[CI] Add pre-commit check for patch logger (#7446)

### What this PR does / why we need it?
See https://github.com/vllm-project/vllm-ascend/pull/7402, pre-commit
hook will forbid init_logger(__name__) in vllm_ascend patch modules

- vLLM version: v0.17.0
- vLLM main:
8a680463fa

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

vllm_ascend/_310p/quantization/modelslim_config.py

@@ -21,7 +21,7 @@ from typing import Any
 
 import torch
 from vllm.config import get_current_vllm_config
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.model_executor.layers.fused_moe import FusedMoE
 from vllm.model_executor.layers.linear import LinearBase
 from vllm.model_executor.layers.quantization import register_quantization_config
@@ -41,8 +41,6 @@ from vllm_ascend.quantization.modelslim_config import (
 )
 from vllm_ascend.utils import ASCEND_QUANTIZATION_METHOD
 
-logger = init_logger(__name__)
-
 
 def create_scheme_for_layer(
     quant_description: dict[str, Any],

vllm_ascend/batch_invariant.py

@@ -20,14 +20,13 @@ import os
 
 import torch
 import torch_npu
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.model_executor.layers.batch_invariant import vllm_is_batch_invariant
 from vllm.triton_utils import HAS_TRITON
 
 # in case recursive call in reduce_sum.
 torch_sum = torch.sum
 
-logger = init_logger(__name__)
 
 if HAS_TRITON:
     from vllm_ascend.ops.triton.batch_invariant.matmul import (

vllm_ascend/core/recompute_scheduler.py

@@ -27,7 +27,7 @@ from vllm.distributed.ec_transfer.ec_connector.base import ECConnectorMetadata
 from vllm.distributed.kv_events import KVEventBatch
 from vllm.distributed.kv_transfer.kv_connector.v1.base import KVConnectorMetadata
 from vllm.distributed.kv_transfer.kv_connector.v1.metrics import KVConnectorStats
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.v1.core.kv_cache_manager import KVCacheBlocks
 from vllm.v1.core.sched.async_scheduler import AsyncScheduler
 from vllm.v1.core.sched.output import NewRequestData, SchedulerOutput
@@ -42,8 +42,6 @@ from vllm.v1.sample.rejection_sampler import PLACEHOLDER_TOKEN_ID
 from vllm.v1.spec_decode.metrics import SpecDecodingStats
 from vllm.v1.utils import ConstantList, record_function_or_nullcontext
 
-logger = init_logger(__name__)
-
 
 # `spec_manager_map` in single_type_kv_cache_manager is a module-level dict
 # whose keys are class objects bound at import time.  When the async

vllm_ascend/distributed/kv_transfer/kv_pool/ucm_connector.py

@@ -5,11 +5,8 @@ import torch
 from ucm.integration.vllm.ucm_connector import UCMConnector
 from vllm.config import VllmConfig
 from vllm.distributed.kv_transfer.kv_connector.v1.base import KVConnectorBase_V1, KVConnectorMetadata, KVConnectorRole
-from vllm.logger import init_logger
 from vllm.v1.core.sched.output import SchedulerOutput
 
-logger = init_logger(__name__)
-
 # isort: off
 if TYPE_CHECKING:
     from vllm.v1.attention.backend import AttentionMetadata  # type: ignore

vllm_ascend/kv_offload/cpu_npu.py

@@ -1,13 +1,11 @@
 import numpy as np
 import torch
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.utils.platform_utils import is_pin_memory_available
 from vllm.v1.attention.backend import AttentionBackend  # type: ignore
 from vllm.v1.kv_offload.mediums import CPULoadStoreSpec, GPULoadStoreSpec
 from vllm.v1.kv_offload.worker.worker import OffloadingHandler, TransferResult, TransferSpec
 
