[Lint] Add python/sglang to ruff F401 checks and remove unused imports in files (#11685)

python/sglang/srt/_custom_ops.py

@@ -15,7 +15,7 @@ if not is_hpu():
     # ROCm does not use vllm custom allreduce
     if use_vllm_custom_allreduce and not is_hip():
         try:
-            import vllm._C
+            import vllm._C  # noqa: F401
         except ImportError as e:
             logger.warning("Failed to import from vllm._C with %r", e)
     else:

python/sglang/srt/compilation/cuda_piecewise_backend.py

@@ -9,7 +9,6 @@ from unittest.mock import patch
 import torch
 import torch.fx as fx
 
-import sglang.srt.compilation.weak_ref_tensor_jit
 from sglang.srt.compilation.compilation_config import CompilationConfig
 from sglang.srt.compilation.compilation_counter import compilation_counter
 

python/sglang/srt/configs/deepseekvl2.py

@@ -1,5 +1,4 @@
 import math
-import os
 from dataclasses import dataclass
 from typing import Dict, List, Optional, Tuple
 

python/sglang/srt/configs/dots_vlm.py

@@ -1,10 +1,5 @@
-from typing import Any, List, Optional, Union
-
-from transformers import AutoProcessor, LlamaTokenizerFast, PretrainedConfig
-from transformers.feature_extraction_utils import BatchFeature
-from transformers.image_utils import ImageInput
-from transformers.processing_utils import ProcessingKwargs, Unpack
-from transformers.tokenization_utils_base import PreTokenizedInput, TextInput
+from transformers import AutoProcessor, PretrainedConfig
+from transformers.processing_utils import ProcessingKwargs
 
 try:
     from transformers import Qwen2_5_VLProcessor

python/sglang/srt/configs/falcon_h1.py

@@ -14,17 +14,12 @@
 # limitations under the License.
 """Falcon-H1 model configuration"""
 
-import enum
 
 from transformers.configuration_utils import PretrainedConfig
-from transformers.modeling_rope_utils import rope_config_validation
 from transformers.utils import logging
 
 from sglang.srt.configs.mamba_utils import Mamba2CacheParams, Mamba2StateShape
-from sglang.srt.layers.dp_attention import (
-    get_attention_tp_size,
-    get_tensor_model_parallel_world_size,
-)
+from sglang.srt.layers.dp_attention import get_tensor_model_parallel_world_size
 
 logger = logging.get_logger(__name__)
 

python/sglang/srt/configs/qwen3_next.py

@@ -21,7 +21,6 @@ from transformers.modeling_rope_utils import rope_config_validation
 from transformers.utils import logging
 
 from sglang.srt.configs.mamba_utils import Mamba2CacheParams, Mamba2StateShape
-from sglang.srt.distributed.utils import divide
 from sglang.srt.layers.dp_attention import get_attention_tp_size
 
 logger = logging.get_logger(__name__)

python/sglang/srt/connector/remote_instance.py

@@ -1,7 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import logging
-from typing import Generator, List, Optional, Tuple
+from typing import Generator, Optional, Tuple
 from urllib.parse import urlparse
 
 import torch

python/sglang/srt/disaggregation/ascend/transfer_engine.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import List, Optional
+from typing import List
 
 import torch
 

python/sglang/srt/disaggregation/decode.py

@@ -25,7 +25,7 @@ import time
 from collections import deque
 from dataclasses import dataclass
 from http import HTTPStatus
-from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Type, Union
+from typing import TYPE_CHECKING, List, Optional, Tuple, Type, Union
 
 import torch
 from torch.distributed import ProcessGroup
@@ -48,10 +48,7 @@ from sglang.srt.disaggregation.utils import (
 )
 from sglang.srt.layers.dp_attention import get_attention_tp_size
 from sglang.srt.managers.schedule_batch import FINISH_ABORT, RequestStage, ScheduleBatch
-from sglang.srt.mem_cache.allocator import (
-    BaseTokenToKVPoolAllocator,
-    SWATokenToKVPoolAllocator,
-)
+from sglang.srt.mem_cache.allocator import BaseTokenToKVPoolAllocator
 from sglang.srt.mem_cache.base_prefix_cache import BasePrefixCache
 from sglang.srt.mem_cache.memory_pool import (
     HybridLinearKVPool,
@@ -61,7 +58,6 @@ from sglang.srt.mem_cache.memory_pool import (
     ReqToTokenPool,
     SWAKVPool,
 )
-from sglang.srt.model_executor.forward_batch_info import ForwardMode
 from sglang.srt.utils import get_int_env_var, require_mlp_sync
 from sglang.srt.utils.torch_memory_saver_adapter import TorchMemorySaverAdapter
 

python/sglang/srt/disaggregation/prefill.py

@@ -20,7 +20,6 @@ Life cycle of a request in the prefill server
 from __future__ import annotations
 
 import logging
-import threading
 import time
 from collections import deque
 from http import HTTPStatus
@@ -54,7 +53,7 @@ from sglang.srt.mem_cache.memory_pool import (
     NSATokenToKVPool,
     SWAKVPool,
 )
-from sglang.srt.model_executor.forward_batch_info import ForwardMode, PPProxyTensors
+from sglang.srt.model_executor.forward_batch_info import PPProxyTensors
 from sglang.srt.utils import (
     DynamicGradMode,
     broadcast_pyobj,

python/sglang/srt/distributed/device_communicators/custom_all_reduce.py

@@ -32,7 +32,7 @@ try:
         ops.meta_size()
     else:
         # Use custom allreduce from sgl kernel (ROCM and TRT-LLM)
-        import sgl_kernel
+        import sgl_kernel  # noqa: F401
     custom_ar = True
 except Exception:
     # For CPUs

