multivariate.py 文件源码

def _sample(self, n_samples):
        if self.logits.get_shape().ndims == 2:
            logits_flat = self.logits
        else:
            logits_flat = tf.reshape(self.logits, [-1, self.n_categories])
        samples_flat = tf.transpose(
            tf.multinomial(logits_flat, n_samples * self.n_experiments))
        shape = tf.concat([[n_samples, self.n_experiments],
                           self.batch_shape], 0)
        samples = tf.reshape(samples_flat, shape)
        static_n_samples = n_samples if isinstance(n_samples, int) else None
        static_n_exps = self.n_experiments if isinstance(self.n_experiments,
                                                         int) else None
        samples.set_shape(
            tf.TensorShape([static_n_samples, static_n_exps]).
            concatenate(self.get_batch_shape()))
        samples = tf.reduce_sum(
            tf.one_hot(samples, self.n_categories, dtype=self.dtype), axis=1)
        return samples