diff options
Diffstat (limited to 'tensorflow/contrib/factorization/python/ops/factorization_ops_test.py')
-rw-r--r-- | tensorflow/contrib/factorization/python/ops/factorization_ops_test.py | 12 |
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, |