如何使用 tensorflow 对张量相位进行切片

Question

如何使用 tensorflow 对张量相位进行切片：

tensor = tf.constant([[1,2,3,4,5],[1,2,3,4,5],[1,2,3,4,5] ] )
    list = [0,2]

我想得到结果张量：

result_tensor = [[1,2,3],[1,2,3],[1,2,3]]

Answer 1

tensor =tf.constant([[1,2,3,4,5],[1,2,3,4,5],[1,2,3,4,5] ] )
lst = [0,2]
tensor[:, lst[0]:lst[1]+1]

Answer 2

tensor =tf.constant([[6,2,3,4,5],[1,7,3,4,5],[1,2,3,4,5] ] )

new_tensor = tf.slice(tensor,[0,0],[-1,3])
print(new_tensor)

这输出

tf.Tensor(
[[6 2 3]
 [1 7 3]
 [1 2 3]], shape=(3, 3), dtype=int32)

Answer 3

    import tensorflow as tf
    sess=tf.Session()
    def sess_print(tensor):
        print(sess.run(tensor))
    
    tensor = tf.constant([[1,2,3,4,5],[1,2,3,4,5],[1,2,3,4,5] ] )
    sess_print(tf.slice(tensor,[0,0],[3,3]))

[[1 2 3]
 [1 2 3]
 [1 2 3]]