python - 具有矢量值的 Tensorflow 稀疏张量到密集张量

Question

我有一些稀疏索引:

[[0 0]
 [0 1]
 [1 0]
 [1 1]
 [1 2]
 [2 0]]

每个指标对应的值为:

[[0.1 0.2 0.3]
 [0.4 0.5 0.6]
 [0.7 0.8 0.9]
 [1.0 1.1 1.2]
 [1.3 1.4 1.5]
 [1.6 1.7 1.8]]

如何在tensorflow中将6x3值张量转换为3x3x3稠密张量？ indices 中未指定的索引值为零向量 [0. 0. 0.]。稠密张量就是这样:

[[[0.1 0.2 0.3]
  [0.4 0.5 0.6]
  [0.0 0.0 0.0]]

 [[0.7 0.8 0.9]
  [1.0 1.1 1.2]
  [1.3 1.4 1.5]]

 [[1.6 1.7 1.8]
  [0.0 0.0 0.0]
  [0.0 0.0 0.0]]]

Answer 1

你可以用 tf.scatter_nd 做到这一点:

import tensorflow as tf

with tf.Graph().as_default(), tf.Session() as sess:
    indices = tf.constant(
        [[0, 0],
         [0, 1],
         [1, 0],
         [1, 1],
         [1, 2],
         [2, 0]])
    values = tf.constant(
        [[0.1, 0.2, 0.3],
         [0.4, 0.5, 0.6],
         [0.7, 0.8, 0.9],
         [1.0, 1.1, 1.2],
         [1.3, 1.4, 1.5],
         [1.6, 1.7, 1.8]])
    out = tf.scatter_nd(indices, values, [3, 3, 3])
    print(sess.run(out))

输出:

[[[0.1 0.2 0.3]
  [0.4 0.5 0.6]
  [0.  0.  0. ]]

 [[0.7 0.8 0.9]
  [1.  1.1 1.2]
  [1.3 1.4 1.5]]

 [[1.6 1.7 1.8]
  [0.  0.  0. ]
  [0.  0.  0. ]]]