python/sglang/srt/distributed/device_communicators/pymscclpp.py

@@ -4,7 +4,7 @@ import math
 import os
 from contextlib import contextmanager
 from enum import IntEnum
-from typing import Any, Callable, List, Optional, TypeVar, Union
+from typing import Optional, Union
 
 import torch
 import torch.distributed as dist
@@ -24,7 +24,7 @@ if _is_hip:
     mscclpp_is_available = False
 if _is_cuda:
     try:
-        import sgl_kernel
+        import sgl_kernel  # noqa: F401
 
         mscclpp_is_available = True
     except:

python/sglang/srt/distributed/device_communicators/symm_mem.py

@@ -9,7 +9,7 @@ from torch.distributed import ProcessGroup
 from sglang.srt.distributed.device_communicators.all_reduce_utils import (
     SYMM_MEM_ALL_REDUCE_MAX_SIZES,
 )
-from sglang.srt.utils import get_device_capability, is_cuda, is_hip
+from sglang.srt.utils import is_cuda, is_hip
 
 try:
     import torch.distributed._symmetric_memory as torch_symm_mem

python/sglang/srt/distributed/naive_distributed.py

@@ -1,5 +1,4 @@
 import base64
-import os
 import pickle
 import time
 from pathlib import Path

python/sglang/srt/entrypoints/context.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copied from vLLM
-import json
 import logging
 from abc import ABC, abstractmethod
 from typing import Union

python/sglang/srt/entrypoints/harmony_utils.py

@@ -3,7 +3,6 @@
 # Adapted from vLLM: https://github.com/vllm-project/vllm/blob/1b9902806915040ac9b3029f2ab7522ec505afc3/vllm/entrypoints/harmony_utils.py
 # Slight differences in processing chat messages
 import datetime
-import json
 from collections.abc import Iterable
 from typing import Literal, Optional, Union
 

python/sglang/srt/entrypoints/http_server.py

@@ -19,7 +19,6 @@ This file implements HTTP APIs for the inference engine via fastapi.
 
 import asyncio
 import dataclasses
-import json
 import logging
 import multiprocessing as multiprocessing
 import os

python/sglang/srt/entrypoints/http_server_engine.py

@@ -1,15 +1,9 @@
-import copy
-import dataclasses
 import multiprocessing
-import pickle
-import threading
 import time
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import List, Optional, Tuple
 
-import pybase64
 import requests
 import torch
-import torch.distributed as dist
 
 from sglang.srt.entrypoints.EngineBase import EngineBase
 from sglang.srt.entrypoints.http_server import launch_server

python/sglang/srt/eplb/eplb_algorithms/deepseek.py

@@ -3,8 +3,6 @@ from typing import Tuple
 
 import torch
 
-from sglang.srt.utils import get_bool_env_var
-
 
 def balanced_packing(
     weight: torch.Tensor, num_packs: int

python/sglang/srt/function_call/glm4_moe_detector.py

@@ -6,11 +6,7 @@ from typing import List
 
 from sglang.srt.entrypoints.openai.protocol import Tool
 from sglang.srt.function_call.base_format_detector import BaseFormatDetector
-from sglang.srt.function_call.core_types import (
-    StreamingParseResult,
-    StructureInfo,
-    _GetInfoFunc,
-)
+from sglang.srt.function_call.core_types import StreamingParseResult, _GetInfoFunc
 from sglang.srt.function_call.ebnf_composer import EBNFComposer
 
 logger = logging.getLogger(__name__)

python/sglang/srt/function_call/json_array_parser.py

@@ -1,5 +1,3 @@
-import json
-import re
 from typing import List
 
 from sglang.srt.entrypoints.openai.protocol import Tool

python/sglang/srt/function_call/utils.py

@@ -1,4 +1,3 @@
-import json
 from json import JSONDecodeError, JSONDecoder
 from json.decoder import WHITESPACE
 from typing import Any, List, Literal, Optional, Tuple, Union

python/sglang/srt/grpc/compile_proto.py

@@ -70,7 +70,7 @@ def compile_proto(proto_file: Path, output_dir: Path, verbose: bool = True) -> b
 
     # Check if grpc_tools is available
     try:
-        import grpc_tools.protoc
+        import grpc_tools.protoc  # noqa: F401
     except ImportError:
         print("Error: grpcio-tools not installed")
         print(

python/sglang/srt/grpc/grpc_request_manager.py

@@ -27,7 +27,6 @@ from sglang.srt.managers.io_struct import (
     TokenizedEmbeddingReqInput,
     TokenizedGenerateReqInput,
 )
-from sglang.srt.managers.scheduler import is_health_check_generate_req
 from sglang.srt.server_args import PortArgs, ServerArgs
 from sglang.srt.utils import get_zmq_socket, kill_process_tree
 from sglang.utils import get_exception_traceback

python/sglang/srt/layers/activation.py

@@ -380,4 +380,7 @@ if not (
     logger.info(
         "sgl-kernel is not available on Non-NV, Non-AMD platforms or Non-AMX CPUs. Fallback to other kernel libraries."
     )
-    from vllm.model_executor.layers.activation import GeluAndMul, SiluAndMul
+    from vllm.model_executor.layers.activation import (  # noqa: F401
+        GeluAndMul,
+        SiluAndMul,
+    )

python/sglang/srt/layers/attention/ascend_backend.py

@@ -20,7 +20,6 @@ if TYPE_CHECKING:
     from sglang.srt.layers.radix_attention import RadixAttention
     from sglang.srt.model_executor.model_runner import ModelRunner
 
