用tf.one_hot函数写任一坐标为1的二维张量

先给出tf.one_hot的用例：（例子转自https://www.jianshu.com/p/c5b4ec39713b）

 import tensorflow as tf
 var0 = tf.one_hot(indices=[1, 2, 3], depth=3, axis=0)
 var1 = tf.one_hot(indices=[1, 2, 3], depth=4, axis=0)
 var2 = tf.one_hot(indices=[1, 2, 3], depth=4, axis=1)
 # axis=1 按行排
 var3 = tf.one_hot(indices=[1, 2, 3], depth=4, axis=-1)
 with tf.Session() as sess:
     sess.run(tf.global_variables_initializer())
     a0 = sess.run(var0)
     a1 = sess.run(var1)
     a2 = sess.run(var2)
     a3 = sess.run(var3)
     print("var0(axis=0 depth=3)\n", a0)
     print("var1(axis=0 depth=4P)\n", a1)
     print("var2(axis=1)\n", a2)
     print("var3(axis=-1)\n", a3)

运行结果如下：

 2018-08-01 18:06:39.012597: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
 var0(axis=0 depth=3)
  [[0. 0. 0.]
  [1. 0. 0.]
  [0. 1. 0.]]
 var1(axis=0 depth=4P)
  [[0. 0. 0.]
  [1. 0. 0.]
  [0. 1. 0.]
  [0. 0. 1.]]
 var2(axis=1)
  [[0. 1. 0. 0.]
  [0. 0. 1. 0.]
  [0. 0. 0. 1.]]
 var3(axis=-1)
  [[0. 1. 0. 0.]
  [0. 0. 1. 0.]
  [0. 0. 0. 1.]]

 进程已结束,退出代码0

这里需要一个4*3的矩阵，记为var1，则需要var1[2,1]为0的one_hot矩阵。如下代码可实现。

 import tensorflow as tf
 q1 = 2
 q2 = 1
 depth = 4
 kuan = 3
 var0 = tf.one_hot(indices=[q2], depth=kuan, on_value=q1, off_value=depth, axis=1)
 var1 = tf.one_hot(indices=[depth, q1, depth], depth=depth, axis=0)
 with tf.Session() as sess:
     sess.run(tf.global_variables_initializer())
     a0 = sess.run(var0)
     a1 = sess.run(var1)
     print("var0(axis=0 depth=3)\n", a0)
     print("var1(axis=0 depth=4P)\n", a1)

运行结果：

 2018-08-01 18:08:01.640973: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
 var0(axis=0 depth=3)
  [[4 2 4]]
 var1(axis=0 depth=4P)
  [[0. 0. 0.]
  [0. 0. 0.]
  [0. 1. 0.]
  [0. 0. 0.]]

 进程已结束,退出代码0