test_ngram.py 3.31 KB
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# SPDX-License-Identifier: Apache-2.0

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import numpy as np
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from vllm.config import SpeculativeConfig, VllmConfig
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from vllm.v1.spec_decode.ngram_proposer import (NgramProposer,
                                                _find_subarray_kmp,
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                                                _kmp_lps_array)
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def test_kmp_lps_array():
    np.testing.assert_array_equal(_kmp_lps_array(np.array([])), np.array([]))
    np.testing.assert_array_equal(_kmp_lps_array(np.array([1])), np.array([0]))
    np.testing.assert_array_equal(_kmp_lps_array(np.array([1, 1, 1])),
                                  np.array([0, 1, 2]))
    np.testing.assert_array_equal(_kmp_lps_array(np.array([1, 2, 3, 4])),
                                  np.array([0, 0, 0, 0]))
    np.testing.assert_array_equal(_kmp_lps_array(np.array([1, 2, 1, 2, 3])),
                                  np.array([0, 0, 1, 2, 0]))
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def test_find_subarray_kmp():
    X = np.array([1, 2, 3, 4, 1, 2, 3, 5, 6])
    assert _find_subarray_kmp(X, 2, 2) is None
    X = np.array([1, 2, 3, 4, 1, 2, 3])
    np.testing.assert_array_equal(_find_subarray_kmp(X, 2, 3),
                                  np.array([4, 1, 2]))
    np.testing.assert_array_equal(_find_subarray_kmp(X, 2, 2), np.array([4,
                                                                         1]))
    np.testing.assert_array_equal(_find_subarray_kmp(X, 1, 3),
                                  np.array([4, 1, 2]))
    np.testing.assert_array_equal(_find_subarray_kmp(X, 1, 2), np.array([4,
                                                                         1]))
    X = np.array([1, 3, 6, 2, 3, 4, 1, 2, 3])
    np.testing.assert_array_equal(_find_subarray_kmp(X, 2, 3),
                                  np.array([4, 1, 2]))
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    # Return on the first match
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    np.testing.assert_array_equal(_find_subarray_kmp(X, 1, 3),
                                  np.array([6, 2, 3]))
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def test_ngram_proposer():
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    def ngram_proposer(min_n: int, max_n: int, k: int) -> NgramProposer:
        return NgramProposer(vllm_config=VllmConfig(
            speculative_config=SpeculativeConfig.from_dict(
                {
                    "prompt_lookup_min": min_n,
                    "prompt_lookup_max": max_n,
                    "num_speculative_tokens": k,
                    "method": "ngram",
                })))
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    # No match.
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    result = ngram_proposer(
        2, 2, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 5]))
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    assert result is None

    # No match for 4-gram.
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    result = ngram_proposer(
        4, 4, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 1, 2, 3]))
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    assert result is None

    # No match for 4-gram but match for 3-gram.
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    result = ngram_proposer(
        3, 4, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 1, 2, 3]))
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    assert np.array_equal(result, np.array([4, 1]))

    # Match for both 4-gram and 3-gram.
    # In this case, the proposer should return the 4-gram match.
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    result = ngram_proposer(3, 4, 2).propose(
        context_token_ids=np.array([2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4]))
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    assert np.array_equal(result, np.array([1, 2]))  # Not [5, 1]

    # Match for 2-gram and 3-gram, but not 4-gram.
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    result = ngram_proposer(
        2, 4,
        2).propose(context_token_ids=np.array([3, 4, 5, 2, 3, 4, 1, 2, 3, 4]))
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    assert np.array_equal(result, np.array([1, 2]))  # Not [5, 2]