contrib: minor spelling tweaks (#18330)

* contrib: minor spelling tweaks

* Fix lint error

4 files changed, 6 insertions, 6 deletions

diff --git a/tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py b/tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py
index f701647c2b..28ddaa69a1 100644
--- a/tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py
+++ b/tensorflow/contrib/layers/python/kernel_tests/sparse_feature_cross_op_test.py
@@ -200,7 +200,7 @@ class SparseCrossOpTest(test.TestCase):
       self._assert_sparse_tensor_equals(expected_out, sess.run(op))
 
   def test_large_batch(self):
-    """Tests with large batch size to force multithreding.
+    """Tests with large batch size to force multithreading.
     """
     batch_size = 5000
     col1 = []
diff --git a/tensorflow/contrib/layers/python/layers/feature_column.py b/tensorflow/contrib/layers/python/layers/feature_column.py
index 9ccb589d69..3ae07cedab 100644
--- a/tensorflow/contrib/layers/python/layers/feature_column.py
+++ b/tensorflow/contrib/layers/python/layers/feature_column.py
@@ -48,7 +48,7 @@ you should choose depends on (1) the feature type and (2) the model type.
    recommended.
 
      embedded_dept_column = embedding_column(
-       sparse_column_with_keys("department", ["math", "philosphy", ...]),
+       sparse_column_with_keys("department", ["math", "philosophy", ...]),
        dimension=10)
 
 * Wide (aka linear) models (`LinearClassifier`, `LinearRegressor`).
diff --git a/tensorflow/contrib/layers/python/layers/feature_column_ops.py b/tensorflow/contrib/layers/python/layers/feature_column_ops.py
index 78affea44c..06060b99e7 100644
--- a/tensorflow/contrib/layers/python/layers/feature_column_ops.py
+++ b/tensorflow/contrib/layers/python/layers/feature_column_ops.py
@@ -815,7 +815,7 @@ class _Transformer(object):
   """
 
   def __init__(self, columns_to_tensors):
-    """Initializes transfomer.
+    """Initializes transformer.
 
     Args:
       columns_to_tensors: A mapping from feature columns to tensors. 'string'
@@ -908,7 +908,7 @@ def _gather_feature_columns(feature_columns):
 
 
 def _check_forbidden_sequence_columns(feature_columns):
-  """Recursively cecks `feature_columns` for `_FORBIDDEN_SEQUENCE_COLUMNS`."""
+  """Recursively checks `feature_columns` for `_FORBIDDEN_SEQUENCE_COLUMNS`."""
   all_feature_columns = _gather_feature_columns(feature_columns)
   for feature_column in all_feature_columns:
     if isinstance(feature_column, _FORBIDDEN_SEQUENCE_COLUMNS):
diff --git a/tensorflow/contrib/layers/python/layers/layers.py b/tensorflow/contrib/layers/python/layers/layers.py
index 949e73deff..151fc7a0d7 100644
--- a/tensorflow/contrib/layers/python/layers/layers.py
+++ b/tensorflow/contrib/layers/python/layers/layers.py
@@ -1542,7 +1542,7 @@ def dense_to_sparse(tensor, eos_token=0, outputs_collections=None, scope=None):
   Args:
      tensor: An `int` `Tensor` to be converted to a `Sparse`.
      eos_token: An integer.
-       It is part of the target label that signfies the end of a sentence.
+       It is part of the target label that signifies the end of a sentence.
      outputs_collections: Collection to add the outputs.
      scope: Optional scope for name_scope.
   """
@@ -1686,7 +1686,7 @@ def _inner_flatten(inputs, new_rank, output_collections=None, scope=None):
     output_collections: Collection to which the outputs will be added.
     scope: Optional scope for `name_scope`.
   Returns:
-    A `Tensor` or `SparseTensor` conataining the same values as `inputs`, but
+    A `Tensor` or `SparseTensor` containing the same values as `inputs`, but
     with innermost dimensions flattened to obtain rank `new_rank`.
 
   Raises: