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[refactor] Remove unnecessary attributes from set_ascend_forward_context (#5204)

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### What this PR does / why we need it?
Remove unnecessary attributes from set_ascend_forward_context
1.prefetch_stream
2.weight_prefetch_method
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: Wang Kunpeng <1289706727@qq.com>
This commit is contained in:
Wang Kunpeng
2025-12-23 08:49:52 +08:00
committed by GitHub
parent 95e8a52156
commit c3a8d13ca7
10 changed files with 55 additions and 83 deletions
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20
vllm_ascend/worker/model_runner_v1.py
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@@ -82,7 +82,6 @@ from vllm.v1.worker.gpu_model_runner import (AsyncGPUModelRunnerOutput,
from vllm.v1.worker.kv_connector_model_runner_mixin import KVConnectorOutput
from vllm.v1.worker.utils import AttentionGroup
import vllm_ascend.envs as envs_ascend
from vllm_ascend.ascend_config import get_ascend_config
from vllm_ascend.attention.attention_mask import AttentionMaskBuilder
from vllm_ascend.attention.attention_v1 import AscendAttentionState
@@ -106,7 +105,6 @@ from vllm_ascend.eplb.core.eplb_worker import EplbProcess
from vllm_ascend.eplb.eplb_updator import EplbUpdator
from vllm_ascend.eplb.utils import model_register
from vllm_ascend.ops.rotary_embedding import set_cos_and_sin, update_cos_sin
from vllm_ascend.ops.weight_prefetch import WeightPrefetchMethod
from vllm_ascend.patch.worker.patch_module import patch_torch_npu_argsort
from vllm_ascend.sample.logits_processor import build_logitsprocs
from vllm_ascend.sample.sampler import AscendSampler
@@ -115,7 +113,8 @@ from vllm_ascend.spec_decode.eagle_proposer import EagleProposer
from vllm_ascend.spec_decode.mtp_proposer import MtpProposer
from vllm_ascend.utils import (AscendDeviceType, ProfileExecuteDuration,
enable_sp, get_ascend_device_type, is_moe_model,
lmhead_tp_enable, maybe_trans_nz)
lmhead_tp_enable, maybe_trans_nz,
set_weight_prefetch_method)
from vllm_ascend.worker.npu_input_batch import NPUInputBatch
from vllm_ascend.ascend_forward_context import ( # isort: skip
@@ -209,18 +208,13 @@ class NPUModelRunner(GPUModelRunner):
self.pcp_rank = 0
if self.pcp_size > 1:
self.model_config.max_model_len += 2 * self.pcp_size * self.max_num_reqs
if envs_ascend.VLLM_ASCEND_ENABLE_PREFETCH_MLP:
self.prefetch_stream = torch.npu.Stream(device=device)
else:
self.prefetch_stream = None
self.sampler = AscendSampler()
self.attn_mask = None
self.attn_state = None
# Ascend-specific configurations
self.ascend_config = get_ascend_config()
self.weight_prefetch_method = WeightPrefetchMethod(
self.ascend_config.weight_prefetch_config)
set_weight_prefetch_method(self.ascend_config.weight_prefetch_config)
# Dump / PrecisionDebugger configuration now comes from AscendConfig
dump_cfg = self.ascend_config.dump_config
self.dump_enable = dump_cfg.enable_dump
@@ -1420,9 +1414,7 @@ class NPUModelRunner(GPUModelRunner):
batch_descriptor=batch_descriptor,
num_actual_tokens=scheduler_output.
total_num_scheduled_tokens,
prefetch_stream=self.prefetch_stream,
model_instance=self.model,
weight_prefetch_method=self.weight_prefetch_method):
model_instance=self.model):
self.maybe_setup_kv_connector(scheduler_output)
hidden_states = self._generate_process_reqs_hidden_states(
@@ -2133,9 +2125,7 @@ class NPUModelRunner(GPUModelRunner):
num_actual_tokens=0,
aclgraph_runtime_mode=aclgraph_runtime_mode,
batch_descriptor=batch_descriptor,
prefetch_stream=self.prefetch_stream,
model_instance=self.model,
weight_prefetch_method=self.weight_prefetch_method):
model_instance=self.model):
hidden_states = self._generate_dummy_run_hidden_states(
input_ids, positions, num_tokens_padded,
intermediate_tensors, inputs_embeds)