From f6af1d2471b99942d5284d804c10d4cb3c3b38b8 Mon Sep 17 00:00:00 2001 From: wangxiyuan Date: Tue, 15 Apr 2025 10:18:05 +0800 Subject: [PATCH] [MISC] fix logger (#515) logger in vllm-ascend doesn't work. This PR fix the issue. Fix: https://github.com/vllm-project/vllm-ascend/issues/431 Signed-off-by: wangxiyuan --- tests/conftest.py | 3 --- vllm_ascend/platform.py | 4 +--- vllm_ascend/quantization/quant_config.py | 3 --- vllm_ascend/utils.py | 4 +--- vllm_ascend/worker/model_runner.py | 4 +--- vllm_ascend/worker/model_runner_v1.py | 4 +--- vllm_ascend/worker/multi_step_runner.py | 3 --- vllm_ascend/worker/worker.py | 4 +--- vllm_ascend/worker/worker_v1.py | 4 +--- 9 files changed, 6 insertions(+), 27 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index 49f42c7..941e5b5 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -29,7 +29,6 @@ from vllm.config import TaskOption from vllm.distributed.parallel_state import (destroy_distributed_environment, destroy_model_parallel) from vllm.inputs import ExplicitEncoderDecoderPrompt, TextPrompt, TokensPrompt -from vllm.logger import init_logger from vllm.outputs import RequestOutput from vllm.sampling_params import BeamSearchParams from vllm.utils import is_list_of @@ -37,8 +36,6 @@ from vllm.utils import is_list_of from tests.model_utils import (TokensTextLogprobs, TokensTextLogprobsPromptLogprobs) -logger = init_logger(__name__) - _M = TypeVar("_M") _PromptMultiModalInput = Union[List[_M], List[List[_M]]] diff --git a/vllm_ascend/platform.py b/vllm_ascend/platform.py index 8cc8817..7f26bfd 100644 --- a/vllm_ascend/platform.py +++ b/vllm_ascend/platform.py @@ -22,7 +22,7 @@ from typing import TYPE_CHECKING, Optional, Tuple import torch import torch_npu # noqa: F401 import vllm.envs as envs -from vllm.logger import init_logger +from vllm.logger import logger try: # register custom ops into torch_library here @@ -48,8 +48,6 @@ else: os.environ["RAY_EXPERIMENTAL_NOSET_ASCEND_RT_VISIBLE_DEVICES"] = "1" -logger = init_logger(__name__) - class NPUPlatform(Platform): diff --git a/vllm_ascend/quantization/quant_config.py b/vllm_ascend/quantization/quant_config.py index e91ff6b..91feb50 100644 --- a/vllm_ascend/quantization/quant_config.py +++ b/vllm_ascend/quantization/quant_config.py @@ -21,7 +21,6 @@ from typing import Any, Callable, Dict, List, Mapping, Optional import torch import torch_npu # noqa: F401 from vllm.distributed import get_tensor_model_parallel_rank -from vllm.logger import init_logger from vllm.model_executor.layers.fused_moe import (FusedMoE, FusedMoEMethodBase, FusedMoeWeightScaleSupported) from vllm.model_executor.layers.fused_moe.layer import \ @@ -41,8 +40,6 @@ from vllm.model_executor.utils import set_weight_attrs from .quantizer import AscendQuantizer -logger = init_logger(__name__) - @register_quantization_config("ascend") class AscendQuantConfig(QuantizationConfig): diff --git a/vllm_ascend/utils.py b/vllm_ascend/utils.py index 5d4c6be..0b6c69e 100644 --- a/vllm_ascend/utils.py +++ b/vllm_ascend/utils.py @@ -17,9 +17,7 @@ # limitations under the License. # import torch -from vllm.logger import init_logger - -logger = init_logger(__name__) +from vllm.logger import logger def try_register_lib(lib_name: str, lib_info: str = ""): diff --git a/vllm_ascend/worker/model_runner.py b/vllm_ascend/worker/model_runner.py index 8a21792..c6fefe7 100644 --- a/vllm_ascend/worker/model_runner.py +++ b/vllm_ascend/worker/model_runner.py @@ -35,7 +35,7 @@ from vllm.core.scheduler import SchedulerOutputs from vllm.distributed import get_kv_transfer_group, get_pp_group from vllm.forward_context import set_forward_context from vllm.inputs import INPUT_REGISTRY, InputRegistry -from vllm.logger import init_logger +from