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question-answering-dataloader's Introduction

tokenizer


    • kmp search based start index & end index
    • traceback original text ( or decode )
    • doc_stride provide
  1. - [ ] tokenizer adapted join

multi answer 구현


  1. context에서 answer string matching
  2. char index to input ids candidate 구함
  3. question + context 에서 input ids 매칭

dataloader


  1. control by tokenizer
  2. dynamic padding, batchsize
  3. batchsize * padding ^ 2 <= min batchsize * max padding ^ 2
  4. args: (dataset, max_padding = 384, min_batchsize = 8, Pmul = 64, Bmul = None)# None은 static 하게 사용됨을 의미

구현


  1. pad 길이 역정렬
  2. sample pool 부족시 index늘리기 (항상 부족할것 임)
  3. sample 가능한 목록중 최대길이의 항목은 무조건 사용
  4. 가장 긴 항목 기준으로 다룰 수 있는 최대 Batchsize 결정
  5. Batchsize 만큼 sampling ( 가장 긴 pad항목 포함 )
  6. 적합한 padding 결정후 crop

그런데, 학습상에서 시간이 지남에 대해 단조롭게 pad가 감소하는것은 성능에 영향을 줄수 있으므로, 이렇게 시뮬레이션 된것들의 batch를 묶고, batch간의 순서를 shuffle한다.

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