message: Forwardprop: tests for a couple ops I wasn't sure about
  e.g. swish has a custom_gradient; seems fine
  More rigorous/automated coverage is on my list.
diff: @@ -37,6 +37,8 @@ from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  +from tensorflow.python.ops import nn_impl
  +from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.unconnected_gradients import UnconnectedGradients
  @@ -278,6 +280,14 @@ class ForwardpropTest(test.TestCase, parameterized.TestCase):
  with self.assertRaisesRegexp(ValueError, "test_error_string"):
  f(c)
  + @parameterized.named_parameters(
  + [("EluM5", -0.5, nn_ops.elu),
  + ("EluP5", [0.5], nn_ops.elu),
  + ("SwishP5", 0.5, nn_impl.swish),
  + ("SwishM5", [-0.5], nn_impl.swish)])
  + def testElementwiseNNOps(self, value, op_fn):
  + _test_gradients(self, op_fn, [constant_op.constant(value)], order=3)
  +
  def testPushPopAccumulatorState(self):
  # Note that this example is somewhat contrived. push_forwardprop_state is
  # probably only useful in practice for building functions that compute jvps
  