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[BugFix] Fix VllmConfig() construction on all platforms (#20695)

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Signed-off-by: Nick Hill <nhill@redhat.com>
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Nick Hill 2025-07-10 08:00:20 +01:00 committed by GitHub
parent 59389c927b
commit ffbcc9e757
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5 changed files with 19 additions and 16 deletions
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1
vllm/config.py
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@ -4722,7 +4722,6 @@ class VllmConfig:
# calculate the default `batch_size_capture_list`
if not envs.VLLM_USE_V1:
batch_size_capture_list = []
max_batchsize_to_capture = 0
if self.scheduler_config is not None and \
self.model_config is not None and \
not self.model_config.enforce_eager:

7
vllm/platforms/cpu.py
View File

@ -96,7 +96,8 @@ class CpuPlatform(Platform):
from vllm.utils import GiB_bytes
model_config = vllm_config.model_config
model_config.disable_cascade_attn = True
if model_config is not None:
model_config.disable_cascade_attn = True
cache_config = vllm_config.cache_config
@ -123,7 +124,7 @@ class CpuPlatform(Platform):
"CPU backend doesn't support fp8_e4m3 KV cache type, "
"cast to fp8_e5m2.")
if (cache_config.cache_dtype != "auto"
if (cache_config.cache_dtype != "auto" and model_config is not None
and model_config.dtype == torch.half):
logger.warning("FP8 KV cache on the CPU backend only does not"
" support fp16 for now, cast to bf16.")
@ -229,7 +230,7 @@ class CpuPlatform(Platform):
os.environ["LOCAL_WORLD_SIZE"] = str(
vllm_config.parallel_config.tensor_parallel_size)
if vllm_config.model_config and vllm_config.model_config.use_mla:
if model_config is not None and model_config.use_mla:
logger.info(
"MLA is enabled on a non-GPU platform; forcing chunked "
"prefill and prefix caching to be disabled.")

8
vllm/platforms/cuda.py
View File

@ -166,17 +166,19 @@ class CudaPlatformBase(Platform):
logger.info(
"Forcing kv cache block size to 64 for FlashMLA backend.")
compilation_config = vllm_config.compilation_config
if (envs.VLLM_ALL2ALL_BACKEND == "deepep_high_throughput"
and parallel_config.data_parallel_size > 1
and vllm_config.compilation_config.use_cudagraph):
and compilation_config.use_cudagraph):
logger.info(
"Data Parallel: Forcing enforce eager to be True since DP "
"with DeepEP high-throughput kernels are not CUDA Graph "
"compatible. The DeepEP low-latency kernels are CUDA Graph "
"compatible. Set the all_to_all backend to deepep_low_latency "
"to use those kernels instead.")
vllm_config.compilation_config.use_cudagraph = False
vllm_config.model_config.enforce_eager = True
compilation_config.use_cudagraph = False
if model_config is not None:
model_config.enforce_eager = True
# TODO (varun): Turning this ON gives incorrect results for the
# Deepseek-V2-lite model.
vllm_config.compilation_config.use_inductor = False

10
vllm/platforms/tpu.py
View File

@ -116,11 +116,13 @@ class TpuPlatform(Platform):
assert vllm_config.speculative_config is None, \
"TPU does not support speculative decoding"
if vllm_config.model_config.dtype in (torch.float16, torch.float32):
model_config = vllm_config.model_config
if model_config is not None and model_config.dtype in (torch.float16,
torch.float32):
logger.warning(
"The TPU backend currently does not support %s. "
"Using bfloat16 instead.", vllm_config.model_config.dtype)
vllm_config.model_config.dtype = torch.bfloat16
"Using bfloat16 instead.", model_config.dtype)
model_config.dtype = torch.bfloat16
from vllm.v1.attention.backends.pallas import PallasAttentionBackend
cache_config.block_size = PallasAttentionBackend.get_page_size(
@ -146,7 +148,7 @@ class TpuPlatform(Platform):
"Forcing --disable_chunked_mm_input.")
scheduler_config.disable_chunked_mm_input = True
if vllm_config.model_config and vllm_config.model_config.use_mla:
if model_config and model_config.use_mla:
logger.info(
"MLA is enabled on a non-GPU platform; forcing chunked "
"prefill and prefix caching to be disabled.")

9
vllm/platforms/xpu.py
View File

@ -85,14 +85,14 @@ class XPUPlatform(Platform):
@classmethod
def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
cache_config = vllm_config.cache_config
model_config = vllm_config.model_config
# in V1(or with ipex chunked prefill) block_size is 64
if cache_config and cache_config.block_size is None:
cache_config.block_size = 64
# FIXME: Temporarily forcing eager mode
# remove after t.compile support stabilizes.
if (envs.VLLM_USE_V1 and vllm_config.model_config is not None
if (envs.VLLM_USE_V1 and model_config is not None
and not vllm_config.model_config.enforce_eager):
from vllm.config import CompilationLevel
vllm_config.compilation_config.level = CompilationLevel.NO_COMPILATION # noqa: E501
@ -100,8 +100,7 @@ class XPUPlatform(Platform):
# Instances created using VllmConfig() typically have model_config as
# None by default. The modification involves adding a check to prevent
# potential null exceptions check and update model config.
if vllm_config.model_config is not None:
model_config = vllm_config.model_config
if model_config is not None:
if model_config.dtype == torch.bfloat16:
bf16_supported = cls.device_support_bf16()
if not bf16_supported:
@ -139,7 +138,7 @@ class XPUPlatform(Platform):
parallel_config.distributed_executor_backend)
parallel_config.distributed_executor_backend = "ray"
if vllm_config.model_config and vllm_config.model_config.use_mla:
if model_config and model_config.use_mla:
logger.info(
"MLA is enabled on a non-GPU platform; forcing chunked "
"prefill and prefix caching to be disabled.")