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2023-09-01 11:19:43 +09:00
"""Compare the outputs of HF and vLLM when using greedy sampling.
This test only tests small models. Big models such as 7B should be tested from
test_big_models.py because it could use a larger instance to run tests.
Run `pytest tests/models/test_models.py`.
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"""
import pytest
from vllm.platforms import current_platform
from ...utils import check_logprobs_close
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MODELS = [
"facebook/opt-125m", # opt
"openai-community/gpt2", # gpt2
# "Milos/slovak-gpt-j-405M", # gptj
# "bigcode/tiny_starcoder_py", # gpt_bigcode
# "EleutherAI/pythia-70m", # gpt_neox
"bigscience/bloom-560m", # bloom - testing alibi slopes
"microsoft/phi-2", # phi
# "stabilityai/stablelm-3b-4e1t", # stablelm
# "bigcode/starcoder2-3b", # starcoder2
"google/gemma-1.1-2b-it", # gemma
"Qwen/Qwen2.5-0.5B-Instruct", # qwen2
"meta-llama/Llama-3.2-1B-Instruct", # llama
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]
if not current_platform.is_cpu():
MODELS += [
# fused_moe which not supported on CPU
"openbmb/MiniCPM3-4B",
]
target_dtype = "half"
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@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("dtype", [target_dtype])
@pytest.mark.parametrize("max_tokens", [32])
@pytest.mark.parametrize("num_logprobs", [5])
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def test_models(
hf_runner,
vllm_runner,
example_prompts,
model: str,
dtype: str,
max_tokens: int,
num_logprobs: int,
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) -> None:
with hf_runner(model, dtype=dtype) as hf_model:
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
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with vllm_runner(model, dtype=dtype) as vllm_model:
vllm_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
# This test is for verifying whether the model's extra_repr
# can be printed correctly.
print(vllm_model.model.llm_engine.model_executor.driver_worker.
model_runner.model)
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check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_outputs,
name_0="hf",
name_1="vllm",
)