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Generate: precision fix in compute_transition_scores doctests (#21251)

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Joao Gante 2023-01-23 11:13:51 +00:00 committed by GitHub
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1 changed files with 6 additions and 6 deletions
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12
src/transformers/generation/utils.py
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@ -975,12 +975,12 @@ class GenerationMixin:
>>> generated_tokens = outputs.sequences[:, input_length:]
>>> for tok, score in zip(generated_tokens[0], transition_scores[0]):
... # | token | token string | logits | probability
... print(f"| {tok:5d} | {tokenizer.decode(tok):8s} | {score.numpy():.4f} | {np.exp(score.numpy()):.2%}")
| 262 | the | -1.4136 | 24.33%
| 1110 | day | -2.6089 | 7.36%
| 618 | when | -2.0096 | 13.40%
| 356 | we | -1.8593 | 15.58%
| 460 | can | -2.5083 | 8.14%
... print(f"| {tok:5d} | {tokenizer.decode(tok):8s} | {score.numpy():.3f} | {np.exp(score.numpy()):.2%}")
| 262 | the | -1.414 | 24.33%
| 1110 | day | -2.609 | 7.36%
| 618 | when | -2.010 | 13.40%
| 356 | we | -1.859 | 15.58%
| 460 | can | -2.508 | 8.14%
>>> # Example 2: Reconstruct the sequence scores from Beam Search
>>> outputs = model.generate(