tf.reshape(tensor, shape, name=None)

矩陣變形是常用的操作，在Tensorflow中調用方式有多種，例如：

1. tf.reshape

tf.reshape(L3,?[-1,?W4.get_shape().as_list()[0]])??

2. object.reshape

mnist.test.images.reshape(-1,?28,?28,?1)?

所有reshape函數中，關鍵的是shape這個參數

下以tf.reshape為例介紹shape參數對結果的影響

tf.reshape(tensor,?shape,?name=None)?

#?tensor?'t'?is?[1,?2,?3,?4,?5,?6,?7,?8,?9]??

#?tensor?'t'?has?shape?[9]??

reshape(t,?[3,?3])?==>?[[1,?2,?3],??

????????????????????????[4,?5,?6],??

????????????????????????[7,?8,?9]]??

??

??

#?tensor?'t'?is?[[[1,?1],?[2,?2]],??

#????????????????[[3,?3],?[4,?4]]]??

#?tensor?'t'?has?shape?[2,?2,?2]??

reshape(t,?[2,?4])?==>?[[1,?1,?2,?2],??

????????????????????????[3,?3,?4,?4]]??

??

??

#?tensor?'t'?is?[[[1,?1,?1],??

#?????????????????[2,?2,?2]],??

#????????????????[[3,?3,?3],??

#?????????????????[4,?4,?4]],??

#????????????????[[5,?5,?5],??

#?????????????????[6,?6,?6]]]??

#?tensor?'t'?has?shape?[3,?2,?3]??

#?pass?'[-1]'?to?flatten?'t'??

reshape(t,?[-1])?==>?[1,?1,?1,?2,?2,?2,?3,?3,?3,?4,?4,?4,?5,?5,?5,?6,?6,?6]??

??

??

#?-1?can?also?be?used?to?infer?the?shape??

??

??

#?-1?is?inferred?to?be?9:??

reshape(t,?[2,?-1])?==>?[[1,?1,?1,?2,?2,?2,?3,?3,?3],??

?????????????????????????[4,?4,?4,?5,?5,?5,?6,?6,?6]]??

#?-1?is?inferred?to?be?2:??

reshape(t,?[-1,?9])?==>?[[1,?1,?1,?2,?2,?2,?3,?3,?3],??

?????????????????????????[4,?4,?4,?5,?5,?5,?6,?6,?6]]??

#?-1?is?inferred?to?be?3:??

reshape(t,?[?2,?-1,?3])?==>?[[[1,?1,?1],??

??????????????????????????????[2,?2,?2],??

??????????????????????????????[3,?3,?3]],??

?????????????????????????????[[4,?4,?4],??

??????????????????????????????[5,?5,?5],??

??????????????????????????????[6,?6,?6]]]??

??

??

#?tensor?'t'?is?[7]??

#?shape?`[]`?reshapes?to?a?scalar??

reshape(t,?[])?==>?7?

總結

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