Seed固定でどこの乱数が固定されるか.pptx

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Seed固定でどこの乱数が固定されるか

Data & Analytics

Seed固定なし numpy pytorch
当然ながら、
Seedを固定しなければ
ノートブックをRestartすると
結果がかわる
ノートブック
Restart前後
ノートブック
Restart前後

Seed固定 numpy pytorch
ノートブック
Restart前後
ノートブック
Restart前後
ノートブックRestart前後での
再現がとれる
Iteration内での乱数は異なる

Iteration内Seed固定 numpy pytorch
Iteration内で毎度Seed固定コードを
流すと同じ乱数が得られる

ハイパーパラメータ探索の時には注意
train_loop関数で学習が行われるとして、
条件B, dが最適と決定
探索時のスコアを再現できない
Seed固定してるはずなのに…
結論：毎度呼び出そう
NLPにおけるmaskや、画像処理におけるaugmentationにおいても、
どこに再現性を持たせたいかを意識し、seed_everythingを呼び出す必要がある

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