106、TensorFlow變量 (二) reshape

import tensorflow as tf
rank_three_tensor = tf.ones([3, 4, 5])                 # 創建一個[3,4,5]大小的張量，3行4列，每個位置上有五個元素
matrix = tf.reshape(rank_three_tensor, [6, 10])  # 將當前變量reshape成[6,10]個大小的變量
matrixB = tf.reshape(matrix, [3, -1])                    # 將現有內容改造成3×20矩陣。-1指定這個維度的元素個數根據其他維度的元素個數來計算。
matrixAlt = tf.reshape(matrixB, [4, 3, -1])  # 將當前的矩陣reshape成 4行3列每個位置上為5個元素的 tensor
# 改變張量的形狀
# The number of elements of a scalar is always
# 1、因為經常有許多不同的形狀具有相同數量的元素。
#     所以改變這樣的張量的形狀，使得reshape前后的張量中元素的數量是相同的，

init = tf.global_variables_initializer()
sess = tf.Session()
print(sess.run(rank_three_tensor))
print(sess.run(matrix))
print(sess.run(matrixB))
print(sess.run(matrixAlt))

下邊是上面代碼輸出的結果

2018-02-16 20:33:55.488664: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\35\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
[[[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]

 [[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]

 [[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]]
[[ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]]
[[ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.
   1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.
   1.  1.]
 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.
   1.  1.]]
[[[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]

 [[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]

 [[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]

 [[ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]
  [ 1.  1.  1.  1.  1.]]]