diff options
Diffstat (limited to 'tensorflow/contrib/learn/python/learn/estimators/dnn.py')
| -rw-r--r-- | tensorflow/contrib/learn/python/learn/estimators/dnn.py | 11 |
1 files changed, 6 insertions, 5 deletions
diff --git a/tensorflow/contrib/learn/python/learn/estimators/dnn.py b/tensorflow/contrib/learn/python/learn/estimators/dnn.py index bfe1cd0aed..f9ba6711e6 100644 --- a/tensorflow/contrib/learn/python/learn/estimators/dnn.py +++ b/tensorflow/contrib/learn/python/learn/estimators/dnn.py @@ -748,15 +748,16 @@ class _DNNEstimator(estimator.Estimator): To create a _DNNEstimator for binary classification, where estimator = _DNNEstimator( feature_columns=[sparse_feature_a_emb, sparse_feature_b_emb], - head=head=head_lib._multi_class__head(n_classes=2), + head=head_lib._multi_class__head(n_classes=2), hidden_units=[1024, 512, 256]) If your label is keyed with "y" in your labels dict, and weights are keyed with "w" in features dict, and you want to enable centered bias, - head=head_lib._multi_class__head(n_classes=2, - label_name="x" - weight_column_name="w", - enable_centered_bias=True) + head = head_lib._multi_class__head( + n_classes=2, + label_name="x", + weight_column_name="w", + enable_centered_bias=True) estimator = _DNNEstimator( feature_columns=[sparse_feature_a_emb, sparse_feature_b_emb], head=head, |