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authorGravatar YongJoon Lee <joon0351@gmail.com>2018-10-03 16:43:55 +0900
committerGravatar YongJoon Lee <joon0351@gmail.com>2018-10-03 16:43:55 +0900
commit946e58e402778606d26056f5decf91ecfb4a9f89 (patch)
treefec37ef8a09614d24ee95e1cb53c37b661fd3c73 /tensorflow/contrib/estimator
parent9f42ebd5982688511ecc0ef7d23de02b64d8dd1e (diff)
fix spelling problem
Diffstat (limited to 'tensorflow/contrib/estimator')
-rw-r--r--tensorflow/contrib/estimator/python/estimator/boosted_trees.py6
-rw-r--r--tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py2
-rw-r--r--tensorflow/contrib/estimator/python/estimator/dnn_with_layer_annotations.py2
3 files changed, 5 insertions, 5 deletions
diff --git a/tensorflow/contrib/estimator/python/estimator/boosted_trees.py b/tensorflow/contrib/estimator/python/estimator/boosted_trees.py
index a1f1c5f3d7..b131ed4f12 100644
--- a/tensorflow/contrib/estimator/python/estimator/boosted_trees.py
+++ b/tensorflow/contrib/estimator/python/estimator/boosted_trees.py
@@ -75,7 +75,7 @@ class _BoostedTreesEstimator(canned_boosted_trees._BoostedTreesBase): # pylint:
layer.
head: the `Head` instance defined for Estimator.
model_dir: Directory to save model parameters, graph and etc. This can
- also be used to load checkpoints from the directory into a estimator
+ also be used to load checkpoints from the directory into an estimator
to continue training a previously saved model.
weight_column: A string or a `_NumericColumn` created by
`tf.feature_column.numeric_column` defining feature column representing
@@ -199,7 +199,7 @@ def boosted_trees_classifier_train_in_memory(
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
- also be used to load checkpoints from the directory into a estimator
+ also be used to load checkpoints from the directory into an estimator
to continue training a previously saved model.
n_classes: number of label classes. Default is binary classification.
Multiclass support is not yet implemented.
@@ -345,7 +345,7 @@ def boosted_trees_regressor_train_in_memory(
the model. All items in the set should be instances of classes derived
from `FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can
- also be used to load checkpoints from the directory into a estimator
+ also be used to load checkpoints from the directory into an estimator
to continue training a previously saved model.
label_dimension: Number of regression targets per example.
Multi-dimensional support is not yet implemented.
diff --git a/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py b/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
index 724bc2c82f..4e7965ef26 100644
--- a/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
+++ b/tensorflow/contrib/estimator/python/estimator/dnn_linear_combined.py
@@ -118,7 +118,7 @@ class DNNLinearCombinedEstimator(estimator.Estimator):
head: A `_Head` instance constructed with a method such as
`tf.contrib.estimator.multi_label_head`.
model_dir: Directory to save model parameters, graph and etc. This can
- also be used to load checkpoints from the directory into a estimator
+ also be used to load checkpoints from the directory into an estimator
to continue training a previously saved model.
linear_feature_columns: An iterable containing all the feature columns
used by linear part of the model. All items in the set must be
diff --git a/tensorflow/contrib/estimator/python/estimator/dnn_with_layer_annotations.py b/tensorflow/contrib/estimator/python/estimator/dnn_with_layer_annotations.py
index 6ca7aaf989..40a91175b7 100644
--- a/tensorflow/contrib/estimator/python/estimator/dnn_with_layer_annotations.py
+++ b/tensorflow/contrib/estimator/python/estimator/dnn_with_layer_annotations.py
@@ -248,7 +248,7 @@ def DNNClassifierWithLayerAnnotations( # pylint: disable=invalid-name
model. All items in the set should be instances of classes derived from
`_FeatureColumn`.
model_dir: Directory to save model parameters, graph and etc. This can also
- be used to load checkpoints from the directory into a estimator to
+ be used to load checkpoints from the directory into an estimator to
continue training a previously saved model.
n_classes: Number of label classes. Defaults to 2, namely binary
classification. Must be > 1.