[BugFix] Use consistent logger everywhere (#3738)

Author: njhill

vllm/lora/models.py

@@ -1,6 +1,5 @@
 import copy
 import json
-import logging
 import math
 import os
 import re
@@ -11,13 +10,14 @@
 from torch import nn
 
 from vllm.config import LoRAConfig
+from vllm.logger import init_logger
 from vllm.lora.layers import (BaseLayerWithLoRA, LoRAMapping, from_layer,
                               from_layer_logits_processor)
 from vllm.lora.lora import LoRALayerWeights, PackedLoRALayerWeights
 from vllm.lora.utils import parse_fine_tuned_lora_name, replace_submodule
 from vllm.utils import LRUCache, is_pin_memory_available
 
-logger = logging.getLogger(__name__)
+logger = init_logger(__name__)
 
 _GLOBAL_LORA_ID = 0
 

vllm/lora/utils.py

@@ -1,9 +1,10 @@
-import logging
 from typing import Tuple
 
 from torch import nn
 
-logger = logging.getLogger(__name__)
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
 
 
 def replace_submodule(model: nn.Module, module_name: str,

vllm/lora/worker_manager.py

@@ -1,16 +1,16 @@
-import logging
 from abc import ABC, abstractmethod, abstractproperty
 from typing import Any, Dict, List, Optional, Set, Type
 
 import torch
 
 from vllm.config import LoRAConfig
+from vllm.logger import init_logger
 from vllm.lora.layers import LoRAMapping
 from vllm.lora.models import (LoRAModel, LoRAModelManager,
                               LRUCacheLoRAModelManager, create_lora_manager)
 from vllm.lora.request import LoRARequest
 
-logger = logging.getLogger(__name__)
+logger = init_logger(__name__)
 
 
 class AbstractWorkerLoRAManager(ABC):

vllm/model_executor/parallel_utils/pynccl.py

@@ -21,15 +21,16 @@
 
 import ctypes
 import datetime
-import logging
 import os
 
 # ===================== import region =====================
 import torch
 import torch.distributed as dist
 from torch.distributed import ReduceOp
 
-logger = logging.getLogger(__name__)
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
 
 so_file = os.environ.get("VLLM_NCCL_SO_PATH", "")
 

vllm/model_executor/parallel_utils/pynccl_utils.py

@@ -1,11 +1,12 @@
 import contextlib
-import logging
 from typing import Optional
 
 import torch
 from torch.distributed import ReduceOp
 
-logger = logging.getLogger(__name__)
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
 
 try:
     from vllm.model_executor.parallel_utils.pynccl import (NCCLCommunicator,