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fixed formatting with black

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jesspeck 2023-08-14 09:41:12 -04:00
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commit ad6ceb64b7
1 changed files with 5 additions and 5 deletions
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src/transformers/generation/logits_process.py
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@ -1085,19 +1085,19 @@ class PrefixConstrainedLogitsProcessor(LogitsProcessor):
class HammingDiversityLogitsProcessor(LogitsProcessor): class HammingDiversityLogitsProcessor(LogitsProcessor):
r""" r"""
[`LogitsProcessor`] that enforces diverse beam search. [`LogitsProcessor`] that enforces diverse beam search.
Note that this logits processor is only effective for Note that this logits processor is only effective for
[`PreTrainedModel.group_beam_search`]. See [Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence [`PreTrainedModel.group_beam_search`]. See [Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence
Models](https://arxiv.org/pdf/1610.02424.pdf) for more details. Models](https://arxiv.org/pdf/1610.02424.pdf) for more details.
<Tip> <Tip>
Diverse beam search can be particularly useful in scenarios where a variety of different outputs is desired, rather than multiple similar sequences. Diverse beam search can be particularly useful in scenarios where a variety of different outputs is desired, rather than multiple similar sequences.
It allows the model to explore different generation paths and provides a broader coverage of possible outputs. It allows the model to explore different generation paths and provides a broader coverage of possible outputs.
</Tip> </Tip>
<Warning> <Warning>
This logits processor can be resource-intensive, especially when using large models or long sequences. This logits processor can be resource-intensive, especially when using large models or long sequences.
@ -1168,7 +1168,7 @@ class HammingDiversityLogitsProcessor(LogitsProcessor):
# Set up for diverse beam search # Set up for diverse beam search
num_beams = 6 num_beams = 6
num_beam_groups = 2 num_beam_groups = 2
model_kwargs = { model_kwargs = {
"encoder_outputs": model.get_encoder()( "encoder_outputs": model.get_encoder()(