chore: move cuda_vmm_utils.py under srt/utils/ (#36053)
This commit is contained in:
@@ -19,11 +19,11 @@ import torch.distributed as dist
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import torch.multiprocessing as mp
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import torch.multiprocessing as mp
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from typing_extensions import ParamSpec
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from typing_extensions import ParamSpec
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from sglang.srt.cuda_vmm_utils import _gpu_fabric_clique
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from sglang.srt.distributed.device_communicators.cuda_wrapper import CudaRTLibrary
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from sglang.srt.distributed.device_communicators.cuda_wrapper import CudaRTLibrary
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from sglang.srt.distributed.parallel_state import in_the_same_node_as
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from sglang.srt.distributed.parallel_state import in_the_same_node_as
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from sglang.srt.environ import envs as sglang_envs
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from sglang.srt.environ import envs as sglang_envs
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from sglang.srt.utils import is_cuda, is_hip, is_musa
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from sglang.srt.utils import is_cuda, is_hip, is_musa
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from sglang.srt.utils.cuda_vmm_utils import _gpu_fabric_clique
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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@@ -31,16 +31,16 @@ from sglang.kernels.ops.communication.all_reduce import (
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IPCManager,
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IPCManager,
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custom_all_reduce,
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custom_all_reduce,
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)
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)
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from sglang.srt.cuda_vmm_utils import (
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VmmGraphInputManager,
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compute_graph_capture_bases,
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is_vmm_pointer,
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)
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from sglang.srt.distributed.parallel_state import in_the_same_node_as
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from sglang.srt.distributed.parallel_state import in_the_same_node_as
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from sglang.srt.environ import envs
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from sglang.srt.environ import envs
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from sglang.srt.model_executor.runner_backend_utils.tc_piecewise_cuda_graph import (
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from sglang.srt.model_executor.runner_backend_utils.tc_piecewise_cuda_graph import (
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is_in_tc_piecewise_cuda_graph,
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is_in_tc_piecewise_cuda_graph,
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)
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)
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from sglang.srt.utils.cuda_vmm_utils import (
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VmmGraphInputManager,
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compute_graph_capture_bases,
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is_vmm_pointer,
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)
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from .configs.custom_all_reduce_v2 import (
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from .configs.custom_all_reduce_v2 import (
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get_all_reduce_config,
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get_all_reduce_config,
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@@ -8,7 +8,7 @@ from typing import Dict, List, Optional, Tuple
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import torch
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import torch
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from sglang.srt.cuda_vmm_utils import align_down, align_up
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from sglang.srt.utils.cuda_vmm_utils import align_down, align_up
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# one (start, end_capped) expert range per peer DWDP rank
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# one (start, end_capped) expert range per peer DWDP rank
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PeerRanges = List[Tuple[int, int]]
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PeerRanges = List[Tuple[int, int]]
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@@ -8,7 +8,7 @@ from typing import Dict, List, Optional
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from cuda.bindings import driver as cuda
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from cuda.bindings import driver as cuda
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from sglang.srt.cuda_vmm_utils import (
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from sglang.srt.utils.cuda_vmm_utils import (
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VmmReservation,
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VmmReservation,
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align_up,
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align_up,
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check_drv,
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check_drv,
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@@ -11,7 +11,12 @@ import torch
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import torch.distributed as dist
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import torch.distributed as dist
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from cuda.bindings import driver as cuda
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from cuda.bindings import driver as cuda
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from sglang.srt.cuda_vmm_utils import (
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from sglang.srt.layers.moe.dwdp.layout import (
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DwdpExpertLayout,
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LayerWeightSpecs,
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MnnvlHandleSet,
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)
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from sglang.srt.utils.cuda_vmm_utils import (
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VmmReservation,
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VmmReservation,
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align_down,
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align_down,
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align_up,
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align_up,
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@@ -23,11 +28,6 @@ from sglang.srt.cuda_vmm_utils import (
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make_device_allocation_prop,
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make_device_allocation_prop,
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tensor_from_pointer,
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tensor_from_pointer,
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)
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)
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from sglang.srt.layers.moe.dwdp.layout import (
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DwdpExpertLayout,
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LayerWeightSpecs,
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MnnvlHandleSet,
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)
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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@@ -8,12 +8,6 @@ from typing import Dict, List, Optional, Tuple
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import torch
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import torch
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from sglang.srt.cuda_vmm_utils import (
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VmmReservation,
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get_device_granularity,
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make_device_allocation_prop,
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tensor_from_pointer,
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)
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from sglang.srt.layers.moe.dwdp.layout import (
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from sglang.srt.layers.moe.dwdp.layout import (