vllm.logger import logger from vllm.lora.layers import LoRAMapping from vllm.lora.request import LoRARequest from vllm.model_executor import SamplingMetadata, SamplingMetadataCache @@ -63,8 +63,6 @@ from vllm.worker.model_runner_base import ( if TYPE_CHECKING: from vllm.attention.backends.abstract import AttentionBackend -logger = init_logger(__name__) - TModelInputForNPU = TypeVar('TModelInputForNPU', bound="ModelInputForNPU") diff --git a/vllm_ascend/worker/model_runner_v1.py b/vllm_ascend/worker/model_runner_v1.py index a6736c5..ec2b314 100644 --- a/vllm_ascend/worker/model_runner_v1.py +++ b/vllm_ascend/worker/model_runner_v1.py @@ -32,7 +32,7 @@ from vllm.config import VllmConfig from vllm.distributed.parallel_state import get_pp_group from vllm.forward_context import set_forward_context from vllm.inputs import INPUT_REGISTRY -from vllm.logger import init_logger +from vllm.logger import logger from vllm.model_executor.layers.fused_moe import FusedMoE from vllm.model_executor.model_loader import get_model from vllm.multimodal import MULTIMODAL_REGISTRY, MultiModalKwargs @@ -56,8 +56,6 @@ if TYPE_CHECKING: NPU_PAGED_ATTENTION_MASK_VALUE = -10000 -logger = init_logger(__name__) - class NPUModelRunner: diff --git a/vllm_ascend/worker/multi_step_runner.py b/vllm_ascend/worker/multi_step_runner.py index 65f0208..2ac9561 100644 --- a/vllm_ascend/worker/multi_step_runner.py +++ b/vllm_ascend/worker/multi_step_runner.py @@ -7,7 +7,6 @@ from typing import (TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, import torch from torch import nn from vllm.distributed import get_pp_group -from vllm.logger import init_logger from vllm.model_executor.layers.sampler import (PromptLogprobs, SampleLogprobs, SamplerOutput, SamplingMetadata, get_logprobs, @@ -30,8 +29,6 @@ from vllm_ascend.worker.model_runner import ( if TYPE_CHECKING: from vllm.attention.backends.abstract import AttentionBackend -logger = init_logger(__name__) - @dataclass(frozen=False) class StatefulModelInputForNPU(StatefulModelInput): diff --git a/vllm_ascend/worker/worker.py b/vllm_ascend/worker/worker.py index 736c138..99d89b2 100644 --- a/vllm_ascend/worker/worker.py +++ b/vllm_ascend/worker/worker.py @@ -28,7 +28,7 @@ from vllm.config import ParallelConfig, VllmConfig from vllm.distributed import (ensure_model_parallel_initialized, init_distributed_environment, set_custom_all_reduce) -from vllm.logger import init_logger +from vllm.logger import logger from vllm.lora.request import LoRARequest from vllm.model_executor import set_random_seed from vllm.model_executor.layers.sampler import SamplerOutput @@ -48,8 +48,6 @@ from vllm_ascend.utils import try_register_lib from vllm_ascend.worker.model_runner import NPUModelRunner from vllm_ascend.worker.pooling_model_runner import NPUPoolingModelRunner -logger = init_logger(__name__) - class NPUWorker(LocalOrDistributedWorkerBase): """A worker class that executes (a partition of) the model on a NPU. diff --git a/vllm_ascend/worker/worker_v1.py b/vllm_ascend/worker/worker_v1.py index b9361d2..d07632d 100644 --- a/vllm_ascend/worker/worker_v1.py +++ b/vllm_ascend/worker/worker_v1.py @@ -29,7 +29,7 @@ from vllm.config import ParallelConfig, VllmConfig from vllm.distributed import (ensure_model_parallel_initialized, init_distributed_environment, set_custom_all_reduce) -from vllm.logger import init_logger +from vllm.logger import logger from vllm.model_executor import set_random_seed from vllm.platforms import current_platform from vllm.utils import STR_DTYPE_TO_TORCH_DTYPE @@ -42,8 +42,6 @@ from vllm.v1.worker.worker_base import WorkerBase from vllm_ascend.worker.model_runner_v1 import NPUModelRunner -logger = init_logger(__name__) - class NPUWorker(WorkerBase):