-import os
 
 import numpy as np
 

python/sglang/srt/layers/attention/base_attn_backend.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Optional, Union
+from typing import TYPE_CHECKING, Optional
 
 import torch
 

python/sglang/srt/layers/attention/fla/chunk.py

@@ -2,7 +2,6 @@
 # -*- coding: utf-8 -*-
 # Copyright (c) 2023-2025, Songlin Yang, Yu Zhang
 
-import warnings
 from typing import Optional
 
 import torch

python/sglang/srt/layers/attention/fla/chunk_o.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 # Copyright (c) 2023-2025, Songlin Yang, Yu Zhang
 
-from typing import Optional, Tuple
+from typing import Optional
 
 import torch
 import triton

python/sglang/srt/layers/attention/fla/index.py

@@ -3,9 +3,7 @@
 # Copyright (c) 2023-2025, Songlin Yang, Yu Zhang
 
 import torch
-import torch.nn.functional as F
 import triton
-import triton.language as tl
 
 from sglang.srt.layers.attention.fla.utils import tensor_cache
 

python/sglang/srt/layers/attention/fla/layernorm_gated.py

@@ -5,7 +5,6 @@
 # This backward pass is faster for dimensions up to 8k, but after that it's much slower due to register spilling.
 # The models we train have hidden dim up to 8k anyway (e.g. Llama 70B), so this is fine.
 
-import math
 
 import torch
 import torch.nn.functional as F

python/sglang/srt/layers/attention/fla/wy_fast.py

@@ -9,8 +9,6 @@ import triton
 import triton.language as tl
 
 from sglang.srt.layers.attention.fla.index import prepare_chunk_indices
-from sglang.srt.layers.attention.fla.op import safe_exp
-from sglang.srt.layers.attention.fla.utils import check_shared_mem
 
 
 @triton.heuristics({"IS_VARLEN": lambda args: args["cu_seqlens"] is not None})

python/sglang/srt/layers/attention/flashinfer_backend.py

@@ -50,7 +50,6 @@ if is_flashinfer_available():
         fast_decode_plan,
     )
     from flashinfer.cascade import merge_state
-    from flashinfer.decode import _get_range_buf, get_seq_lens
 
 
 class WrapperDispatch(Enum):

python/sglang/srt/layers/attention/hybrid_attn_backend.py

@@ -1,4 +1,4 @@
-from typing import Optional, Union
+from typing import Optional
 
 import torch
 

python/sglang/srt/layers/attention/hybrid_linear_attn_backend.py

@@ -1,9 +1,6 @@
-from dataclasses import astuple, dataclass
-from functools import lru_cache
 from typing import Optional, Union
 
 import torch
-import torch.nn.functional as F
 
 from sglang.srt.layers.attention.base_attn_backend import AttentionBackend
 from sglang.srt.layers.attention.fla.chunk import chunk_gated_delta_rule

python/sglang/srt/layers/attention/intel_amx_backend.py

@@ -14,7 +14,7 @@ if TYPE_CHECKING:
 
 class IntelAMXAttnBackend(AttentionBackend):
     def __init__(self, model_runner: ModelRunner):
-        import sgl_kernel
+        import sgl_kernel  # noqa: F401
 
         super().__init__()
         self.forward_metadata = None

python/sglang/srt/layers/attention/mamba/causal_conv1d_triton.py

@@ -4,7 +4,6 @@
 
 from typing import List, Optional, Union
 
-import numpy as np
 import torch
 import triton
 import triton.language as tl

python/sglang/srt/layers/attention/mamba/ops/ssd_combined.py

@@ -10,7 +10,6 @@
 
 import torch
 import triton
-import triton.language as tl
 from einops import rearrange
 from packaging import version
 

python/sglang/srt/layers/attention/npu_ops/mla_preprocess.py

@@ -13,7 +13,7 @@ def is_mla_preprocess_enabled() -> bool:
 
 
 if is_mla_preprocess_enabled():
-    import sgl_kernel_npu
+    import sgl_kernel_npu  # noqa: F401
     import torch_npu
 
     torch.npu.config.allow_internal_format = True

python/sglang/srt/layers/attention/nsa/nsa_indexer.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple
+from typing import TYPE_CHECKING, Any, Dict, Optional
 
 import torch
 import torch.nn.functional as F
@@ -547,7 +547,7 @@ class Indexer(CustomOp):
         forward_batch: ForwardBatch,
         layer_id: int,
     ) -> torch.Tensor:
-        import custom_ops
+        import custom_ops  # noqa: F401
         import torch_npu
 
         from sglang.srt.layers.dp_attention import (

python/sglang/srt/layers/attention/nsa_backend.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import sys
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, Dict, List, Literal, Optional, TypeAlias
 
@@ -34,18 +33,18 @@ _is_hip = is_hip()
 
 if _is_hip:
     try:
-        from aiter import (
+        from aiter import (  # noqa: F401
             flash_attn_varlen_func,
             mha_batch_prefill_func,
             paged_attention_ragged,
         )
-        from aiter.mla import mla_decode_fwd, mla_prefill_fwd
+        from aiter.mla import mla_decode_fwd, mla_prefill_fwd  # noqa: F401
     except ImportError:
         print(
             "aiter is AMD specific kernel library. Please make sure aiter is installed on your AMD device."
         )
 else:
-    from sgl_kernel.flash_attn import flash_attn_varlen_func, flash_attn_with_kvcache
+    from sgl_kernel.flash_attn import flash_attn_with_kvcache
 
