diff options
Diffstat (limited to 'tensorflow/contrib/learn/python/learn/estimators/dnn.py')
| -rw-r--r-- | tensorflow/contrib/learn/python/learn/estimators/dnn.py | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/tensorflow/contrib/learn/python/learn/estimators/dnn.py b/tensorflow/contrib/learn/python/learn/estimators/dnn.py index cb1fd39e03..91eb3a57ac 100644 --- a/tensorflow/contrib/learn/python/learn/estimators/dnn.py +++ b/tensorflow/contrib/learn/python/learn/estimators/dnn.py @@ -119,7 +119,9 @@ class DNNClassifier(dnn_linear_combined.DNNLinearCombinedClassifier): feature_columns: An iterable containing all the feature columns used by 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. + 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 continue + training a previously saved model. n_classes: number of target classes. Default is binary classification. It must be greater than 1. weight_column_name: A string defining feature column name representing @@ -277,7 +279,9 @@ class DNNRegressor(dnn_linear_combined.DNNLinearCombinedRegressor): feature_columns: An iterable containing all the feature columns used by 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. + 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 continue + training a previously saved model. weight_column_name: A string defining feature column name representing weights. It is used to down weight or boost examples during training. It will be multiplied by the loss of the example. |