Comments (3)
see #23 (comment)
the bisection algorithm is expected not to work with alpha=1, but also, it makes little sense to use it, because the regular torch.nn.softmax would be faster and better for this case.
we will clarify the documentation and then close these issues if that's alright
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Sure! sounds good
from entmax.
docstrings updated, thanks for reporting
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Related Issues (20)
- Usage of alpha HOT 3
- Unexpected behaviour of sparsemax gradients for 3d tensors HOT 8
- entmax implementation for Tesnoflow 2 HOT 1
- Replicating the behaviour from the paper HOT 1
- entmax_bisect leads to loss becoming nan HOT 16
- Problem with sparse activations HOT 9
- Entmax fails when all inputs are -inf HOT 1
- Alpha value less than one? HOT 8
- Index -1 is out of bounds HOT 1
- A bug when alpha = 1 for entmax_bisect? HOT 3
- Release patch 1.0.1 with torch install_requires fix HOT 5
- Code to reproduce figure 3 HOT 1
- alpha-entmax
- Errors when using the loss function HOT 9
- entmax_bisect bugs with fp16/bf16 HOT 1
- Nans gradients for tensors with singleton dimensions for budget_bisect. HOT 5
- Instability of entmax bisect around 0? HOT 1
- EntmaxBisect forward requires unused argument HOT 2
- Sparse losses return nan when there is -inf in the input HOT 2
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