def _sample_n(self, n, seed=None):
shape = array_ops.concat(0, ([n], self.batch_shape()))
# Sample uniformly-at-random from the open-interval (-1, 1).
uniform_samples = random_ops.random_uniform(
shape=shape,
minval=np.nextafter(self.dtype.as_numpy_dtype(-1.),
self.dtype.as_numpy_dtype(0.)),
maxval=1.,
dtype=self.dtype,
seed=seed)
return (self.loc - self.scale * math_ops.sign(uniform_samples) *
math_ops.log(1. - math_ops.abs(uniform_samples)))
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