 
 @dataclass(frozen=True)

python/sglang/srt/layers/layernorm.py

@@ -372,4 +372,4 @@ if not (
     logger.info(
         "sgl-kernel layernorm implementation is not available on current platform. Fallback to other kernel libraries."
     )
-    from vllm.model_executor.layers.layernorm import GemmaRMSNorm, RMSNorm
+    from vllm.model_executor.layers.layernorm import GemmaRMSNorm, RMSNorm  # noqa: F401

python/sglang/srt/layers/moe/cutlass_moe.py

@@ -116,8 +116,6 @@ def cutlass_fused_experts_fp8(
 
     if is_cuda:
         from sglang.srt.layers.quantization.fp8_kernel import (
-            per_group_transpose,
-            per_token_group_quant_fp8_hopper_moe_mn_major,
             sglang_per_token_group_quant_fp8,
         )
 

python/sglang/srt/layers/moe/cutlass_w4a8_moe.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 """Cutlass W4A8 MoE kernel."""
-import logging
 from typing import Optional
 
 import torch

python/sglang/srt/layers/moe/ep_moe/kernels.py

@@ -1,12 +1,9 @@
 import logging
-from typing import List, Optional
 
 import torch
 import triton
 
-from sglang.srt.layers.quantization.fp8_kernel import per_token_group_quant_fp8
-from sglang.srt.utils import ceil_div, dispose_tensor, is_cuda
-from sglang.utils import is_in_ci
+from sglang.srt.utils import ceil_div, is_cuda
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/layers/moe/flashinfer_cutedsl_moe.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional, Union
+from typing import Optional, Union
 
 import torch
 from flashinfer.cute_dsl.blockscaled_gemm import grouped_gemm_nt_masked

python/sglang/srt/layers/moe/fused_moe_triton/layer.py

@@ -43,13 +43,7 @@ from sglang.srt.utils import (
 )
 
 if is_flashinfer_available():
-    from flashinfer import (
-        RoutingMethodType,
-        fp4_quantize,
-        reorder_rows_for_gated_act_gemm,
-        shuffle_matrix_a,
-        shuffle_matrix_sf_a,
-    )
+    from flashinfer import RoutingMethodType, fp4_quantize
 
 _is_hip = is_hip()
 _is_cpu_amx_available = cpu_has_amx_support()

python/sglang/srt/layers/moe/moe_runner/triton.py

@@ -51,7 +51,9 @@ elif _is_hip:
 
 
 if _is_cuda or _is_hip:
-    from sgl_kernel import moe_align_block_size as sgl_moe_align_block_size
+    from sgl_kernel import (  # noqa: F401
+        moe_align_block_size as sgl_moe_align_block_size,
+    )
 
 
 @dataclass

python/sglang/srt/layers/moe/rocm_moe_utils.py

@@ -2,7 +2,6 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from enum import IntEnum
-from functools import cache
 from typing import Optional
 
 import torch

python/sglang/srt/layers/moe/token_dispatcher/deepep.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import logging
 from contextlib import nullcontext
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Optional, Tuple, Union
+from typing import TYPE_CHECKING, List, NamedTuple, Optional, Tuple, Union
 
 from sglang.srt.eplb.expert_distribution import get_global_expert_distribution_recorder
 from sglang.srt.layers.moe.token_dispatcher.base import (

python/sglang/srt/layers/moe/token_dispatcher/mooncake.py

@@ -22,7 +22,7 @@ try:
 except ImportError:
     use_mooncake_ep = False
 
-from enum import Enum, IntEnum, auto
+from enum import Enum, auto
 
 import torch
 import torch.distributed as dist

python/sglang/srt/layers/quantization/awq.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 
 import logging
 import warnings
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional
+from typing import TYPE_CHECKING, Any, Dict, List, Optional
 
 import torch
 

python/sglang/srt/layers/quantization/base_config.py

@@ -3,7 +3,6 @@ from __future__ import annotations
 
 import inspect
 from abc import ABC, abstractmethod
-from dataclasses import dataclass
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type
 
 import torch

python/sglang/srt/layers/quantization/compressed_tensors/compressed_tensors_moe.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 import enum
 import logging
 from enum import Enum
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING, List
 
 import torch
 from compressed_tensors import CompressionFormat
@@ -21,14 +21,7 @@ from sglang.srt.layers.quantization.utils import (
     per_tensor_dequantize,
     replace_parameter,
 )
-from sglang.srt.utils import (
-    get_bool_env_var,
-    is_cpu,
-    is_cuda,
-    is_hip,
-    is_npu,
-    set_weight_attrs,
-)
+from sglang.srt.utils import get_bool_env_var, is_hip, set_weight_attrs
 
 if TYPE_CHECKING:
     from sglang.srt.layers.moe.fused_moe_triton import FusedMoE
@@ -49,7 +42,7 @@ if _use_aiter:
     from sglang.srt.layers.moe.rocm_moe_utils import rocm_fused_experts_tkw1
 
 try:
-    import vllm
+    import vllm  # noqa: F401
 
     VLLM_AVAILABLE = True
 except ImportError:

python/sglang/srt/layers/quantization/deep_gemm_wrapper/configurer.py

@@ -12,7 +12,7 @@ def _compute_enable_deep_gemm():
         return False
 
     try:
-        import deep_gemm
+        import deep_gemm  # noqa: F401
     except ImportError:
         return False
 

python/sglang/srt/layers/quantization/deep_gemm_wrapper/entrypoint.py

@@ -5,7 +5,7 @@ from typing import Tuple
 import torch
 
 from sglang.srt.layers.quantization.deep_gemm_wrapper import compile_utils
-from sglang.srt.layers.quantization.deep_gemm_wrapper.configurer import (
+from sglang.srt.layers.quantization.deep_gemm_wrapper.configurer import (  # noqa: F401
     DEEPGEMM_BLACKWELL,
     DEEPGEMM_SCALE_UE8M0,
     ENABLE_JIT_DEEPGEMM,
@@ -17,7 +17,7 @@ logger = logging.getLogger(__name__)
 
 if ENABLE_JIT_DEEPGEMM:
     import deep_gemm
-    from deep_gemm.utils.layout import get_mn_major_tma_aligned_tensor
+    from deep_gemm.utils.layout import get_mn_major_tma_aligned_tensor  # noqa: F401
 
