[V0 deprecation] Remove VLLM_USE_V1 usage in config module (#27784)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-10-30 17:42:49 +08:00
committed by GitHub
parent e806178d2a
commit af826e0820
4 changed files with 9 additions and 62 deletions

View File

@@ -32,7 +32,6 @@ from vllm.transformers_utils.config import (
get_pooling_config,
get_sentence_transformer_tokenizer_config,
is_encoder_decoder,
is_interleaved,
try_get_dense_modules,
try_get_generation_config,
try_get_safetensors_metadata,
@@ -442,15 +441,12 @@ class ModelConfig:
self.enforce_eager = True
# Set the default seed to 0 in V1.
# NOTE(woosuk): In V0, we set the default seed to None because the
# driver worker shares the same process as the user process, and thus
# setting a seed affects the user process as well.
# In V1, we use separate processes for workers (unless
# NOTE(woosuk): In V1, we use separate processes for workers (unless
# VLLM_ENABLE_V1_MULTIPROCESSING=0), so setting a seed here
# doesn't affect the user process. However, without a consistent seed,
# different tensor parallel workers would sample different tokens,
# leading to inconsistent results.
if envs.VLLM_USE_V1 and self.seed is None:
if self.seed is None:
self.seed = 0
if not envs.VLLM_ENABLE_V1_MULTIPROCESSING:
logger.warning(
@@ -703,23 +699,6 @@ class ModelConfig:
revision=self.revision,
)
# Interleaved attention is not supported by some backends in V0
if (
not self.disable_sliding_window
and is_interleaved(self.hf_text_config)
and not envs.VLLM_USE_V1
and (backend := envs.VLLM_ATTENTION_BACKEND) in ("XFORMERS", "FLASHINFER")
):
logger.warning_once(
"%s has interleaved attention, which is currently not "
"supported by the %s backend. Disabling sliding window and "
"capping the max length to the sliding window size (%d).",
self.hf_text_config.model_type,
backend,
self.hf_text_config.sliding_window,
)
self.disable_sliding_window = True
self.original_max_model_len = self.max_model_len
self.max_model_len = self.get_and_verify_max_len(self.max_model_len)
# Init multimodal config if needed