.

Revert #18413. Too many internal test failures due to the name scope change caused by this change.
Revert #18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change.

PiperOrigin-RevId: 197991247

1 files changed, 3 insertions, 3 deletions

diff --git a/tensorflow/python/feature_column/feature_column.py b/tensorflow/python/feature_column/feature_column.py
index ede6e0d159..ffcb9990d5 100644
--- a/tensorflow/python/feature_column/feature_column.py
+++ b/tensorflow/python/feature_column/feature_column.py
@@ -48,7 +48,7 @@ should choose depends on (1) the feature type and (2) the model type.
 
       embedded_dept_column = embedding_column(
           categorical_column_with_vocabulary_list(
-              "department", ["math", "philosphy", ...]), dimension=10)
+              "department", ["math", "philosophy", ...]), dimension=10)
 
   * Wide (aka linear) models (`LinearClassifier`, `LinearRegressor`).
 
@@ -280,7 +280,7 @@ def input_layer(features,
 # TODO(akshayka): InputLayer should be a subclass of Layer, and it
 # should implement the logic in input_layer using Layer's build-and-call
 # paradigm; input_layer should create an instance of InputLayer and
-# return the result of inovking its apply method, just as functional layers do.
+# return the result of invoking its apply method, just as functional layers do.
 class InputLayer(object):
   """An object-oriented version of `input_layer` that reuses variables."""
 
@@ -834,7 +834,7 @@ def shared_embedding_columns(
     tensor_name_in_ckpt=None, max_norm=None, trainable=True):
   """List of dense columns that convert from sparse, categorical input.
 
-  This is similar to `embedding_column`, except that that it produces a list of
+  This is similar to `embedding_column`, except that it produces a list of
   embedding columns that share the same embedding weights.
 
   Use this when your inputs are sparse and of the same type (e.g. watched and