 _SANITY_CHECK = get_bool_env_var("SGLANG_DEEPGEMM_SANITY_CHECK")
 

python/sglang/srt/layers/quantization/fp8_kernel.py

@@ -67,7 +67,7 @@ if _is_hip:
             raise ImportError("aiter is required when SGLANG_USE_AITER is set to True")
     else:
         try:
-            import vllm._C
+            import vllm._C  # noqa: F401
         except ImportError:
             raise ImportError("vllm is required when SGLANG_USE_AITER is set to False")
 

python/sglang/srt/layers/quantization/fpgemm_fp8.py

@@ -11,7 +11,6 @@ from torch.nn.parameter import Parameter
 from sglang.srt.layers.linear import LinearBase
 from sglang.srt.layers.parameter import ChannelQuantScaleParameter, ModelWeightParameter
 from sglang.srt.layers.quantization.base_config import (
-    FusedMoEMethodBase,
     LinearMethodBase,
     QuantizationConfig,
     QuantizeMethodBase,
@@ -28,7 +27,7 @@ from sglang.srt.layers.quantization.marlin_utils_fp8 import (
     prepare_fp8_layer_for_marlin,
 )
 from sglang.srt.layers.quantization.unquant import UnquantizedLinearMethod
-from sglang.srt.layers.quantization.utils import is_layer_skipped, replace_parameter
+from sglang.srt.layers.quantization.utils import is_layer_skipped
 from sglang.srt.utils import get_bool_env_var, is_cuda
 
 _is_cuda = is_cuda()

python/sglang/srt/layers/quantization/gptq.py

@@ -199,7 +199,6 @@ class GPTQConfig(QuantizationConfig):
         self, layer: torch.nn.Module, prefix: str
     ) -> Optional[LinearMethodBase]:
         # Delay the import to avoid circular dependency
-        from sglang.srt.layers.linear import LinearBase
         from sglang.srt.layers.moe.fused_moe_triton import FusedMoE
 
         if isinstance(layer, FusedMoE):

python/sglang/srt/layers/quantization/int8_kernel.py

@@ -8,7 +8,7 @@ import torch
 import triton
 import triton.language as tl
 
-from sglang.srt.utils import get_bool_env_var, get_device_name, is_cuda
+from sglang.srt.utils import get_device_name, is_cuda
 
 _is_cuda = is_cuda()
 if _is_cuda:

python/sglang/srt/layers/quantization/modelopt_quant.py

@@ -1059,16 +1059,7 @@ class ModelOptNvFp4FusedMoEMethod(FusedMoEMethodBase):
         intermediate_size,
         num_experts,
     ):
-        from flashinfer import (
-            RoutingMethodType,
-            e2m1_and_ufp8sf_scale_to_float,
-            fp4_quantize,
-            next_positive_power_of_2,
-            nvfp4_block_scale_interleave,
-            reorder_rows_for_gated_act_gemm,
-            shuffle_matrix_a,
-            shuffle_matrix_sf_a,
-        )
+        from flashinfer import nvfp4_block_scale_interleave
         from flashinfer.fused_moe.core import (
             _maybe_get_cached_w2_permute_indices,
             _maybe_get_cached_w3_w1_permute_indices,

python/sglang/srt/layers/quantization/petit.py

@@ -2,7 +2,7 @@
 
 
 import logging
-from typing import Any, Callable, Dict, List, Optional
+from typing import Any, Dict, List, Optional
 
 import regex as re
 import torch

python/sglang/srt/layers/quantization/quark/quark_moe.py

@@ -3,16 +3,16 @@
 from __future__ import annotations
 
 import logging
-from typing import TYPE_CHECKING, Any, Callable, Optional
+from typing import TYPE_CHECKING, Any
 
 import torch
-from aiter import ActivationType, QuantType, biased_grouped_topk
+from aiter import ActivationType, QuantType
 from aiter.fused_moe import fused_moe
 from aiter.utility.fp4_utils import e8m0_shuffle
 
 from sglang.srt.layers.moe import MoeRunnerConfig
 from sglang.srt.layers.quantization.base_config import FusedMoEMethodBase
-from sglang.srt.utils import get_bool_env_var, is_hip, mxfp_supported, set_weight_attrs
+from sglang.srt.utils import is_hip, set_weight_attrs
 
 if TYPE_CHECKING:
     from sglang.srt.layers.moe.token_dispatcher import (

python/sglang/srt/layers/quantization/quark/schemes/quark_w4a4_mxfp4.py

@@ -2,20 +2,13 @@
 
 from typing import Any, Callable, Optional
 
-import aiter
 import torch
-import torch.nn.functional as F
-from aiter.ops.gemm_op_a4w4 import gemm_a4w4
-from aiter.ops.shuffle import shuffle_weight
 from aiter.ops.triton.gemm_afp4wfp4 import gemm_afp4wfp4
 from aiter.ops.triton.gemm_afp4wfp4_pre_quant_atomic import gemm_afp4wfp4_pre_quant
 from aiter.ops.triton.quant import dynamic_mxfp4_quant
-from aiter.utility import dtypes
-from aiter.utility.fp4_utils import e8m0_shuffle
 
 from sglang.srt.layers.parameter import GroupQuantScaleParameter, PackedvLLMParameter
 from sglang.srt.layers.quantization.quark.schemes import QuarkScheme
-from sglang.srt.utils import get_bool_env_var
 
