mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2025-12-11 07:54:57 +08:00
3cb07a36a2
Signed-off-by: Bill Nell <bill@neuralmagic.com> Signed-off-by: youkaichao <youkaichao@gmail.com> Co-authored-by: youkaichao <youkaichao@gmail.com>
94 lines
2.9 KiB
Python
94 lines
2.9 KiB
Python
"""Compare the outputs of HF and vLLM when using greedy sampling.
|
|
|
|
This tests bigger models and use half precision.
|
|
|
|
Run `pytest tests/models/test_big_models.py`.
|
|
"""
|
|
import pytest
|
|
|
|
from vllm.platforms import current_platform
|
|
|
|
from ...utils import check_logprobs_close, check_outputs_equal
|
|
|
|
MODELS = [
|
|
"meta-llama/Llama-2-7b-hf",
|
|
# "mistralai/Mistral-7B-v0.1", # Tested by test_mistral.py
|
|
# "Deci/DeciLM-7b", # Broken
|
|
# "tiiuae/falcon-7b", # Broken
|
|
"EleutherAI/gpt-j-6b",
|
|
# "mosaicml/mpt-7b", # Broken
|
|
# "Qwen/Qwen1.5-0.5B" # Broken,
|
|
]
|
|
|
|
if not current_platform.is_cpu():
|
|
MODELS += [
|
|
# fused_moe which not supported on CPU
|
|
"openbmb/MiniCPM3-4B",
|
|
# Head size isn't supported on CPU
|
|
"h2oai/h2o-danube3-4b-base",
|
|
]
|
|
|
|
# TODO: remove this after CPU float16 support ready
|
|
target_dtype = "float" if current_platform.is_cpu() else "half"
|
|
|
|
|
|
@pytest.mark.parametrize("model", MODELS)
|
|
@pytest.mark.parametrize("dtype", [target_dtype])
|
|
@pytest.mark.parametrize("max_tokens", [32])
|
|
def test_models(
|
|
hf_runner,
|
|
vllm_runner,
|
|
example_prompts,
|
|
model: str,
|
|
dtype: str,
|
|
max_tokens: int,
|
|
) -> None:
|
|
|
|
if model == "openbmb/MiniCPM3-4B":
|
|
# the output becomes slightly different when upgrading to
|
|
# pytorch 2.5 . Changing to logprobs checks instead of exact
|
|
# output checks.
|
|
NUM_LOG_PROBS = 8
|
|
with hf_runner(model, dtype=dtype) as hf_model:
|
|
hf_outputs = hf_model.generate_greedy_logprobs_limit(
|
|
example_prompts, max_tokens, NUM_LOG_PROBS)
|
|
|
|
with vllm_runner(model, dtype=dtype, enforce_eager=True) as vllm_model:
|
|
vllm_outputs = vllm_model.generate_greedy_logprobs(
|
|
example_prompts, max_tokens, NUM_LOG_PROBS)
|
|
|
|
check_logprobs_close(
|
|
outputs_0_lst=hf_outputs,
|
|
outputs_1_lst=vllm_outputs,
|
|
name_0="hf",
|
|
name_1="vllm",
|
|
)
|
|
else:
|
|
with hf_runner(model, dtype=dtype) as hf_model:
|
|
hf_outputs = hf_model.generate_greedy(example_prompts, max_tokens)
|
|
|
|
with vllm_runner(model, dtype=dtype, enforce_eager=True) as vllm_model:
|
|
vllm_outputs = vllm_model.generate_greedy(example_prompts,
|
|
max_tokens)
|
|
|
|
check_outputs_equal(
|
|
outputs_0_lst=hf_outputs,
|
|
outputs_1_lst=vllm_outputs,
|
|
name_0="hf",
|
|
name_1="vllm",
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize("model", MODELS)
|
|
@pytest.mark.parametrize("dtype", [target_dtype])
|
|
def test_model_print(
|
|
vllm_runner,
|
|
model: str,
|
|
dtype: str,
|
|
) -> None:
|
|
with vllm_runner(model, dtype=dtype, enforce_eager=True) as vllm_model:
|
|
# 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)
|