pooling backward 동작 확인 코드 - LOPES-HUFS/DeepLearningFromForR GitHub Wiki
우선 backward로 들어가는 dout을 Pooling_dout이라고 놓고 형상을 맞춰 만듭니다.
그 다음 첫번째 줄을 실행합니다.
>>> import numpy as np
>>> Pooling_dout =np.arange(432000).reshape(12, 12, 30, 100)
>>> pooling_backward_dout = Pooling_dout.transpose(0, 2, 3, 1)
>>> pooling_backward_dout
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...,
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...,
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[326999, 329999, 332999, ..., 353999, 356999, 359999]]],
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[362999, 365999, 368999, ..., 389999, 392999, 395999]]],
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[396002, 399002, 402002, ..., 423002, 426002, 429002],
...,
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[396098, 399098, 402098, ..., 423098, 426098, 429098],
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[[396100, 399100, 402100, ..., 423100, 426100, 429100],
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...,
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...,
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...,
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...,
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[398898, 401898, 404898, ..., 425898, 428898, 431898],
[398899, 401899, 404899, ..., 425899, 428899, 431899]],
[[398900, 401900, 404900, ..., 425900, 428900, 431900],
[398901, 401901, 404901, ..., 425901, 428901, 431901],
[398902, 401902, 404902, ..., 425902, 428902, 431902],
...,
[398997, 401997, 404997, ..., 425997, 428997, 431997],
[398998, 401998, 404998, ..., 425998, 428998, 431998],
[398999, 401999, 404999, ..., 425999, 428999, 431999]]]])
>>> pool_size = 4
>>> dmax = np.zeros((pooling_backward_dout.size, pool_size))
>>> dmax.shape
(432000, 4)
>>> pooling_backward_dout.flatten()
array([ 0, 3000, 6000, ..., 425999, 428999, 431999])
>>>