 __all__ = ["QuarkW4A4MXFP4"]
 

python/sglang/srt/layers/quantization/utils.py

@@ -11,7 +11,6 @@ import numpy
 import torch
 
 from sglang.srt.layers.quantization.fp8_kernel import scaled_fp8_quant
-from sglang.srt.utils import is_cuda
 
 if TYPE_CHECKING:
     from sglang.srt.layers.quantization.base_config import QuantizationConfig

python/sglang/srt/layers/quantization/w4afp8.py

@@ -1,14 +1,13 @@
 from __future__ import annotations
 
 import logging
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple
+from typing import TYPE_CHECKING, Any, Dict, List, Optional
 
 import torch
 from torch.nn import Module
 from torch.nn.parameter import Parameter
 
-from sglang.srt.distributed.parallel_state import get_moe_expert_parallel_world_size
-from sglang.srt.layers.linear import LinearBase, UnquantizedLinearMethod
+from sglang.srt.layers.linear import UnquantizedLinearMethod
 from sglang.srt.layers.quantization.base_config import (
     FusedMoEMethodBase,
     QuantizationConfig,
@@ -17,11 +16,11 @@ from sglang.srt.layers.quantization.base_config import (
 from sglang.srt.layers.quantization.fp8 import Fp8LinearMethod
 from sglang.srt.layers.quantization.unquant import UnquantizedLinearMethod
 from sglang.srt.layers.quantization.utils import is_layer_skipped
-from sglang.srt.utils import is_npu, set_weight_attrs
+from sglang.srt.utils import set_weight_attrs
 
 if TYPE_CHECKING:
     from sglang.srt.layers.moe import MoeRunnerConfig
-    from sglang.srt.layers.moe.ep_moe.layer import DeepEPMoE, EPMoE
+    from sglang.srt.layers.moe.ep_moe.layer import DeepEPMoE
     from sglang.srt.layers.moe.token_dispatcher import (
         CombineInput,
         DeepEPNormalOutput,

python/sglang/srt/layers/quantization/w8a8_int8.py

@@ -1,28 +1,12 @@
 from __future__ import annotations
 
-import importlib
-import sys
 from types import MappingProxyType
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Callable,
-    Dict,
-    List,
-    Mapping,
-    Optional,
-    Tuple,
-    Union,
-    cast,
-)
+from typing import TYPE_CHECKING, Any, Dict, List, Mapping, Optional, Tuple, Union, cast
 
 import torch
 from torch.nn.parameter import Parameter
 
-from sglang.srt.distributed import (
-    get_tensor_model_parallel_rank,
-    get_tensor_model_parallel_world_size,
-)
+from sglang.srt.distributed import get_tensor_model_parallel_world_size
 from sglang.srt.layers.amx_utils import _amx_process_weight_after_loading
 from sglang.srt.layers.moe import MoeRunner, MoeRunnerBackend, MoeRunnerConfig
 from sglang.srt.layers.moe.moe_runner.triton import TritonMoeQuantInfo

python/sglang/srt/layers/utils.py

@@ -1,6 +1,5 @@
 import logging
 import re
-from functools import lru_cache
 
 import torch
 

python/sglang/srt/lora/backend/triton_backend.py

@@ -11,7 +11,6 @@ from sglang.srt.lora.triton_ops import (
 )
 from sglang.srt.lora.utils import LoRABatchInfo
 from sglang.srt.model_executor.forward_batch_info import ForwardBatch
-from sglang.srt.server_args import ServerArgs
 
 
 class TritonLoRABackend(BaseLoRABackend):

python/sglang/srt/lora/eviction_policy.py

@@ -20,7 +20,7 @@ import logging
 import time
 from abc import ABC, abstractmethod
 from collections import OrderedDict
-from typing import Any, Dict, List, Optional, Set
+from typing import Optional, Set
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/lora/lora_manager.py

@@ -16,7 +16,7 @@
 # and "Punica: Multi-Tenant LoRA Serving"
 
 import logging
-from typing import Dict, Iterable, List, Optional, Set, Tuple
+from typing import Dict, Iterable, List, Optional
 
 import torch
 

python/sglang/srt/managers/cache_controller.py

@@ -14,11 +14,10 @@ limitations under the License.
 """
 
 import logging
-import math
 import threading
 import time
-from queue import Empty, Full, PriorityQueue, Queue
-from typing import TYPE_CHECKING, List, NamedTuple, Optional, Set, Tuple
+from queue import Empty, Full, Queue
+from typing import TYPE_CHECKING, List, NamedTuple, Optional
 
 import torch
 
@@ -41,7 +40,7 @@ from sglang.srt.layers.dp_attention import (
     get_attention_tp_size,
     is_dp_attention_enabled,
 )
-from sglang.srt.mem_cache.memory_pool import MHATokenToKVPool, MLATokenToKVPool
+from sglang.srt.mem_cache.memory_pool import MLATokenToKVPool
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/managers/schedule_batch.py

