Check that the value is nonnegative.

def check_nonnegative(value):
  """Check that the value is nonnegative."""
  if isinstance(value, tf.Tensor):
    with tf.control_dependencies([tf.assert_greater_equal(value, 0)]):
      value = tf.identity(value)
  elif value < 0:
    raise ValueError("Value must be non-negative.")
  return value