def testStringInput(self):
   with self.assertRaisesRegexp(
       ValueError, 'on integer or non floating types are not supported'):
     # pylint: disable=g-long-lambda
     estimator.infer_real_valued_columns_from_input(
         np.array([['%d.0' % i for i in xrange(8)] for _ in xrange(7)]))

 def testBoolInput(self):
   with self.assertRaisesRegexp(
       ValueError, 'on integer or non floating types are not supported'):
     estimator.infer_real_valued_columns_from_input(
         np.array([[False for _ in xrange(8)] for _ in xrange(7)]))

 def testInt32Input(self):
   feature_columns = estimator.infer_real_valued_columns_from_input(
       np.ones(
           shape=[7, 8], dtype=np.int32))
   self._assert_single_feature_column([8], dtypes.int32, feature_columns)

 def testFloat64Input(self):
   feature_columns = estimator.infer_real_valued_columns_from_input(
       np.ones(
           shape=[7, 8], dtype=np.float64))
   self._assert_single_feature_column([8], dtypes.float64, feature_columns)

  def testInvalidArgs(self):
    with self.assertRaisesRegexp(ValueError, 'x or input_fn must be provided'):
      estimator.infer_real_valued_columns_from_input(None)

    with self.assertRaisesRegexp(ValueError, 'cannot be tensors'):
      estimator.infer_real_valued_columns_from_input(constant_op.constant(1.0))