@@ -59,11 +59,10 @@ from sglang.srt.mem_cache.allocator import (
     SWATokenToKVPoolAllocator,
 )
 from sglang.srt.mem_cache.base_prefix_cache import BasePrefixCache
-from sglang.srt.mem_cache.chunk_cache import ChunkCache, SWAChunkCache
+from sglang.srt.mem_cache.chunk_cache import SWAChunkCache
 from sglang.srt.mem_cache.common import (
     alloc_for_decode,
     alloc_for_extend,
-    alloc_token_slots,
     evict_from_tree_cache,
 )
 from sglang.srt.mem_cache.mamba_radix_cache import MambaRadixCache
@@ -76,7 +75,6 @@ from sglang.srt.sampling.sampling_batch_info import SamplingBatchInfo
 from sglang.srt.sampling.sampling_params import SamplingParams
 from sglang.srt.server_args import ServerArgs, get_global_server_args
 from sglang.srt.utils import flatten_nested_list
-from sglang.srt.utils.common import next_power_of_2
 
 if TYPE_CHECKING:
     from sglang.srt.configs.model_config import ModelConfig

python/sglang/srt/managers/scheduler_metrics_mixin.py

@@ -3,13 +3,10 @@ from __future__ import annotations
 import logging
 import time
 from collections import defaultdict
-from typing import TYPE_CHECKING, Dict, List, Optional, Union
-
-import torch
+from typing import TYPE_CHECKING, List, Optional
 
 from sglang.srt.disaggregation.kv_events import EventPublisherFactory, KVEventBatch
 from sglang.srt.disaggregation.utils import DisaggregationMode
-from sglang.srt.managers.io_struct import TokenizedGenerateReqInput
 from sglang.srt.managers.schedule_policy import PrefillAdder
 from sglang.srt.managers.scheduler import Req, ScheduleBatch
 from sglang.srt.metrics.collector import SchedulerMetricsCollector, SchedulerStats

python/sglang/srt/managers/tokenizer_manager.py

@@ -16,7 +16,6 @@
 import asyncio
 import copy
 import dataclasses
-import json
 import logging
 import math
 import os

python/sglang/srt/managers/utils.py

@@ -1,8 +1,7 @@
 from __future__ import annotations
 
 import logging
-import multiprocessing as mp
-from typing import TYPE_CHECKING, Dict, List, Optional
+from typing import TYPE_CHECKING, Optional
 
 from sglang.srt.layers.logits_processor import LogitsProcessorOutput
 from sglang.srt.managers.schedule_batch import Req

python/sglang/srt/mem_cache/allocator_ascend.py

@@ -92,7 +92,7 @@ class AscendPagedTokenToKVPoolAllocator(PagedTokenToKVPoolAllocator):
         )
 
         if num_new_pages_item < 200:
-            import sgl_kernel_npu
+            import sgl_kernel_npu  # noqa: F401
 
             torch.ops.npu.alloc_extend(
                 prefix_lens,

python/sglang/srt/mem_cache/base_prefix_cache.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Any, List, NamedTuple, Optional, Tuple
+from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Tuple
 
 import torch
 

python/sglang/srt/mem_cache/evict_policy.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, List, Tuple, Union
+from typing import TYPE_CHECKING, Tuple, Union
 
 if TYPE_CHECKING:
     from sglang.srt.mem_cache.radix_cache import TreeNode

python/sglang/srt/mem_cache/mamba_radix_cache.py

@@ -22,7 +22,6 @@ The radix tree data structure for managing the hybrid (full and Mamba) KV cache.
 import heapq
 import time
 from collections import defaultdict
-from functools import partial
 from typing import TYPE_CHECKING, List, Optional, Tuple
 
 import torch
@@ -33,7 +32,6 @@ from sglang.srt.mem_cache.memory_pool import HybridReqToTokenPool
 from sglang.srt.mem_cache.radix_cache import (
     RadixKey,
     _key_match_page_size1,
-    _key_match_paged,
     get_child_key,
 )
 

python/sglang/srt/mem_cache/memory_pool_host.py

@@ -1,7 +1,6 @@
 import abc
 import logging
 import threading
-from enum import IntEnum
 from functools import wraps
 from typing import Optional
 

python/sglang/srt/mem_cache/multimodal_cache.py

@@ -1,6 +1,5 @@
 import logging
 from collections import OrderedDict
-from typing import Dict
 
 import torch
 

python/sglang/srt/mem_cache/radix_cache.py

@@ -23,7 +23,7 @@ import heapq
 import time
 from collections import defaultdict
 from functools import lru_cache, partial
-from typing import TYPE_CHECKING, Any, Iterator, List, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Iterator, List, Optional, Tuple, Union
 
 import torch
 

python/sglang/srt/mem_cache/storage/aibrix_kvcache/unit_test.py

@@ -3,20 +3,8 @@ import os
 
 import torch
 import torch.distributed
-from aibrix_kvcache import (
-    BaseKVCacheManager,
-    GroupAwareKVCacheManager,
-    KVCacheBlockLayout,
-    KVCacheBlockSpec,
-    KVCacheConfig,
-    KVCacheMetrics,
-    KVCacheTensorSpec,
-    ModelSpec,
-    TokenListView,
-)
-from aibrix_kvcache.common.absl_logging import getLogger, log_every_n_seconds, log_if
+from aibrix_kvcache.common.absl_logging import log_every_n_seconds
 from aibrix_kvcache_storage import AibrixKVCacheStorage
-from torch.distributed import Backend, ProcessGroup
 
 from sglang.srt.mem_cache.hicache_storage import HiCacheStorageConfig
 from sglang.srt.mem_cache.memory_pool import MHATokenToKVPool

python/sglang/srt/mem_cache/storage/eic/eic_storage.py

@@ -2,21 +2,18 @@ import json
 import logging
 import os
 import time
-import uuid
-from dataclasses import dataclass
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, List, Optional, Tuple
 
 import eic
 import torch
 import yaml
 
-from sglang.srt.layers.dp_attention import get_attention_tp_rank, get_attention_tp_size
 from sglang.srt.mem_cache.hicache_storage import (
     HiCacheStorage,
     HiCacheStorageConfig,
     HiCacheStorageExtraInfo,
 )
-from sglang.srt.mem_cache.memory_pool_host import HostKVCache, MLATokenToKVPoolHost
+from sglang.srt.mem_cache.memory_pool_host import HostKVCache
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/mem_cache/storage/hf3fs/hf3fs_client.py

