Question

我想通过复制其中一个张量来连接两个张量。例如，我有两个形状的张量[2,2,3]和[2,3]。结果应该是[2,2,6]的形状。

t1 = [[[ 1, 1, 1], [2, 2, 2]],
      [[ 3, 3, 3], [4, 4, 4]]]
t2 = [[ 5, 5, 5], [6, 6, 6]]
"""
t3 = # some tf ops
t3 should be
t3 = [[[ 1, 1, 1, 5, 5, 5], [2, 2, 2, 5, 5, 5]],
      [[ 3, 3, 3, 6, 6, 6], [4, 4, 4, 6, 6, 6]]]
"""

所以如果两个张量的形状[10,5,8]和[10,3]，结果应该是形状[10,5,11]。

已更新

另一个例子：

t1 = np.reshape(np.arange(3*4*5), [3,4,5])
t2 = np.reshape(np.arange(3*1*2), [3,2])
""""
t3 should be
  [[[  0.,   1.,   2.,   3.,   4.,   0.,   1.],
    [  5.,   6.,   7.,   8.,   9.,   0.,   1.],
    [ 10.,  11.,  12.,  13.,  14.,   0.,   1.],
    [ 15.,  16.,  17.,  18.,  19.,   0.,   1.]],

   [[ 20.,  21.,  22.,  23.,  24.,   2.,   3.],
    [ 25.,  26.,  27.,  28.,  29.,   2.,   3.],
    [ 30.,  31.,  32.,  33.,  34.,   2.,   3.],
    [ 35.,  36.,  37.,  38.,  39.,   2.,   3.]],

   [[ 40.,  41.,  42.,  43.,  44.,   4.,   5.],
    [ 45.,  46.,  47.,  48.,  49.,   4.,   5.],
    [ 50.,  51.,  52.,  53.,  54.,   4.,   5.],
    [ 55.,  56.,  57.,  58.,  59.,   4.,   5.]]]
"""

Answer 1

函数tf.tile可以帮助您实现它。单击here以获取该功能的详细信息。

import numpy as np
import tensorflow as tf

t1 = np.reshape(np.arange(3*4*5), [3,4,5])
t2 = np.reshape(np.arange(3*1*2), [3,2])

# Keep t1 stay
t1_p = tf.placeholder(tf.float32, [3,4,5])

# Change t2 from shape(3,2) to shape(3,4,2) followed below two steps:
#    1. copy element of 2rd dimension of t2 as many times as you hope, as the updated example, it is 4
#    2. reshape the tiled tensor to compatible shape
t2_p = tf.placeholder(tf.float32, [3,2])
# copy the element of 2rd dimention of t2 by 4 times
t2_p_tiled = tf.tile(t2_p, [1, 4])
# reshape tiled t2 with shape(3,8) to the compatible shape(3,4,2)
t2_p_reshaped = tf.reshape(t2_p_tiled, [3,4,2])

# Concat t1 and changed t2, then you will get t3 you want
t3_p = tf.concat([t1_p, t2_p_reshaped], 2)

sess = tf.InteractiveSession()
t3 = sess.run(t3_p, {t1_p:t1, t2_p:t2})

print '*' * 20
print t1
print '*' * 20
print t2
print '*' * 20
print t3

# if you confused what the tf.tile did, you can print t2_p_tiled to see what happend
t2_tile = sess.run(t2_p_tiled, {t2_p:t2})
print '*' * 20
print t2_tile

Answer 2

您需要使用功能包https://www.tensorflow.org/api_docs/python/array_ops/slicing_and_joining#pack

代码应该与此类似：

t2 = tf.transpose(t2)
tf.pack([t1, tf.pack(t2,t2, axis=1)], axis=2)

<强>更新

因此，如果两个张量的形状[10,5,8]和[10,3]，结果应该是形状[10,5,11]。

我不确定这是可能的。你能写下这个张量是什么以及结果张量应该如何？第一个和结果张量的第二个维度不是你可以从头开始为第二个张量创建的东西。

TensorFlow：如何通过复制张量之一来连接张量？

2 个答案: