在Tensorflow中创建三对角二维张量

这是一种方法


tf.scatter_nd


：

    
      import tensorflow as tf
def tridiagonal(diag, sub, sup):
    n = tf.shape(diag)[0]
    r = tf.range(n)
    ii = tf.concat([r, r[1:], r[:-1]], axis=0)
    jj = tf.concat([r, r[:-1], r[1:]], axis=0)
    idx = tf.stack([ii, jj], axis=1)
    values = tf.concat([diag, sub, sup], axis=0)
    return tf.scatter_nd(idx, values, [n, n])
diag = tf.placeholder(tf.int32, [None])
sub = tf.placeholder(tf.int32, [None])
sup = tf.placeholder(tf.int32, [None])
tri = tridiagonal(diag, sub, sup)
with tf.Session() as sess:
    print(sess.run(tri, feed_dict={diag: [0, 1, 2, 3],
                                   sub: [4, 5, 6],
                                   sup: [7, 8, 9]}))
</code>
  

    
      [[0 7 0 0]
 [4 1 8 0]
 [0 5 2 9]
 [0 0 6 3]]
</code>