experiments/STT-tensorflow
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Fixes a bug in setting default optimizers for DNNLinearCombinedClassifier.

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PiperOrigin-RevId: 158190192
This commit is contained in:
A. Unique TensorFlower 2017-06-06 14:27:21 -07:00 committed by TensorFlower Gardener
parent 3ca6533049
commit a4e7b7add4
1 changed files with 4 additions and 4 deletions

8
tensorflow/python/estimator/canned/dnn_linear_combined.py
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@ -300,9 +300,9 @@ class DNNLinearCombinedClassifier(estimator.Estimator):
def __init__(self,
model_dir=None,
linear_feature_columns=None,
linear_optimizer=None,
linear_optimizer='Ftrl',
dnn_feature_columns=None,
dnn_optimizer=None,
dnn_optimizer='Adagrad',
dnn_hidden_units=None,
dnn_activation_fn=nn.relu,
dnn_dropout=None,
@ -319,12 +319,12 @@ class DNNLinearCombinedClassifier(estimator.Estimator):
used by linear part of the model. All items in the set must be
instances of classes derived from `FeatureColumn`.
linear_optimizer: An instance of `tf.Optimizer` used to apply gradients to
the linear part of the model. If `None`, will use a FTRL optimizer.
the linear part of the model. Defaults to FTRL optimizer.
dnn_feature_columns: An iterable containing all the feature columns used
by deep part of the model. All items in the set must be instances of
classes derived from `FeatureColumn`.
dnn_optimizer: An instance of `tf.Optimizer` used to apply gradients to
the deep part of the model. If `None`, will use an Adagrad optimizer.
the deep part of the model. Defaults to Adagrad optimizer.
dnn_hidden_units: List of hidden units per layer. All layers are fully
connected.
dnn_activation_fn: Activation function applied to each layer. If None,