@@ -1,6 +1,5 @@
 import logging
 import os
-import threading
 from abc import ABC, abstractmethod
 from typing import List
 

python/sglang/srt/mem_cache/storage/lmcache/lmc_radix_cache.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 import logging
 import threading
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING, Optional
 
 import torch
 

python/sglang/srt/mem_cache/storage/nixl/hicache_nixl.py

@@ -1,9 +1,8 @@
-import hashlib
 import logging
 import os
 import time
 import uuid
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Union
 
 import torch
 

python/sglang/srt/mem_cache/storage/nixl/nixl_utils.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Union
 
 import torch
 

python/sglang/srt/mem_cache/storage/nixl/test_hicache_nixl_storage.py

@@ -2,7 +2,7 @@
 
 import os
 import unittest
-from typing import List, Optional
+from typing import List
 from unittest.mock import MagicMock
 
 import torch

python/sglang/srt/metrics/func_timer.py

@@ -18,7 +18,7 @@ Records the latency of some functions
 import asyncio
 import time
 from functools import wraps
-from typing import Any, Callable, List, Optional
+from typing import Any, Callable, Optional
 
 from sglang.srt.metrics.utils import exponential_buckets
 

python/sglang/srt/model_executor/model_runner.py

@@ -104,11 +104,7 @@ from sglang.srt.mem_cache.memory_pool import (
 )
 from sglang.srt.model_executor.cpu_graph_runner import CPUGraphRunner
 from sglang.srt.model_executor.cuda_graph_runner import CudaGraphRunner
-from sglang.srt.model_executor.forward_batch_info import (
-    ForwardBatch,
-    ForwardMode,
-    PPProxyTensors,
-)
+from sglang.srt.model_executor.forward_batch_info import ForwardBatch, PPProxyTensors
 from sglang.srt.model_executor.npu_graph_runner import NPUGraphRunner
 from sglang.srt.model_executor.piecewise_cuda_graph_runner import (
     PiecewiseCudaGraphRunner,

python/sglang/srt/model_executor/npu_graph_runner.py

@@ -19,10 +19,9 @@ import logging
 import threading
 from typing import TYPE_CHECKING, Optional, Union
 
-import numpy as np
 import torch
 
-from sglang.srt.configs.model_config import AttentionArch, is_deepseek_nsa
+from sglang.srt.configs.model_config import is_deepseek_nsa
 from sglang.srt.model_executor.cuda_graph_runner import CudaGraphRunner
 
 logger = logging.getLogger(__name__)

python/sglang/srt/models/bailing_moe.py

@@ -19,7 +19,7 @@
 # limitations under the License.
 """SGLang BailingMoE model."""
 import logging
-from typing import Any, Dict, Iterable, Optional, Tuple, Union
+from typing import Iterable, Optional, Tuple, Union
 
 import torch
 import torch.nn.functional as F
@@ -59,7 +59,6 @@ from sglang.srt.layers.moe.ep_moe.layer import get_moe_impl_class
 from sglang.srt.layers.moe.fused_moe_triton.layer import FusedMoE
 from sglang.srt.layers.moe.token_dispatcher import DeepEPDispatcher
 from sglang.srt.layers.moe.topk import TopK
-from sglang.srt.layers.moe.utils import DeepEPMode
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.layers.rotary_embedding import get_rope

python/sglang/srt/models/bert.py

@@ -1,5 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
-from typing import Any, Dict, Iterable, Optional, Set, Tuple
+from typing import Iterable, Optional, Set, Tuple
 
 import torch
 from torch import nn

python/sglang/srt/models/deepseek_v2.py

@@ -183,9 +183,9 @@ elif _is_hip:
         awq_dequantize_triton as awq_dequantize,
     )
 elif _is_npu:
-    import custom_ops
-    import sgl_kernel_npu
-    import torch_npu
+    import custom_ops  # noqa: F401
+    import sgl_kernel_npu  # noqa: F401
+    import torch_npu  # noqa: F401
 else:
     pass
 

python/sglang/srt/models/dots_ocr.py

@@ -6,7 +6,6 @@ from typing import Iterable, List, Optional, Tuple
 
 import torch
 import torch.nn as nn
-from transformers.activations import ACT2FN
 
 from sglang.srt.configs import DotsOCRConfig
 from sglang.srt.layers.logits_processor import LogitsProcessor
@@ -22,7 +21,6 @@ from sglang.srt.model_loader.weight_utils import default_weight_loader
 from sglang.srt.models.dots_vlm_vit import DotsVisionTransformer
 from sglang.srt.models.qwen2 import Qwen2ForCausalLM
 from sglang.srt.utils import add_prefix
-from sglang.srt.utils.hf_transformers_utils import get_processor
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/models/dots_vlm.py

@@ -23,7 +23,6 @@ import torch
 from torch import nn
 
 from sglang.srt.configs.dots_vlm import DotsVLMConfig
-from sglang.srt.distributed import parallel_state
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.managers.mm_utils import (
     MultiModalityDataPaddingPatternMultimodalTokens,

python/sglang/srt/models/falcon_h1.py

@@ -1,4 +1,3 @@
-import enum
 import logging
 from typing import Any, Iterable, List, Optional, Set, Tuple
 

python/sglang/srt/models/gemma3n_mm.py

@@ -14,8 +14,7 @@ from transformers import (
 )
 from transformers.models.auto.modeling_auto import AutoModel
 
-from sglang.srt.layers.layernorm import RMSNorm
-from sglang.srt.layers.linear import ColumnParallelLinear, RowParallelLinear
+from sglang.srt.layers.linear import RowParallelLinear
 from sglang.srt.layers.logits_processor import LogitsProcessor
 from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.vocab_parallel_embedding import VocabParallelEmbedding