8ea5e44a43
[CI/Test] improve robustness of test by replacing del with context manager (vllm_runner) (#5357)
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
"""Test the different finish_reason="stop" situations during generation:
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1. One of the provided stop strings
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2. One of the provided stop tokens
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3. The EOS token
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Run `pytest tests/engine/test_stop_reason.py`.
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"""
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import pytest
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import transformers
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from vllm import SamplingParams
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MODEL = "facebook/opt-350m"
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STOP_STR = "."
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SEED = 42
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MAX_TOKENS = 1024
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@pytest.fixture
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def vllm_model(vllm_runner):
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with vllm_runner(MODEL) as vllm_model:
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yield vllm_model
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def test_stop_reason(vllm_model, example_prompts):
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tokenizer = transformers.AutoTokenizer.from_pretrained(MODEL)
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stop_token_id = tokenizer.convert_tokens_to_ids(STOP_STR)
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llm = vllm_model.model
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# test stop token
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outputs = llm.generate(example_prompts,
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sampling_params=SamplingParams(
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ignore_eos=True,
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seed=SEED,
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max_tokens=MAX_TOKENS,
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stop_token_ids=[stop_token_id]))
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for output in outputs:
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output = output.outputs[0]
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assert output.finish_reason == "stop"
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assert output.stop_reason == stop_token_id
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# test stop string
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outputs = llm.generate(example_prompts,
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sampling_params=SamplingParams(
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ignore_eos=True,
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seed=SEED,
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max_tokens=MAX_TOKENS,
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stop="."))
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for output in outputs:
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output = output.outputs[0]
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assert output.finish_reason == "stop"
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assert output.stop_reason == STOP_STR
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# test EOS token
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outputs = llm.generate(example_prompts,
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sampling_params=SamplingParams(
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seed=SEED, max_tokens=MAX_TOKENS))
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for output in outputs:
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output = output.outputs[0]
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assert output.finish_reason == "length" or (
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output.finish_reason == "stop" and output.stop_reason is None)
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