tensorflow中tf.argmax和tf.reduce_max

import tensorflow as tf

import numpy as np d_scores = {} d_scores[0] = [[[1,2],[3,4],[5,6]],[[7,8],[9,10],[11,12]]]  classes = tf.argmax(d_scores[0],axis=1) scores = tf.reduce_max(d_scores[0],axis=1)  with tf.Session() as sess:      print(classes.eval())     print(scores.eval())

结果

[[2 2]

import tensorflow as tf import numpy as np d_scores = {} d_scores[0] = [[[1,2],[3,4],[5,6]],[[7,8],[9,10],[11,12]]]  classes = tf.argmax(d_scores[0],axis=2) scores = tf.reduce_max(d_scores[0],axis=2)  with tf.Session() as sess:      print(classes.eval())     print(scores.eval())

可以看出tf.argmax和tf.reduce_max会把指定维度降掉

文章来源: tensorflow中tf.argmax和tf.reduce_max