[chore] Remove obsolete comments
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@@ -516,10 +516,6 @@ def _apply_top_k_top_p(
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top_p_mask[:, -1] = False
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logits_sort.masked_fill_(top_p_mask, -float("inf"))
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# Re-sort the probabilities.
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# logits = torch.empty_like(logits_sort).scatter_(dim=-1,
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# index=logits_idx,
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# src=logits_sort)
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return logits_sort, logits_idx
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@@ -883,7 +879,6 @@ def _sample_with_torch(
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seq_groups=seq_groups_arg,
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)
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if logits_idx is not None:
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# multinomial_samples[sampling_type] = logits_idx[:, result_idx[:][0]]
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token_ids = logits_idx[long_sample_indices].gather(
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dim=1, index=result_idx.to(logits_idx.device)
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)
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