66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
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"""Compare the outputs of HF and vLLM when using greedy sampling.
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It tests chunked prefill. Chunked prefill can be enabled by
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enable_chunked_prefill=True. If prefill size exceeds max_num_batched_tokens,
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prefill requests are chunked.
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Run `pytest tests/models/test_chunked_prefill.py`.
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"""
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import pytest
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MODELS = [
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"facebook/opt-125m",
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"meta-llama/Llama-2-7b-hf",
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]
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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", [32])
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@pytest.mark.parametrize("chunked_prefill_token_size", [1, 4, 16])
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@pytest.mark.parametrize("enforce_eager", [False, True])
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# NOTE: Increasing this in this suite will fail CI because we currently cannot
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# reset distributed env properly. Use a value > 1 just when you test.
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@pytest.mark.parametrize("tensor_parallel_size", [1])
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def test_models(
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hf_runner,
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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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chunked_prefill_token_size: int,
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enforce_eager: bool,
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tensor_parallel_size: int,
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) -> None:
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max_num_seqs = min(chunked_prefill_token_size, 256)
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enable_chunked_prefill = False
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max_num_batched_tokens = None
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if chunked_prefill_token_size != -1:
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enable_chunked_prefill = True
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max_num_batched_tokens = chunked_prefill_token_size
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hf_model = hf_runner(model, dtype=dtype)
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hf_outputs = hf_model.generate_greedy(example_prompts, max_tokens)
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del hf_model
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vllm_model = vllm_runner(
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model,
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dtype=dtype,
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max_num_batched_tokens=max_num_batched_tokens,
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enable_chunked_prefill=enable_chunked_prefill,
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tensor_parallel_size=tensor_parallel_size,
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enforce_eager=enforce_eager,
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max_num_seqs=max_num_seqs,
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)
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vllm_outputs = vllm_model.generate_greedy(example_prompts, max_tokens)
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del vllm_model
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for i in range(len(example_prompts)):
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hf_output_ids, hf_output_str = hf_outputs[i]
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vllm_output_ids, vllm_output_str = vllm_outputs[i]
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assert hf_output_str == vllm_output_str, (
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f"Test{i}:\nHF: {hf_output_str!r}\nvLLM: {vllm_output_str!r}")
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assert hf_output_ids == vllm_output_ids, (
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f"Test{i}:\nHF: {hf_output_ids}\nvLLM: {vllm_output_ids}")
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