Comments (1)
Add this module class AdaptiveConcatPool2d(nn.Module): "Concats AdaptiveAvgPool2d
and AdaptiveMaxPool2d
." def init(self): self.ap = nn.AdaptiveAvgPool2d(1) self.mp = nn.AdaptiveMaxPool2d(1) def forward(self, x): return torch.cat([self.mp(x), self.ap(x)]…
from kaggle-rainforest-connection-species-audio-detection.
Related Issues (20)
- pretrainedなし
- CRNNためす
- シェルスクリプトから実行してみる
- accのグラフも書く
- wandbのパラメータに最後まで実行されたかわかるようなパラメータ入れる
- ランダムに学習する
- TTA, 推論するデータにノイズを加えてその平均値で推論を行なうということをやってみる。
- 図にaccuracyも追加する
- sweep機能実装
- confusion matrixの実装
- 推論苦手なclass対策を行う
- nfftのsweep
- yukiさんのlwlrapの評価方法を確認する
- あらいさんが言ってたgapとgmpのやつ探す
- lossにgapとかいれてみる。
- lossにgapとgmpの和を入れる
- 背景だけで学習ある程度判別できるのであれば、不得意なクラスはそれで特定するのはどう?
- hpssを入れて学習
- exp015が完全にランダムになっちゃってることがわかったので、再度実験し直す。
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from kaggle-rainforest-connection-species-audio-detection.