TensorFlow 维度变换

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Reference

reshape

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arr = tf.range(60)
t = tf.reshape(arr, [3, 4, 5])
t1 = tf.reshape(t, [3, 4 * 5])
t2 = tf.reshape(t, [3, -1])
t3 = tf.reshape(t, [-1])
print(t) # tf.Tensor(
         # [[[ 0  1  2  3  4]
         #   [ 5  6  7  8  9]
         #   [10 11 12 13 14]
         #   [15 16 17 18 19]]
         # 
         #  [[20 21 22 23 24]
         #   [25 26 27 28 29]
         #   [30 31 32 33 34]
         #   [35 36 37 38 39]]
         # 
         #  [[40 41 42 43 44]
         #   [45 46 47 48 49]
         #   [50 51 52 53 54]
         #   [55 56 57 58 59]]], shape=(3, 4, 5), dtype=int32)
print(t1) # tf.Tensor(
          # [[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]
          #  [20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39]
          #  [40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59]], shape=(3, 20), dtype=int32)
print(t2) # tf.Tensor(
          # [[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]
          #  [20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39]
          #  [40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59]], shape=(3, 20), dtype=int32)
print(t3) # tf.Tensor(
          # [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
          #  24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
          #  48 49 50 51 52 53 54 55 56 57 58 59], shape=(60,), dtype=int32)

transpose

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arr = tf.range(60)
t1 = tf.reshape(arr, [3, -1])
t2 = tf.reshape(arr, [3, 4, 5])
t11 = tf.transpose(t1)
t21 = tf.transpose(t2)
t22 = tf.transpose(t2, perm=[0, 2, 1])
print(t1) # tf.Tensor(
          # [[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19]
          #  [20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39]
          #  [40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59]], shape=(3, 20), dtype=int32)
print(t11) # tf.Tensor(
           # [[ 0 20 40]
           #  [ 1 21 41]
           #  [ 2 22 42]
           #  [ 3 23 43]
           #  [ 4 24 44]
           #  [ 5 25 45]
           #  [ 6 26 46]
           #  [ 7 27 47]
           #  [ 8 28 48]
           #  [ 9 29 49]
           #  [10 30 50]
           #  [11 31 51]
           #  [12 32 52]
           #  [13 33 53]
           #  [14 34 54]
           #  [15 35 55]
           #  [16 36 56]
           #  [17 37 57]
           #  [18 38 58]
           #  [19 39 59]], shape=(20, 3), dtype=int32)
print(t2) # tf.Tensor(
          # [[[ 0  1  2  3  4]
          #   [ 5  6  7  8  9]
          #   [10 11 12 13 14]
          #   [15 16 17 18 19]]
          # 
          #  [[20 21 22 23 24]
          #   [25 26 27 28 29]
          #   [30 31 32 33 34]
          #   [35 36 37 38 39]]
          # 
          #  [[40 41 42 43 44]
          #   [45 46 47 48 49]
          #   [50 51 52 53 54]
          #   [55 56 57 58 59]]], shape=(3, 4, 5), dtype=int32)
print(t21) # tf.Tensor(
           # [[[ 0 20 40]
           #   [ 5 25 45]
           #   [10 30 50]
           #   [15 35 55]]
           # 
           #  [[ 1 21 41]
           #   [ 6 26 46]
           #   [11 31 51]
           #   [16 36 56]]
           # 
           #  [[ 2 22 42]
           #   [ 7 27 47]
           #   [12 32 52]
           #   [17 37 57]]
           # 
           #  [[ 3 23 43]
           #   [ 8 28 48]
           #   [13 33 53]
           #   [18 38 58]]
           # 
           #  [[ 4 24 44]
           #   [ 9 29 49]
           #   [14 34 54]
           #   [19 39 59]]], shape=(5, 4, 3), dtype=int32)
print(t22) # tf.Tensor(
           # [[[ 0  5 10 15]
           #   [ 1  6 11 16]
           #   [ 2  7 12 17]
           #   [ 3  8 13 18]
           #   [ 4  9 14 19]]
           # 
           #  [[20 25 30 35]
           #   [21 26 31 36]
           #   [22 27 32 37]
           #   [23 28 33 38]
           #   [24 29 34 39]]
           # 
           #  [[40 45 50 55]
           #   [41 46 51 56]
           #   [42 47 52 57]
           #   [43 48 53 58]
           #   [44 49 54 59]]], shape=(3, 5, 4), dtype=int32)

expand_dims

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arr = tf.range(60)
t = tf.reshape(arr, [3, 4, 5])
t1 = tf.expand_dims(t, axis=0)
print(t) # tf.Tensor(
         # [[[ 0  1  2  3  4]
         #   [ 5  6  7  8  9]
         #   [10 11 12 13 14]
         #   [15 16 17 18 19]]
         # 
         #  [[20 21 22 23 24]
         #   [25 26 27 28 29]
         #   [30 31 32 33 34]
         #   [35 36 37 38 39]]
         # 
         #  [[40 41 42 43 44]
         #   [45 46 47 48 49]
         #   [50 51 52 53 54]
         #   [55 56 57 58 59]]], shape=(3, 4, 5), dtype=int32)
print(t1) # tf.Tensor(
          # [[[[ 0  1  2  3  4]
          #    [ 5  6  7  8  9]
          #    [10 11 12 13 14]
          #    [15 16 17 18 19]]
          # 
          #   [[20 21 22 23 24]
          #    [25 26 27 28 29]
          #    [30 31 32 33 34]
          #    [35 36 37 38 39]]
          # 
          #   [[40 41 42 43 44]
          #    [45 46 47 48 49]
          #    [50 51 52 53 54]
          #    [55 56 57 58 59]]]], shape=(1, 3, 4, 5), dtype=int32)

squeeze

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arr = tf.range(60)
t = tf.reshape(arr, [1, 3, 4, 5])
t1 = tf.squeeze(t, axis=0)
print(t) # tf.Tensor(
         # [[[[ 0  1  2  3  4]
         #    [ 5  6  7  8  9]
         #    [10 11 12 13 14]
         #    [15 16 17 18 19]]
         # 
         #   [[20 21 22 23 24]
         #    [25 26 27 28 29]
         #    [30 31 32 33 34]
         #    [35 36 37 38 39]]
         # 
         #   [[40 41 42 43 44]
         #    [45 46 47 48 49]
         #    [50 51 52 53 54]
         #    [55 56 57 58 59]]]], shape=(1, 3, 4, 5), dtype=int32)
print(t1) # tf.Tensor(
          # [[[ 0  1  2  3  4]
          #   [ 5  6  7  8  9]
          #   [10 11 12 13 14]
          #   [15 16 17 18 19]]
          # 
          #  [[20 21 22 23 24]
          #   [25 26 27 28 29]
          #   [30 31 32 33 34]
          #   [35 36 37 38 39]]
          # 
          #  [[40 41 42 43 44]
          #   [45 46 47 48 49]
          #   [50 51 52 53 54]
          #   [55 56 57 58 59]]], shape=(3, 4, 5), dtype=int32)

本文标题:TensorFlow 维度变换

文章作者:魏超

发布时间:2019年05月13日 - 09:05

最后更新:2019年05月20日 - 09:05

原始链接:http://www.weichao.io/2019/05/13/TensorFlow-维度变换/

许可协议: 署名-非商业性使用-禁止演绎 4.0 国际 转载请保留原文链接及作者。

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