Reapply "[Refactor] Unify full-graph parameter update logic (#6041)" (#6227) (#6231)

This reverts commit 95649344aa.

The CI failure doesn't related to this change. Let's reapply it.

- vLLM version: v0.14.0
- vLLM main:
d68209402d
This commit is contained in:
wangxiyuan
2026-01-26 09:04:54 +08:00
committed by GitHub
parent c38c838d03
commit 4e3919e965
10 changed files with 420 additions and 415 deletions

View File

@@ -84,10 +84,7 @@ from vllm_ascend.attention.utils import AscendCommonAttentionMetadata, using_pag
from vllm_ascend.compilation.acl_graph import (ACLGraphWrapper,
set_draft_graph_params,
set_graph_params,
update_attn_dcp_pcp_params,
update_attn_params,
update_mla_attn_dcp_pcp_params,
update_mla_attn_params)
update_full_graph_params)
# yapf: enable
from vllm_ascend.eplb.adaptor.vllm_adaptor import VllmEplbAdaptor
from vllm_ascend.eplb.core.eplb_device_transfer_loader import \
@@ -1142,26 +1139,9 @@ class NPUModelRunner(GPUModelRunner):
if forward_context.cudagraph_runtime_mode == CUDAGraphMode.FULL \
and not self.use_sparse:
# TODO: maybe_padded_num_tokens will be removed, use num_input_tokens instead
if self.vllm_config.model_config.use_mla:
if self.pcp_size * self.dcp_size > 1:
# FIXME: Try using `auto_dispatch_capture=True`
update_mla_attn_dcp_pcp_params(self.update_stream,
forward_context,
maybe_padded_num_tokens)
else:
# FIXME: Try using `auto_dispatch_capture=True`
update_mla_attn_params(self.update_stream, forward_context,
maybe_padded_num_tokens,
self.speculative_config)
else:
if self.pcp_size * self.dcp_size > 1:
update_attn_dcp_pcp_params(self.update_stream,
forward_context,
maybe_padded_num_tokens)
else:
update_attn_params(self.update_stream, forward_context,
maybe_padded_num_tokens,
self.vllm_config)
update_full_graph_params(self.attn_backend, self.update_stream, forward_context,
maybe_padded_num_tokens, self.vllm_config,
self.vllm_config.speculative_config)
if get_forward_context().sp_enabled and not isinstance(
hidden_states, IntermediateTensors):
@@ -2038,25 +2018,9 @@ class NPUModelRunner(GPUModelRunner):
assert forward_context is not None
if forward_context.cudagraph_runtime_mode == CUDAGraphMode.FULL and \
not forward_context.capturing and not self.use_sparse:
if self.vllm_config.model_config.use_mla:
# FIXME: Try using `auto_dispatch_capture=True`
if self.pcp_size * self.dcp_size > 1:
# FIXME: Try using `auto_dispatch_capture=True`
update_mla_attn_dcp_pcp_params(self.update_stream,
forward_context,
positions.shape[0])
else:
# FIXME: Try using `auto_dispatch_capture=True`
update_mla_attn_params(self.update_stream, forward_context,
num_tokens, self.speculative_config)
else:
if self.pcp_size * self.dcp_size > 1:
update_attn_dcp_pcp_params(self.update_stream,
forward_context,
positions.shape[0])
else:
update_attn_params(self.update_stream, forward_context,
num_tokens, self.vllm_config)
update_full_graph_params(self.attn_backend, self.update_stream, forward_context,
num_tokens, self.vllm_config,
self.speculative_config, positions.shape[0])
if self.use_aux_hidden_state_outputs:
hidden_states, _ = hidden_states
@@ -2899,7 +2863,7 @@ class NPUModelRunner(GPUModelRunner):
attn_layers = get_layers_from_vllm_config(self.vllm_config,
AttentionLayerBase)
# NOTE: Must process Attention/MLAAttention before MambaBase to maintain
# ordering expected by acl_graph.py's _update_attn_fia_params.
# ordering expected by graph parameter update logic in attention backends.
mamba_layers: dict[str, MambaBase] = {}
for layer_name, attn_module in attn_layers.items():
if isinstance(attn_module, Attention):