TensorFlow入门基础知识（四）tf.sparse_to_dense的用法

import tensorflow  as tf
import numpy as np
v1 = tf.reshape(tf.range(10),[10,1])
v2 = tf.reshape(tf.range(0,10),[10,1])
v3 = tf.concat(1,[v1,v2])
dense_labels = tf.sparse_to_dense(v3,
[10, 12],
1.0, 0.0)
init_op = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init_op)
print(sess.run(v1))
print(sess.run(v2))
print(sess.run(v3))
print(sess.run(dense_labels))

[[0]
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]]
[[0]
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]]
[[0 0]
[1 1]
[2 2]
[3 3]
[4 4]
[5 5]
[6 6]
[7 7]
[8 8]
[9 9]]
[[1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0.]]