[BugFix] Fix bad words with speculative decoding (#31908)
Signed-off-by: Nick Hill <nickhill123@gmail.com>
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@@ -691,9 +691,13 @@ def test_frequency_penalties(rejection_sampler):
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def test_bad_words(rejection_sampler):
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"""Test rejection sampling with bad words constraints"""
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"""Test rejection sampling with bad words constraints.
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This test applies bad words to non-consecutive requests (0 and 2, but not 1)
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to verify correct logit indexing when iterating over requests with bad words.
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"""
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spec_tokens = [[1, 2, 3], [1, 15, 3], [1, 2, 3]]
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output_tokens = [[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]]
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output_tokens = [[1, 2, 3, 4], [1, 15, 3, 4], [1, 2, 3, 4]]
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logits = create_logits_tensor(output_tokens, token_idx_to_override=15)
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metadata = create_sampling_metadata(
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@@ -701,17 +705,9 @@ def test_bad_words(rejection_sampler):
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output_token_ids=[[2], [3], [4]],
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spec_token_ids=spec_tokens,
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bad_words_token_ids={
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0: [
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[
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2,
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]
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],
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1: [
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[
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2,
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]
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],
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# Do not apply bad words to the last request
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0: [[2]],
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# Request 1 has no bad words (to test non-consecutive request handling)
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2: [[2]],
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},
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)
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bonus_token_tensor = torch.tensor(
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@@ -726,8 +722,11 @@ def test_bad_words(rejection_sampler):
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sampling_metadata=metadata,
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)
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# Request 0: bad word [2] matches prefix, so token 2 is rejected -> 15
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# Request 1: no bad words, all tokens match -> [1, 15, 3, 4]
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# Request 2: bad word [2] matches prefix, so token 2 is rejected -> 15
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expected = torch.tensor(
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[[1, 15, -1, -1], [1, 15, 3, 4], [1, 2, 3, 4]],
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[[1, 15, -1, -1], [1, 15, 3, 4], [1, 15, -1, -1]],
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dtype=torch.int,
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device=logits.device,
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)
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