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[Misc] Avoid unnecessary import (#21106)

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Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
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wangxiyuan 2025-07-17 20:57:41 +08:00 committed by GitHub
parent fe8a2c544a
commit 89e3c4e9b4
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2 changed files with 13 additions and 9 deletions
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2
vllm/entrypoints/openai/speech_to_text.py
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@ -24,7 +24,6 @@ from vllm.entrypoints.openai.serving_engine import (OpenAIServing,
from vllm.entrypoints.openai.serving_models import OpenAIServingModels from vllm.entrypoints.openai.serving_models import OpenAIServingModels
from vllm.inputs.data import PromptType from vllm.inputs.data import PromptType
from vllm.logger import init_logger from vllm.logger import init_logger
from vllm.model_executor.model_loader import get_model_cls
from vllm.model_executor.models import SupportsTranscription from vllm.model_executor.models import SupportsTranscription
from vllm.outputs import RequestOutput from vllm.outputs import RequestOutput
from vllm.utils import PlaceholderModule from vllm.utils import PlaceholderModule
@ -78,6 +77,7 @@ class OpenAISpeechToText(OpenAIServing):
@cached_property @cached_property
def model_cls(self) -> type[SupportsTranscription]: def model_cls(self) -> type[SupportsTranscription]:
from vllm.model_executor.model_loader import get_model_cls
model_cls = get_model_cls(self.model_config) model_cls = get_model_cls(self.model_config)
return cast(type[SupportsTranscription], model_cls) return cast(type[SupportsTranscription], model_cls)

20
vllm/lora/utils.py
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@ -2,7 +2,7 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import os import os
from typing import Optional, Union from typing import TYPE_CHECKING, Optional, Union
import huggingface_hub import huggingface_hub
import regex as re import regex as re
@ -31,10 +31,14 @@ from vllm.lora.layers import (BaseLayerWithLoRA, ColumnParallelLinearWithLoRA,
RowParallelLinearWithLoRA, RowParallelLinearWithLoRA,
VocabParallelEmbeddingWithLoRA) VocabParallelEmbeddingWithLoRA)
from vllm.model_executor.layers.linear import LinearBase from vllm.model_executor.layers.linear import LinearBase
# yapf: enable # yapf: enable
from vllm.model_executor.layers.logits_processor import LogitsProcessor
from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead if TYPE_CHECKING:
from vllm.model_executor.models.utils import WeightsMapper from vllm.model_executor.layers.logits_processor import LogitsProcessor
from vllm.model_executor.layers.vocab_parallel_embedding import (
ParallelLMHead)
from vllm.model_executor.models.utils import WeightsMapper
logger = init_logger(__name__) logger = init_logger(__name__)
@ -75,8 +79,8 @@ def from_layer(layer: nn.Module,
def from_layer_logits_processor( def from_layer_logits_processor(
layer: LogitsProcessor, layer: "LogitsProcessor",
lm_head: ParallelLMHead, lm_head: "ParallelLMHead",
max_loras: int, max_loras: int,
lora_config: LoRAConfig, lora_config: LoRAConfig,
model_config: Optional[PretrainedConfig] = None, model_config: Optional[PretrainedConfig] = None,
@ -98,8 +102,8 @@ def replace_submodule(model: nn.Module, module_name: str,
def parse_fine_tuned_lora_name( def parse_fine_tuned_lora_name(
name: str, name: str,
weights_mapper: Optional[WeightsMapper] = None weights_mapper: Optional["WeightsMapper"] = None
) -> tuple[str, bool, bool]: ) -> tuple[str, bool, bool]:
"""Parse the name of lora weights. """Parse the name of lora weights.