tensorflow_probability/python/mcmc/simple_step_size_adaptation.py
def _maybe_validate_target_accept_prob(target_accept_prob, validate_args):
  """Validates that target_accept_prob is in (0, 1)."""
  if not validate_args:
    return target_accept_prob
  with tf.control_dependencies([
      tf.compat.v1.assert_positive(
          target_accept_prob, message='`target_accept_prob` must be > 0.'),
      tf.compat.v1.assert_less(
          target_accept_prob,
          tf.ones_like(target_accept_prob),
          message='`target_accept_prob` must be < 1.')
  ]):
    return tf.identity(target_accept_prob)
def _maybe_validate_target_accept_prob(target_accept_prob, validate_args):
  """Validates that target_accept_prob is in (0, 1)."""
  if not validate_args:
    return target_accept_prob
  with tf.control_dependencies([
      tf.compat.v1.assert_positive(
          target_accept_prob, message='`target_accept_prob` must be > 0.'),
      tf.compat.v1.assert_less(
          target_accept_prob,
          tf.ones_like(target_accept_prob),
          message='`target_accept_prob` must be < 1.')
  ]):
    return tf.identity(target_accept_prob)
def _maybe_validate_target_accept_prob ( target_accept_prob , validate_args ) : if not validate_args : return target_accept_prob with tf . control_dependencies ( [ tf . compat . v1 . assert_positive ( target_accept_prob , message = '`target_accept_prob` must be > 0.' ) , tf . compat . v1 . assert_less ( target_accept_prob , tf . ones_like ( target_accept_prob ) , message = '`target_accept_prob` must be < 1.' ) ] ) : return tf . identity ( target_accept_prob )
Validates that target_accept_prob is in (0, 1).
Validates that target_accept_prob is in ( 0 1 ) .