message: Added missing test case in LinearModel
  LinearModel is miising test case for sparse_combiner=sqrtn, added the
  same to make the coverage complete.
diff: @@ -1838,6 +1838,22 @@ class LinearModelTest(test.TestCase):
  sess.run(bias.assign([5.]))
  self.assertAllClose([[1005.], [5010.]], self.evaluate(predictions))
  + def test_sparse_combiner_sqrtn(self):
  + wire_cast = fc.categorical_column_with_hash_bucket('wire_cast', 4)
  + with ops.Graph().as_default():
  + wire_tensor = sparse_tensor.SparseTensor(
  + values=['omar', 'stringer', 'marlo'], # hashed to = [2, 0, 3]
  + indices=[[0, 0], [1, 0], [1, 1]],
  + dense_shape=[2, 2])
  + features = {'wire_cast': wire_tensor}
  + model = fc.LinearModel([wire_cast], sparse_combiner='sqrtn')
  + predictions = model(features)
  + wire_cast_var, bias = model.variables
  + with _initialized_session() as sess:
  + self.evaluate(wire_cast_var.assign([[10.], [100.], [1000.], [10000.]]))
  + self.evaluate(bias.assign([5.]))
  + self.assertAllClose([[1005.], [7083.139]], self.evaluate(predictions))
  +
  def test_sparse_combiner_with_negative_weights(self):
  wire_cast = fc.categorical_column_with_hash_bucket('wire_cast', 4)
  wire_cast_weights = fc.weighted_categorical_column(wire_cast, 'weights')
  