def _log_prob(self, x):
    (loc, scale, low, high) = self._loc_scale_low_high()
    log_prob = (((- tf.math.log1p(tf.square(((x - loc) / scale)))) - (np.log(np.pi) + tf.math.log(scale))) - self._log_normalizer(loc=loc, scale=scale, low=low, high=high))
    return tf.where(((x > high) | (x < low)), dtype_util.as_numpy_dtype(x.dtype)((- np.inf)), log_prob)
def _log_prob(self, x):
    (loc, scale, low, high) = self._loc_scale_low_high()
    log_prob = (((- tf.math.log1p(tf.square(((x - loc) / scale)))) - (np.log(np.pi) + tf.math.log(scale))) - self._log_normalizer(loc=loc, scale=scale, low=low, high=high))
    return tf.where(((x > high) | (x < low)), dtype_util.as_numpy_dtype(x.dtype)((- np.inf)), log_prob)