Files
vllm/tests/detokenizer/test_min_tokens.py
2025-10-05 07:06:22 -07:00

53 lines
1.6 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import pytest
from transformers import AutoTokenizer
from vllm import SamplingParams
from vllm.v1.engine import EngineCoreRequest
from vllm.v1.engine.detokenizer import FastIncrementalDetokenizer
PROMPT = "Hello, my name is Lee, and I'm a student in the " + "college of engineering"
@pytest.mark.parametrize(
"min_tokens,stop,truth",
[
(0, None, " is Lee, and I'm a student in the college of engineering"),
(0, "e", " is L"),
(5, "e", " is Lee, and I'm a stud"),
],
)
def test_min_tokens_with_stop(min_tokens: int, stop: str, truth: str):
"""Test for a specific min_tokens and stop.
See https://github.com/vllm-project/vllm/pull/22014
"""
tokenizer = AutoTokenizer.from_pretrained("facebook/opt-125m")
all_prompt_ids = tokenizer(PROMPT, add_special_tokens=False).input_ids
# The prompt is "Hello, my name is"
prompt_token_ids = all_prompt_ids[:4]
params = SamplingParams(
stop=stop,
min_tokens=min_tokens,
)
request = EngineCoreRequest(
request_id="",
prompt_token_ids=prompt_token_ids,
mm_features=None,
sampling_params=params,
pooling_params=None,
eos_token_id=None,
arrival_time=0.0,
lora_request=None,
cache_salt=None,
data_parallel_rank=None,
)
detokenizer = FastIncrementalDetokenizer(tokenizer, request)
detokenizer.update(all_prompt_ids[4:], False)
assert detokenizer.output_text == truth