univariate.py 文件源码

def _sample(self, n_samples):
        minval, maxval = self.minval, self.maxval
        if not self.is_reparameterized:
            minval = tf.stop_gradient(minval)
            maxval = tf.stop_gradient(maxval)
        shape = tf.concat([[n_samples], self.batch_shape], 0)
        samples = tf.random_uniform(shape, 0, 1, dtype=self.dtype) * \
            (maxval - minval) + minval
        static_n_samples = n_samples if isinstance(n_samples, int) else None
        samples.set_shape(
            tf.TensorShape([static_n_samples]).concatenate(
                self.get_batch_shape()))
        return samples