tf.multinomial

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明明按概率，亲测却非常随机

tf.multinomial(logits, num_samples, seed=None, name=None)

从multinomial分布中采样，样本个数是num_samples，每个样本被采样的概率由logits给出

parametrs:

  • logits: 2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :] represents the unnormalized log probabilities for all classes.2维量，shape是 [batch_size, num_classes]，每一行都是关于种类的未归一化的对数概率

  • num_samples: 0-D. Number of independent samples to draw for each row slice.标量，表示采样的个数，更重要的是，它限制了返回张量中元素的范围{：0，1，2，…，num_samples-1 }

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import tensorflow as tf
samples = tf.multinomial(tf.log([[10., 10., 10.]]), 5)
with tf.Session() as sess:
	sess.run(samples)

# 运行结果：array([[2, 1, 2, 2, 0]])