vllm/tests/v1/spec_decode/test_ngram.py

91 lines
4.1 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import numpy as np
from vllm.config import ModelConfig, SpeculativeConfig, VllmConfig
from vllm.v1.spec_decode.ngram_proposer import (NgramProposer,
_find_subarray_kmp,
_kmp_lps_array)
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]))
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]))
# Return on the first match
np.testing.assert_array_equal(_find_subarray_kmp(X, 1, 3),
np.array([6, 2, 3]))
def test_ngram_proposer():
def ngram_proposer(min_n: int, max_n: int, k: int) -> NgramProposer:
# Dummy model config. Just to set max_model_len.
model_config = ModelConfig(model="facebook/opt-125m",
task="generate",
max_model_len=100,
tokenizer="facebook/opt-125m",
tokenizer_mode="auto",
dtype="auto",
seed=None,
trust_remote_code=False)
return NgramProposer(
vllm_config=VllmConfig(model_config=model_config,
speculative_config=SpeculativeConfig.
from_dict({
"prompt_lookup_min": min_n,
"prompt_lookup_max": max_n,
"num_speculative_tokens": k,
"method": "ngram",
})))
# No match.
result = ngram_proposer(
2, 2, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 5]))
assert result is None
# No match for 4-gram.
result = ngram_proposer(
4, 4, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 1, 2, 3]))
assert result is None
# No match for 4-gram but match for 3-gram.
result = ngram_proposer(
3, 4, 2).propose(context_token_ids=np.array([1, 2, 3, 4, 1, 2, 3]))
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.
result = ngram_proposer(3, 4, 2).propose(
context_token_ids=np.array([2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4]))
assert np.array_equal(result, np.array([1, 2])) # Not [5, 1]
# Match for 2-gram and 3-gram, but not 4-gram.
result = ngram_proposer(
2, 4,
2).propose(context_token_ids=np.array([3, 4, 5, 2, 3, 4, 1, 2, 3, 4]))
assert np.array_equal(result, np.array([1, 2])) # Not [5, 2]