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-rw-r--r--tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py8
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py b/tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py
index 02acd70812..9cb4c3515a 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/state_saving_rnn_estimator.py
@@ -144,7 +144,7 @@ def _prepare_features_for_sqss(features, labels, mode,
describing sequence features. All items in the set should be instances
of classes derived from `FeatureColumn`.
context_feature_columns: An iterable containing all the feature columns
- describing context features, i.e., features that apply accross all time
+ describing context features, i.e., features that apply across all time
steps. All items in the set should be instances of classes derived from
`FeatureColumn`.
@@ -261,7 +261,7 @@ def _read_batch(cell,
describing sequence features. All items in the set should be instances
of classes derived from `FeatureColumn`.
context_feature_columns: An iterable containing all the feature columns
- describing context features, i.e., features that apply accross all time
+ describing context features, i.e., features that apply across all time
steps. All items in the set should be instances of classes derived from
`FeatureColumn`.
num_threads: The Python integer number of threads enqueuing input examples
@@ -420,7 +420,7 @@ def _get_rnn_model_fn(cell_type,
describing sequence features. All items in the set should be instances
of classes derived from `FeatureColumn`.
context_feature_columns: An iterable containing all the feature columns
- describing context features, i.e., features that apply accross all time
+ describing context features, i.e., features that apply across all time
steps. All items in the set should be instances of classes derived from
`FeatureColumn`.
predict_probabilities: A boolean indicating whether to predict probabilities
@@ -563,7 +563,7 @@ class StateSavingRnnEstimator(estimator.Estimator):
describing sequence features. All items in the set should be instances
of classes derived from `FeatureColumn`.
context_feature_columns: An iterable containing all the feature columns
- describing context features, i.e., features that apply accross all time
+ describing context features, i.e., features that apply across all time
steps. All items in the set should be instances of classes derived from
`FeatureColumn`.
num_classes: The number of classes for categorization. Used only and