d4d93db2c5
Signed-off-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Co-authored-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Co-authored-by: Nicolò Lucchesi <nlucches@redhat.com> Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com> Co-authored-by: Michael Goin <michael@neuralmagic.com>
42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Make sure ignore_eos works.
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Run `pytest tests/samplers/test_ignore_eos.py`.
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"""
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import pytest
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from vllm import SamplingParams
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@pytest.fixture(autouse=True)
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def v1(run_with_both_engines):
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"""We can run both engines for this test."""
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pass
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# We also test with llama because it has generation_config to specify EOS
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# (past regression).
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MODELS = ["distilbert/distilgpt2", "meta-llama/Llama-3.2-1B"]
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("dtype", ["half"])
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@pytest.mark.parametrize("max_tokens", [512])
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def test_ignore_eos(
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vllm_runner,
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example_prompts,
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model: str,
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dtype: str,
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max_tokens: int,
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) -> None:
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with vllm_runner(model, dtype=dtype) as vllm_model:
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sampling_params = SamplingParams(max_tokens=max_tokens,
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ignore_eos=True)
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for prompt in example_prompts:
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ignore_eos_output = vllm_model.model.generate(
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prompt, sampling_params=sampling_params)
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output_length = len(ignore_eos_output[0].outputs[0].token_ids)
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assert output_length == max_tokens
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