univariate.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))
        samples_flat = tf.cast(samples_flat, self.dtype)
        if self.logits.get_shape().ndims == 2:
            return samples_flat
        shape = tf.concat([[n_samples], self.batch_shape], 0)
        samples = tf.reshape(samples_flat, shape)
        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