message: Specify float32 as float type instead of float64
diff: @@ -32,9 +32,9 @@ IRIS_TEST = os.path.join(os.path.dirname(__file__), "iris_test.csv")
  def main(unused_argv):
  # Load datasets.
  training_set = tf.contrib.learn.datasets.base.load_csv_with_header(
  - filename=IRIS_TRAINING, target_dtype=np.int, features_dtype=np.float)
  + filename=IRIS_TRAINING, target_dtype=np.int, features_dtype=np.float32)
  test_set = tf.contrib.learn.datasets.base.load_csv_with_header(
  - filename=IRIS_TEST, target_dtype=np.int, features_dtype=np.float)
  + filename=IRIS_TEST, target_dtype=np.int, features_dtype=np.float32)
  validation_metrics = {
  "accuracy":
  @@ -83,7 +83,7 @@ def main(unused_argv):
  # Classify two new flower samples.
  new_samples = np.array(
  - [[6.4, 3.2, 4.5, 1.5], [5.8, 3.1, 5.0, 1.7]], dtype=float)
  + [[6.4, 3.2, 4.5, 1.5], [5.8, 3.1, 5.0, 1.7]], dtype=np.float32)
  y = list(classifier.predict(new_samples))
  print("Predictions: {}".format(str(y)))
  