frozenleaves/vllm-dev
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

[V0 Deprecation] Remove V0 FlashInfer attention backend (#22776)

Browse Source 
Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
This commit is contained in:
Woosuk Kwon
2025-08-18 19:54:16 -07:00
committed by GitHub
parent 6603288736
commit 14006840ea
8 changed files with 9 additions and 1133 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
tests/basic_correctness/test_basic_correctness.py
View File

@ -12,7 +12,6 @@ import pytest
import torch
from vllm import LLM, envs
from vllm.platforms import current_platform
from vllm.v1.engine.llm_engine import LLMEngine as LLMEngineV1
from ..conftest import HfRunner, VllmRunner
@ -78,11 +77,7 @@ def test_models(
"VLLM_USE_V1") and envs.VLLM_USE_V1:
pytest.skip("enable_prompt_embeds is not supported in v1.")
if backend == "FLASHINFER" and current_platform.is_rocm():
pytest.skip("Flashinfer does not support ROCm/HIP.")
if backend in ("XFORMERS",
"FLASHINFER") and model == "google/gemma-2-2b-it":
if backend == "XFORMERS" and model == "google/gemma-2-2b-it":
pytest.skip(
f"{backend} does not support gemma2 with full context length.")
@ -141,8 +136,6 @@ def test_models(
("meta-llama/Llama-3.2-1B-Instruct", "mp", "", "L4", {}),
("distilbert/distilgpt2", "ray", "", "A100", {}),
("distilbert/distilgpt2", "mp", "", "A100", {}),
("distilbert/distilgpt2", "mp", "FLASHINFER", "A100", {}),
("meta-llama/Meta-Llama-3-8B", "ray", "FLASHINFER", "A100", {}),
])
@pytest.mark.parametrize("enable_prompt_embeds", [True, False])
def test_models_distributed(

2
tests/compile/test_basic_correctness.py
View File

@ -34,7 +34,7 @@ class TestSetting:
model_args=["--max-model-len", "2048"],
pp_size=2,
tp_size=2,
attn_backend="FLASHINFER",
attn_backend="FLASH_ATTN",
method="generate",
fullgraph=True,
),

8
tests/core/block/e2e/test_correctness_sliding_window.py
View File

@ -32,7 +32,7 @@ BLOCK_SIZE = 16
@pytest.mark.parametrize("test_llm_kwargs", [{}])
@pytest.mark.parametrize("batch_size", [5])
@pytest.mark.parametrize("seed", [1])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "FLASHINFER", "XFORMERS"])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "XFORMERS"])
def test_sliding_window_retrieval(baseline_llm_generator, test_llm_generator,
batch_size, seed, backend, monkeypatch):
"""
@ -43,8 +43,6 @@ def test_sliding_window_retrieval(baseline_llm_generator, test_llm_generator,
Additionally, we compare the results of the v1 and v2 managers.
"""
if backend == "FLASHINFER" and current_platform.is_rocm():
pytest.skip("Flashinfer does not support ROCm/HIP.")
if backend == "XFORMERS" and current_platform.is_rocm():
pytest.skip("Xformers does not support ROCm/HIP.")
@ -96,7 +94,7 @@ def test_sliding_window_retrieval(baseline_llm_generator, test_llm_generator,
@pytest.mark.parametrize("test_llm_kwargs", [{"enable_chunked_prefill": True}])
@pytest.mark.parametrize("batch_size", [5])
@pytest.mark.parametrize("seed", [1])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "FLASHINFER", "XFORMERS"])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "XFORMERS"])
def test_sliding_window_chunked_prefill(test_llm_generator, batch_size, seed,
backend, monkeypatch):
"""
@ -107,8 +105,6 @@ def test_sliding_window_chunked_prefill(test_llm_generator, batch_size, seed,
The results with and without chunked prefill are not the same due to
numerical instabilities.
"""
if backend == "FLASHINFER" and current_platform.is_rocm():
pytest.skip("Flashinfer does not support ROCm/HIP.")
if backend == "XFORMERS" and current_platform.is_rocm():
pytest.skip("Xformers does not support ROCm/HIP.")
override_backend_env_variable(monkeypatch, backend)

1
tests/distributed/test_pp_cudagraph.py
View File

@ -17,7 +17,6 @@ if TYPE_CHECKING:
])
@pytest.mark.parametrize("ATTN_BACKEND", [
"FLASH_ATTN",
"FLASHINFER",
])
@create_new_process_for_each_test()
def test_pp_cudagraph(

3
tests/kernels/attention/test_attention_selector.py
View File

@ -81,6 +81,9 @@ def test_env(
m.setenv(STR_BACKEND_ENV_VAR, name)
m.setenv("VLLM_MLA_DISABLE", "1" if use_mla else "0")
if name == "FLASHINFER" and not use_v1:
pytest.skip("FlashInfer backend is only available on V1 engine")
if device == "cpu":
if not use_v1:
pytest.skip("CPU backend only supports V1")

5
tests/models/quantization/test_fp8.py
View File

@ -32,7 +32,7 @@ from ..utils import check_logprobs_close
# Due to low-precision numerical divergence, we only test logprob of 4 tokens
@pytest.mark.parametrize("max_tokens", [4])
@pytest.mark.parametrize("enforce_eager", [True])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "XFORMERS", "FLASHINFER"])
@pytest.mark.parametrize("backend", ["FLASH_ATTN", "XFORMERS"])
# NOTE: Increasing this in this suite will fail CI because we currently cannot
# reset distributed env properly. Use a value > 1 just when you test.
@pytest.mark.parametrize("tensor_parallel_size", [1])
@ -57,9 +57,6 @@ def test_models(
numerical sensitive kernels.
"""
if backend == "FLASHINFER" and current_platform.is_rocm():
pytest.skip("Flashinfer does not support ROCm/HIP.")
if kv_cache_dtype == "fp8_e5m2" and current_platform.is_rocm():
pytest.skip(
f"{kv_cache_dtype} is currently not supported on ROCm/HIP.")

1098
vllm/attention/backends/flashinfer.py
View File

File diff suppressed because it is too large Load Diff

16
vllm/platforms/cuda.py
View File

@ -350,17 +350,7 @@ class CudaPlatformBase(Platform):
return FLEX_ATTENTION_V1
# Backends for V0 engine
if selected_backend == _Backend.FLASHINFER:
logger.info("Using FlashInfer backend.")
if cls.has_device_capability(100):
from vllm.v1.attention.backends.utils import (
set_kv_cache_layout)
logger.info_once(
"Using HND KV cache layout on V1 engine by default for "
"Blackwell (SM 10.0) GPUs.")
set_kv_cache_layout("HND")
return "vllm.attention.backends.flashinfer.FlashInferBackend"
elif selected_backend == _Backend.XFORMERS:
if selected_backend == _Backend.XFORMERS:
logger.info("Using XFormers backend.")
return "vllm.attention.backends.xformers.XFormersBackend"
elif selected_backend == _Backend.DUAL_CHUNK_FLASH_ATTN:
@ -416,10 +406,6 @@ class CudaPlatformBase(Platform):
if (fp8_kv_cache and not flash_attn_supports_fp8()):
logger.info(
"Cannot use FlashAttention backend for FP8 KV cache.")
logger.warning(
"Please use FlashInfer backend with FP8 KV Cache for "
"better performance by setting environment variable "
"VLLM_ATTENTION_BACKEND=FLASHINFER")
target_backend = _Backend.XFORMERS
except ImportError:
logger.info(