41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
import pytest
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from vllm import LLM, SamplingParams
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def test_multiple_sampling_params():
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llm = LLM(model="facebook/opt-125m",
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max_num_batched_tokens=4096,
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tensor_parallel_size=1)
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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sampling_params = [
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SamplingParams(temperature=0.01, top_p=0.95),
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SamplingParams(temperature=0.3, top_p=0.95),
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SamplingParams(temperature=0.7, top_p=0.95),
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SamplingParams(temperature=0.99, top_p=0.95),
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]
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# Multiple SamplingParams should be matched with each prompt
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outputs = llm.generate(prompts, sampling_params=sampling_params)
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assert len(prompts) == len(outputs)
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# Exception raised, if the size of params does not match the size of prompts
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with pytest.raises(ValueError):
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outputs = llm.generate(prompts, sampling_params=sampling_params[:3])
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# Single SamplingParams should be applied to every prompt
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single_sampling_params = SamplingParams(temperature=0.3, top_p=0.95)
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outputs = llm.generate(prompts, sampling_params=single_sampling_params)
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assert len(prompts) == len(outputs)
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# sampling_params is None, default params should be applied
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outputs = llm.generate(prompts, sampling_params=None)
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assert len(prompts) == len(outputs) |