Generate: update compute transition scores doctest (#27558)
This commit is contained in:
parent
913d03dc5e
commit
5330b83bc5
|
@ -1217,9 +1217,10 @@ class GenerationMixin:
|
|||
... outputs.sequences, outputs.scores, outputs.beam_indices, normalize_logits=False
|
||||
... )
|
||||
>>> # If you sum the generated tokens' scores and apply the length penalty, you'll get the sequence scores.
|
||||
>>> # Tip: recomputing the scores is only guaranteed to match with `normalize_logits=False`. Depending on the
|
||||
>>> # Tip 1: recomputing the scores is only guaranteed to match with `normalize_logits=False`. Depending on the
|
||||
>>> # use case, you might want to recompute it with `normalize_logits=True`.
|
||||
>>> output_length = input_length + np.sum(transition_scores.numpy() < 0, axis=1)
|
||||
>>> # Tip 2: the output length does NOT include the input length
|
||||
>>> output_length = np.sum(transition_scores.numpy() < 0, axis=1)
|
||||
>>> length_penalty = model.generation_config.length_penalty
|
||||
>>> reconstructed_scores = transition_scores.sum(axis=1) / (output_length**length_penalty)
|
||||
>>> print(np.allclose(outputs.sequences_scores, reconstructed_scores))
|
||||
|
|
Loading…
Reference in New Issue