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-rw-r--r--tensorflow/contrib/factorization/python/ops/factorization_ops_test.py12
1 files changed, 6 insertions, 6 deletions
diff --git a/tensorflow/contrib/factorization/python/ops/factorization_ops_test.py b/tensorflow/contrib/factorization/python/ops/factorization_ops_test.py
index c813733915..bb5140aeb3 100644
--- a/tensorflow/contrib/factorization/python/ops/factorization_ops_test.py
+++ b/tensorflow/contrib/factorization/python/ops/factorization_ops_test.py
@@ -210,7 +210,7 @@ class WalsModelTest(test.TestCase):
# Test row projection.
# Using the specified projection weights for the 2 row feature vectors.
- # This is expected to reprodue the same row factors in the model as the
+ # This is expected to reproduce the same row factors in the model as the
# weights and feature vectors are identical to that used in model
# training.
projected_rows = wals_model.project_row_factors(
@@ -283,8 +283,8 @@ class WalsModelTest(test.TestCase):
# Test column projection.
# Using the specified projection weights for the 3 column feature vectors.
- # This is expected to reprodue the same column factors in the model as the
- # weights and feature vectors are identical to that used in model
+ # This is expected to reproduce the same column factors in the model as
+ # the weights and feature vectors are identical to that used in model
# training.
projected_cols = wals_model.project_col_factors(
sp_input=sp_feeder,
@@ -385,7 +385,7 @@ class WalsModelTest(test.TestCase):
# Test row projection.
# Using the specified projection weights for the 2 row feature vectors.
- # This is expected to reprodue the same row factors in the model as the
+ # This is expected to reproduce the same row factors in the model as the
# weights and feature vectors are identical to that used in model
# training.
projected_rows = wals_model.project_row_factors(
@@ -462,8 +462,8 @@ class WalsModelTest(test.TestCase):
# Test column projection.
# Using the specified projection weights for the 2 column feature vectors.
- # This is expected to reprodue the same column factors in the model as the
- # weights and feature vectors are identical to that used in model
+ # This is expected to reproduce the same column factors in the model as
+ # the weights and feature vectors are identical to that used in model
# training.
projected_cols = wals_model.project_col_factors(
sp_input=sp_feeder,