-logger = init_logger(__name__)
-
 
 def expand_block_ids(
     block_ids: np.ndarray,

vllm_ascend/patch/platform/patch_mamba_config_310.py

@@ -4,7 +4,7 @@
 from math import lcm
 
 import vllm.model_executor.models.config
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.model_executor.models import ModelRegistry
 from vllm.model_executor.models.config import MambaModelConfig
 from vllm.utils.math_utils import cdiv
@@ -24,7 +24,6 @@ def verify_and_update_config(cls, vllm_config) -> None:
     Args:
         vllm_config: vLLM Config
     """
-    logger = init_logger(__name__)
     # Save the user input before it gets modified by MambaModelConfig
     mamba_block_size = vllm_config.cache_config.mamba_block_size
     # Enable FULL_AND_PIECEWISE by default

vllm_ascend/quantization/compressed_tensors_config.py

@@ -21,7 +21,7 @@ from typing import Any, Optional, cast
 
 import torch
 from compressed_tensors.quantization import QuantizationArgs, QuantizationStrategy, QuantizationType
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.model_executor.layers.fused_moe import FusedMoE
 from vllm.model_executor.layers.linear import LinearBase, UnquantizedLinearMethod
 from vllm.model_executor.layers.quantization import QUANTIZATION_METHODS, register_quantization_config
@@ -37,8 +37,6 @@ from vllm_ascend.utils import COMPRESSED_TENSORS_METHOD
 
 from .methods import AscendLinearScheme, AscendMoEScheme
 
-logger = init_logger(__name__)
-
 
 # Remove the original compressed_tensors method to replace with our implementation
 def _remove_quantization_method():

vllm_ascend/quantization/modelslim_config.py

@@ -31,7 +31,7 @@ from typing import Any, Optional
 
 import torch
 from vllm.config import get_current_vllm_config
-from vllm.logger import init_logger
+from vllm.logger import logger
 from vllm.model_executor.layers.attention_layer_base import AttentionLayerBase
 from vllm.model_executor.layers.fused_moe import FusedMoE
 from vllm.model_executor.layers.linear import LinearBase
@@ -47,8 +47,6 @@ from .methods import get_scheme_class
 # The config filename that ModelSlim generates after quantizing a model.
 MODELSLIM_CONFIG_FILENAME = "quant_model_description.json"
 
-logger = init_logger(__name__)
-
 # key: model_type
 # value: vLLM prefix -> HF prefix mapping (used to convert vLLM layer names to HF format
 # for looking up keys in quant_model_description.json)

vllm_ascend/quantization/utils.py

@@ -19,12 +19,10 @@ import json
 from pathlib import Path
 
 from vllm import envs
-from vllm.logger import init_logger
+from vllm.logger import logger
 
 from vllm_ascend.utils import ASCEND_QUANTIZATION_METHOD, COMPRESSED_TENSORS_METHOD
 
-logger = init_logger(__name__)
-
 
 def get_model_file(
     model: str | Path,

vllm_ascend/spec_decode/draft_proposer.py

@@ -2,14 +2,11 @@ import torch
 import torch.nn as nn
 from typing_extensions import override
 from vllm.config import VllmConfig
-from vllm.logger import init_logger
 from vllm.model_executor.model_loader import get_model
 from vllm.v1.spec_decode.utils import create_vllm_config_for_draft_model
 
 from vllm_ascend.spec_decode.eagle_proposer import SpecDecodeBaseProposer
 
-logger = init_logger(__name__)
-
 
 class AscendDraftModelProposer(SpecDecodeBaseProposer):
     def __init__(

vllm_ascend/spec_decode/medusa_proposer.py

@@ -1,14 +1,11 @@
 import torch
 from vllm.config import CUDAGraphMode
-from vllm.logger import init_logger
 from vllm.v1.sample.metadata import SamplingMetadata
 from vllm.v1.spec_decode.medusa import MedusaProposer
 from vllm.v1.spec_decode.metadata import SpecDecodeMetadata
 
 from vllm_ascend.ascend_forward_context import set_ascend_forward_context
 
-logger = init_logger(__name__)
-
 
 class AscendMedusaProposer(MedusaProposer):
     """