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test_regression.py 2.6 KB
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# SPDX-License-Identifier: Apache-2.0
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"""Containing tests that check for regressions in vLLM's behavior.

It should include tests that are reported by users and making sure they
will never happen again.

"""
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import gc

import torch

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from vllm import LLM, SamplingParams
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from utils import models_path_prefix
import os
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def test_duplicated_ignored_sequence_group():
    """https://github.com/vllm-project/vllm/issues/1655"""

    sampling_params = SamplingParams(temperature=0.01,
                                     top_p=0.1,
                                     max_tokens=256)
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    llm = LLM(model=os.path.join(models_path_prefix, "facebook/opt-125m"),
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              max_num_batched_tokens=4096,
              tensor_parallel_size=1)
    prompts = ["This is a short prompt", "This is a very long prompt " * 1000]
    outputs = llm.generate(prompts, sampling_params=sampling_params)

    assert len(prompts) == len(outputs)


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def test_max_tokens_none():
    sampling_params = SamplingParams(temperature=0.01,
                                     top_p=0.1,
                                     max_tokens=None)
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    llm = LLM(model=os.path.join(models_path_prefix, "facebook/opt-125m"),
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              max_num_batched_tokens=4096,
              tensor_parallel_size=1)
    prompts = ["Just say hello!"]
    outputs = llm.generate(prompts, sampling_params=sampling_params)

    assert len(prompts) == len(outputs)


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def test_gc():
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    llm = LLM(os.path.join(models_path_prefix, "facebook/opt-125m"), enforce_eager=True)
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    del llm

    gc.collect()
    torch.cuda.empty_cache()

    # The memory allocated for model and KV cache should be released.
    # The memory allocated for PyTorch and others should be less than 50MB.
    # Usually, it's around 10MB.
    allocated = torch.cuda.memory_allocated()
    assert allocated < 50 * 1024 * 1024


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def test_model_from_modelscope(monkeypatch):
    # model: https://modelscope.cn/models/qwen/Qwen1.5-0.5B-Chat/summary
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    MODELSCOPE_MODEL_NAME = os.path.join(models_path_prefix, "qwen/Qwen1.5-0.5B-Chat")
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    monkeypatch.setenv("VLLM_USE_MODELSCOPE", "True")
    try:
        llm = LLM(model=MODELSCOPE_MODEL_NAME)

        prompts = [
            "Hello, my name is",
            "The president of the United States is",
            "The capital of France is",
            "The future of AI is",
        ]
        sampling_params = SamplingParams(temperature=0.8, top_p=0.95)

        outputs = llm.generate(prompts, sampling_params)
        assert len(outputs) == 4
    finally:
        monkeypatch.delenv("VLLM_USE_MODELSCOPE", raising=False)


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if __name__ == "__main__":
    import pytest
    pytest.main([__file__])