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Upgrade to 0.11.1 newest vllm commit (#3762)

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### What this PR does / why we need it?

c9461e05a4

Fix ```spec decode rejection sampler```, caused by
https://github.com/vllm-project/vllm/pull/26060
Fix some ```import```, caused by
https://github.com/vllm-project/vllm/pull/27374
Fix ```scheduler_config.send_delta_data```, caused by
https://github.com/vllm-project/vllm-ascend/pull/3719
Fix ```init_with_cudagraph_sizes```, caused by
https://github.com/vllm-project/vllm/pull/26016
Fix ```vl model```of replacing PatchEmbed's conv3d to linear layer,
caused by https://github.com/vllm-project/vllm/pull/27418

### Does this PR introduce _any_ user-facing change?
N/A

### How was this patch tested?
CI passed with new added/existing test.


- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4

---------

Signed-off-by: Icey <1790571317@qq.com>
This commit is contained in:
Icey
2025-10-28 14:55:03 +08:00
committed by GitHub
parent f846bd20e4
commit a7450db1bd
12 changed files with 175 additions and 51 deletions
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70
vllm_ascend/platform.py
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@@ -33,7 +33,8 @@ from vllm_ascend.torchair.utils import (check_torchair_cache_exist,
delete_torchair_cache_file)
from vllm_ascend.utils import (ASCEND_QUANTIZATION_METHOD, enable_sp, is_310p,
prefill_context_parallel_enable,
update_aclgraph_sizes, vllm_version_is)
update_aclgraph_sizes,
update_cudagraph_capture_sizes, vllm_version_is)
if TYPE_CHECKING:
from vllm.config import ModelConfig, VllmConfig
@@ -142,24 +143,47 @@ class NPUPlatform(Platform):
"Non-MLA LLMs forcibly disable the chunked prefill feature,"
"as the performance of operators supporting this feature "
"functionality is currently suboptimal.")
if not model_config.is_multimodal_model and \
structured_outputs_config.backend == "auto" and \
not getattr(scheduler_config, "scheduler_delay_factor", 0) > 0 and \
scheduler_config.policy == "fcfs":
ascend_scheduler_config.enabled = True
chunked_prefill_enabled_in_ascend_scheduler = getattr(
ascend_scheduler_config, "enable_chunked_prefill", False)
if chunked_prefill_enabled_in_ascend_scheduler:
logger.warning(
"Chunked prefill feature is enabled in ascend_scheduler,"
"but note that the operator supporting this feature "
"would lead to performance degradation.")
# In this situation, max_num_batched_tokens would have been rewritten.
# So we must make sure max_num_batched_tokens is not smaller than max_model_len.
if (scheduler_config.max_num_batched_tokens
< scheduler_config.max_model_len
and not chunked_prefill_enabled_in_ascend_scheduler):
scheduler_config.max_num_batched_tokens = scheduler_config.max_model_len
if vllm_version_is("0.11.0"):
if not model_config.is_multimodal_model and \
structured_outputs_config.backend == "auto" and \
not scheduler_config.send_delta_data and \
not getattr(scheduler_config, "scheduler_delay_factor", 0) > 0 and \
scheduler_config.policy == "fcfs":
ascend_scheduler_config.enabled = True
chunked_prefill_enabled_in_ascend_scheduler = getattr(
ascend_scheduler_config, "enable_chunked_prefill",
False)
if chunked_prefill_enabled_in_ascend_scheduler:
logger.warning(
"Chunked prefill feature is enabled in ascend_scheduler,"
"but note that the operator supporting this feature "
"would lead to performance degradation.")
# In this situation, max_num_batched_tokens would have been rewritten.
# So we must make sure max_num_batched_tokens is not smaller than max_model_len.
if (scheduler_config.max_num_batched_tokens
< scheduler_config.max_model_len and
not chunked_prefill_enabled_in_ascend_scheduler):
scheduler_config.max_num_batched_tokens = scheduler_config.max_model_len
else:
if not model_config.is_multimodal_model and \
structured_outputs_config.backend == "auto" and \
not getattr(scheduler_config, "scheduler_delay_factor", 0) > 0 and \
scheduler_config.policy == "fcfs":
ascend_scheduler_config.enabled = True
chunked_prefill_enabled_in_ascend_scheduler = getattr(
ascend_scheduler_config, "enable_chunked_prefill",
False)
if chunked_prefill_enabled_in_ascend_scheduler:
logger.warning(
"Chunked prefill feature is enabled in ascend_scheduler,"
"but note that the operator supporting this feature "
"would lead to performance degradation.")
# In this situation, max_num_batched_tokens would have been rewritten.
# So we must make sure max_num_batched_tokens is not smaller than max_model_len.
if (scheduler_config.max_num_batched_tokens
< scheduler_config.max_model_len and
not chunked_prefill_enabled_in_ascend_scheduler):
scheduler_config.max_num_batched_tokens = scheduler_config.max_model_len
kv_cache_dtype = vllm_config.additional_config.get(
"kv_cache_dtype", None)
@@ -237,8 +261,12 @@ class NPUPlatform(Platform):
f"{vllm_config.parallel_config.tensor_parallel_size}")
if len(sp_aclgraph_sizes) != len(original_sizes):
compilation_config.cudagraph_capture_sizes = sp_aclgraph_sizes
vllm_config.compilation_config.init_with_cudagraph_sizes(
sp_aclgraph_sizes)
if vllm_version_is("0.11.0"):
compilation_config.init_with_cudagraph_sizes(
sp_aclgraph_sizes)
else:
update_cudagraph_capture_sizes(vllm_config,
sp_aclgraph_sizes)
# TODO: Full graph is fully supported later, and the default value will be set to full graph.
if compilation_config.cudagraph_mode == CUDAGraphMode.FULL_AND_PIECEWISE: