python
import tensorflow.contrib.learn as skflow
X_train = [[0, 0], [1, 0], [1, 1], [0, 1]]
y_train = [0, 0, 1, 1]
classifier = skflow.DNNClassifier(feature_columns=[skflow.infer_real_valued_columns_from_input(X_train)], hidden_units=[10, 20, 10], n_classes=2)
classifier.fit(X_train, y_train, steps=200)
X_test = [[0, 0], [1, 0]]
predictions = list(classifier.predict(X_test))
for i, prediction in enumerate(predictions):
