unit8co/darts

Dirichlet Likelihood TFT model

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#1,813 opened on 2023年6月3日

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buggood first issue

説明

Hello, I'm tring to use DirichletLikelihood in TFT model, but I got this issue. How can I fix it?

`ValueError: Expected value argument (Tensor of shape (32, 12, 1)) to be within the support (Simplex()) of the distribution Dirichlet(concentration: torch.Size([12, 1])), but found invalid values:
tensor([[[0.5691],
         [0.8910],
         [0.6211],
         [0.0000],
         [0.3685],
         [0.3022],
         [0.5626],
         [0.3967],
         [0.6753],
         [0.6197],
         [0.4106],
         [0.6041]],
...
        [[0.0000],
         [0.0000],
         [0.0000],
         [0.0000],
         [0.0000],
         [0.0000],
         [0.4241],
         [0.3950],
         [0.3232],
         [0.2716],
         [0.3947],
         [0.2650]]])`

Thanks

コントリビューターガイド

技術スタック
pythonpytorch
領域
datamachine learning
Issue 種別
bug
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
3
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
1-3 hours
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
stale
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
needs investigation
前提条件
PyTorch basicsTemporal Fusion TransformerDirichlet distribution
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
40
調査方針
The error indicates that the TFT model output tensor of shape (32, 12, 1) is being passed as the value argument to Dirichlet, but Dirichlet expects a simplex (values summing to 1 along the last dimension). The issue likely stems from the TFT model's output not being normalized. Investigate the darts source code for the TFT model and its integration with DirichletLikelihood, specifically how the output is transformed before being passed to the distribution. Look at the comments in the issue for any additional context or attempted fixes. Check if there is a missing softmax or normalization step in the model head.