content: #  Copyright 2016 The TensorFlow Authors. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #  See the License for the specific language governing permissions and
  #  limitations under the License.
  """Example of DNNClassifier for Iris plant dataset."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from sklearn import metrics, cross_validation
  import tensorflow as tf
  from tensorflow.contrib import learn
  
  
  def main(unused_argv):
    # Load dataset.
    iris = learn.datasets.load_dataset('iris')
    x_train, x_test, y_train, y_test = cross_validation.train_test_split(
        iris.data, iris.target, test_size=0.2, random_state=42)
  
    # Build 3 layer DNN with 10, 20, 10 units respectively.
    classifier = learn.DNNClassifier(hidden_units=[10, 20, 10], n_classes=3)
  
    # Fit and predict.
    classifier.fit(x_train, y_train, steps=200)
    score = metrics.accuracy_score(y_test, classifier.predict(x_test))
    print('Accuracy: {0:f}'.format(score))
  
  
  if __name__ == '__main__':
    tf.app.run()
  