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[BugFix] Partial revert of #29558 (DeepEP HT + PIECEWISE CG support) (#30910)

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Signed-off-by: Lucas Wilkinson <lwilkins@redhat.com>
Signed-off-by: Lucas Wilkinson <LucasWilkinson@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
Lucas Wilkinson
2025-12-18 02:50:15 -05:00
committed by GitHub
parent aa7e836055
commit 30bb19a760
2 changed files with 14 additions and 74 deletions
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50
vllm/config/compilation.py
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@@ -915,8 +915,6 @@ class CompilationConfig:
"mode is CompilationMode.VLLM_COMPILE"
)
added_default_splitting_ops = False
if self.pass_config.fuse_attn_quant and not self.use_inductor_graph_partition:
self.set_splitting_ops_for_attn_fusion()
else:
@@ -930,7 +928,6 @@ class CompilationConfig:
# for details. Make a copy to avoid mutating the class-level
# list via reference.
self.splitting_ops = list(self._attention_ops)
added_default_splitting_ops = True
elif len(self.splitting_ops) == 0:
if (
self.cudagraph_mode == CUDAGraphMode.PIECEWISE
@@ -958,44 +955,25 @@ class CompilationConfig:
self.cudagraph_mode = CUDAGraphMode.FULL
self.splitting_ops = []
# split MoE ops for cudagraph
moe_ops = [
"vllm::moe_forward",
"vllm::moe_forward_shared",
]
# Disable CUDA graphs for DeepEP high-throughput since its not CG compatible
backend = all2all_backend or envs.VLLM_ALL2ALL_BACKEND
dp_size = data_parallel_size if data_parallel_size is not None else 1
need_moe_splitting = (
if (
backend == "deepep_high_throughput"
and dp_size > 1
# pure attn-fusion without inductor partition deliberately disables
# piecewise graphs and MoE splitting.
and not (
self.pass_config.fuse_attn_quant
and not self.use_inductor_graph_partition
and self.cudagraph_mode != CUDAGraphMode.NONE
):
# TODO: Piecewise Cuda graph might be enabled
# if torch compile cache key issue fixed
# See https://github.com/vllm-project/vllm/pull/25093
logger.info(
"DeepEP: Disabling CUDA Graphs since DeepEP high-throughput kernels "
"are optimized for prefill and are incompatible with CUDA Graphs. "
"In order to use CUDA Graphs for decode-optimized workloads, "
"use --all2all-backend with another option, such as "
"deepep_low_latency, pplx, or allgather_reducescatter."
)
)
if need_moe_splitting and self.cudagraph_mode != CUDAGraphMode.NONE:
# if we just initialized default splitting_ops for this config,
# automatically append the MoE ops
if added_default_splitting_ops:
for op in moe_ops:
if op not in self.splitting_ops:
self.splitting_ops.append(op)
# make sure MoE ops are split out
if not any(op in self.splitting_ops for op in moe_ops):
self.cudagraph_mode = CUDAGraphMode.NONE
logger.warning_once(
"DeepEP high throughput backend with data_parallel_size > 1 "
"requires splitting MoE ops from cudagraphs. Please ensure "
"'vllm::moe_forward' or 'vllm::moe_forward_shared' are "
"present in CompilationConfig.splitting_ops."
)
elif self.cudagraph_mode.has_full_cudagraphs():
# fall back to piecewise when MoE splitting is required.
self.cudagraph_mode = CUDAGraphMode.PIECEWISE
self.cudagraph_mode = CUDAGraphMode.NONE
def set_splitting_ops_for_attn_fusion(self):
assert self.pass_config.fuse_attn_quant