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Adding a min_steps parameter to BeamSearch
#5207
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epwalsh
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May 17, 2021
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Thanks @danieldeutsch, this looks great! I just have one comment
allennlp/nn/beam_search.py
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| @@ -471,19 +475,25 @@ def __init__( | |||
| beam_size: int = 10, | |||
| per_node_beam_size: int = None, | |||
| sampler: Sampler = None, | |||
| min_steps: int = 0, | |||
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I think making this an Optional[int] is more clear.
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| min_steps: int = 0, | |
| min_steps: Optional[int] = None, |
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Ok, I pushed this change. I had to change the code to make sure the value is valid, too.
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Abhishek-P
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Aug 11, 2021
* Implementing minimum number of decoding steps * Adding unit tests * Reformatting * Adding entry to changelog * Adding end token comment * Adding start token comment * Changing param to optional Co-authored-by: Pete <petew@allenai.org>
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Implements feature request 1 from #5205.
Changes proposed in this pull request:
min_stepsparameter toBeamSearch, which allows specifying the minimum length of the predicted sequences. This is commonly used in tasks like summarization, for instance by BARTBefore submitting
section of the
CONTRIBUTINGdocs.Writing docstrings section of the
CONTRIBUTINGdocs.After submitting
codecov/patchreports high test coverage (at least 90%).You can find this under the "Actions" tab of the pull request once the other checks have finished.