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[CI] upgrade vllm to 0.8.5 (#715)

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1. Upgrade vllm to 0.8.5
2. Drop 0.8.4 support
3. Keep doc to 0.8.4rc2 until we release 0.8.5

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-04-30 09:15:50 +08:00
committed by GitHub
parent 95e7aa4736
commit f8350569e6
20 changed files with 48 additions and 579 deletions
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64
vllm_ascend/worker/model_runner_v1.py
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@@ -47,13 +47,13 @@ from vllm.v1.core.encoder_cache_manager import compute_encoder_budget
from vllm.v1.kv_cache_interface import (FullAttentionSpec, KVCacheConfig,
KVCacheSpec)
from vllm.v1.outputs import EMPTY_MODEL_RUNNER_OUTPUT, ModelRunnerOutput
from vllm.v1.sample.sampler import Sampler
from vllm.v1.utils import bind_kv_cache
from vllm.v1.worker.gpu_input_batch import CachedRequestState, InputBatch
from vllm_ascend.attention.attention import AttentionMaskBuilder
from vllm_ascend.attention.attention_v1 import AscendAttentionState
from vllm_ascend.platform import NPUPlatform
from vllm_ascend.utils import vllm_version_is
if TYPE_CHECKING:
import xgrammar as xgr # type: ignore[import-untyped]
@@ -291,11 +291,7 @@ class NPUModelRunner:
self.attn_mask_builder = AttentionMaskBuilder.initialize_from_len(
self.attn_mask_len, self.dtype)
if vllm_version_is("0.8.4"):
self.sampler = None
else:
from vllm.v1.sample.sampler import Sampler
self.sampler = Sampler()
self.sampler = Sampler()
def _update_states(self, scheduler_output: "SchedulerOutput") -> None:
"""Update the cached states and the persistent batch with the scheduler
@@ -346,34 +342,19 @@ class NPUModelRunner:
generator.manual_seed(sampling_params.seed)
else:
generator = None
if vllm_version_is("0.8.4"):
self.requests[req_id] = CachedRequestState(
req_id=req_id,
prompt_token_ids=new_req_data.prompt_token_ids,
prompt=new_req_data.prompt,
mm_inputs=new_req_data.mm_inputs,
mm_positions=new_req_data.mm_positions,
sampling_params=sampling_params,
generator=generator,
block_ids=new_req_data.block_ids,
num_computed_tokens=new_req_data.num_computed_tokens,
output_token_ids=[],
lora_request=new_req_data.lora_request,
)
else:
# the prompt removed by: https://github.com/vllm-project/vllm/pull/17214
self.requests[req_id] = CachedRequestState(
req_id=req_id,
prompt_token_ids=new_req_data.prompt_token_ids,
mm_inputs=new_req_data.mm_inputs,
mm_positions=new_req_data.mm_positions,
sampling_params=sampling_params,
generator=generator,
block_ids=new_req_data.block_ids,
num_computed_tokens=new_req_data.num_computed_tokens,
output_token_ids=[],
lora_request=new_req_data.lora_request,
)
self.requests[req_id] = CachedRequestState(
req_id=req_id,
prompt_token_ids=new_req_data.prompt_token_ids,
mm_inputs=new_req_data.mm_inputs,
mm_positions=new_req_data.mm_positions,
sampling_params=sampling_params,
generator=generator,
block_ids=new_req_data.block_ids,
num_computed_tokens=new_req_data.num_computed_tokens,
output_token_ids=[],
lora_request=new_req_data.lora_request,
)
req_ids_to_add.append(req_id)
@@ -666,17 +647,10 @@ class NPUModelRunner:
# Sample the next token and get logprobs if needed.
sampling_metadata = self.input_batch.sampling_metadata
if vllm_version_is("0.8.4"):
sampler_output = self.model.sample(
logits=logits,
sampling_metadata=sampling_metadata,
)
else:
assert self.sampler is not None
sampler_output = self.sampler(
logits=logits,
sampling_metadata=sampling_metadata,
)
sampler_output = self.sampler(
logits=logits,
sampling_metadata=sampling_metadata,
)
# TODO(woosuk): The following loop can be slow since it iterates over
# the requests one by one. Optimize.