vllm/tests/compile/test_basic_correctness.py

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from typing import Dict, List, Optional
import pytest
from vllm.compilation.levels import CompilationLevel
from vllm.utils import cuda_device_count_stateless
from ..utils import compare_all_settings
# we cannot afford testing the full Catesian product
# of all models and all levels
@pytest.mark.parametrize(
"model, model_args, pp_size, tp_size, attn_backend, method, fullgraph",
[
("meta-llama/Llama-3.2-1B", [], 2, 2, "FLASHINFER", "generate", True),
("nm-testing/Meta-Llama-3-8B-Instruct-W8A8-Dyn-Per-Token-2048-Samples",
["--quantization", "compressed-tensors"
], 1, 1, "FLASH_ATTN", "generate", True),
("ibm/PowerMoE-3b", [], 1, 2, "FLASH_ATTN", "generate", True),
# TODO: add multi-modality test for llava
("llava-hf/llava-1.5-7b-hf", [], 2, 1, "FLASHINFER", "generate", False)
])
def test_compile_correctness(model, model_args, pp_size, tp_size, attn_backend,
method, fullgraph):
# this test is run under multiple suits, with different GPUs.
# make sure we only run the test with correct CUDA devices.
# don't use "<", as it will duplicate the tests.
if cuda_device_count_stateless() != pp_size * tp_size:
pytest.skip("Not correct CUDA devices for the test.")
import os
os.environ["VLLM_ATTENTION_BACKEND"] = attn_backend
all_args = [["--enforce-eager"] + model_args + ["-pp", str(pp_size)] +
["-tp", str(tp_size)]] * 3
# don't test VLLM_TORCH_COMPILE_LEVEL == 3 case
# inductor will change the output, so we cannot compare them.
all_envs: List[Optional[Dict[str, str]]] = []
for level in [
CompilationLevel.NO_COMPILATION,
CompilationLevel.DYNAMO_AS_IS,
CompilationLevel.DYNAMO_ONCE,
]:
all_envs.append({"VLLM_TORCH_COMPILE_LEVEL": str(level)})
if level != CompilationLevel.DYNAMO_ONCE and not fullgraph:
# "DYNAMO_ONCE" will always use fullgraph
all_envs[-1][
"VLLM_TEST_DYNAMO_FULLGRAPH_CAPTURE"] = "0" # type: ignore
compare_all_settings(model, all_args, all_envs, method=method)