def _sample_n(self, n, seed=None):
    shape = array_ops.concat([[n], array_ops.shape(self._rate)], 0)
    sampled = random_ops.random_uniform(shape, minval=np.finfo(self.dtype.as_numpy_dtype).tiny, maxval=1.0, seed=seed, dtype=self.dtype)
    return ((- math_ops.log(sampled)) / self._rate)
def _sample_n(self, n, seed=None):
    shape = array_ops.concat([[n], array_ops.shape(self._rate)], 0)
    sampled = random_ops.random_uniform(shape, minval=np.finfo(self.dtype.as_numpy_dtype).tiny, maxval=1.0, seed=seed, dtype=self.dtype)
    return ((- math_ops.log(sampled)) / self._rate)