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EdgeInfo,
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EdgeInfo,
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LayerWeightSpecs,
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LayerWeightSpecs,
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@@ -21,6 +15,12 @@ from sglang.srt.layers.moe.dwdp.layout import (
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PageAlignedLayout,
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PageAlignedLayout,
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)
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)
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from sglang.srt.layers.moe.dwdp.page_pool import PagePool, compute_slot_sizes
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from sglang.srt.layers.moe.dwdp.page_pool import PagePool, compute_slot_sizes
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from sglang.srt.utils.cuda_vmm_utils import (
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VmmReservation,
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get_device_granularity,
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make_device_allocation_prop,
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tensor_from_pointer,
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)
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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@@ -6,7 +6,7 @@ from typing import TYPE_CHECKING, List, Optional, Sequence
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import torch
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import torch
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from sglang.srt.cuda_vmm_utils import (
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from sglang.srt.utils.cuda_vmm_utils import (
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BumpArenaStub,
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BumpArenaStub,
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VmmReservation,
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VmmReservation,
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align_up,
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align_up,
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@@ -24,10 +24,10 @@ from typing import Any, Iterator, Optional
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import torch
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import torch
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from sglang.srt.cuda_vmm_utils import BumpArenaStub
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from sglang.srt.environ import envs
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from sglang.srt.environ import envs
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from sglang.srt.runtime_context import get_resources
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from sglang.srt.runtime_context import get_resources
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from sglang.srt.utils import is_cuda
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from sglang.srt.utils import is_cuda
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from sglang.srt.utils.cuda_vmm_utils import BumpArenaStub
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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_active_graph_pool_user: Optional[str] = None
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_active_graph_pool_user: Optional[str] = None
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@@ -21,7 +21,7 @@ def align_up(value: int, alignment: int) -> int:
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def _driver_modules():
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def _driver_modules():
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from cuda.bindings import driver as cuda
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from cuda.bindings import driver as cuda
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from sglang.srt.cuda_vmm_utils import check_drv
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from sglang.srt.utils.cuda_vmm_utils import check_drv
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return cuda, check_drv
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return cuda, check_drv
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@@ -10,22 +10,6 @@ from dataclasses import dataclass
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import torch
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import torch
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from sglang.srt.cuda_vmm_utils import (
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_FD_SEND_TIMEOUT_S,
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VmmReservation,
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_get_cuda_driver,
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_recv_fd,
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_send_fd,
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align_up,
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allocation_handle_type_name,
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check_drv,
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get_allocation_granularity,
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get_device_allocation_handle_type,
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import_and_map_alloc,
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make_device_allocation_prop,
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release_mappings,
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tensor_from_pointer,
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)
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from sglang.srt.managers.schedule_batch import (
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from sglang.srt.managers.schedule_batch import (
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Modality,
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Modality,
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MultimodalDataItem,
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MultimodalDataItem,
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@@ -43,6 +27,22 @@ from sglang.srt.utils.cuda_ipc_transport_utils import (
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CudaIpcTensorTransportProxy,
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CudaIpcTensorTransportProxy,
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get_mm_feature_pool_size_per_worker,
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get_mm_feature_pool_size_per_worker,
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)
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)
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from sglang.srt.utils.cuda_vmm_utils import (
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_FD_SEND_TIMEOUT_S,
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VmmReservation,
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_get_cuda_driver,
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_recv_fd,
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_send_fd,
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align_up,
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allocation_handle_type_name,
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check_drv,
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get_allocation_granularity,
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get_device_allocation_handle_type,
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import_and_map_alloc,
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make_device_allocation_prop,
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release_mappings,
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tensor_from_pointer,
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)
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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@@ -21,8 +21,8 @@ import torch.distributed as dist
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from cuda.bindings import driver as drv
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from cuda.bindings import driver as drv
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from sglang.kernels.jit.utils import cache_once
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from sglang.kernels.jit.utils import cache_once
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from sglang.srt import cuda_vmm_utils
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from sglang.srt.utils import cuda_vmm_utils
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from sglang.srt.cuda_vmm_utils import (
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from sglang.srt.utils.cuda_vmm_utils import (
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check_drv,
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check_drv,
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exchange_posix_fds,
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exchange_posix_fds,
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export_shareable_handles,
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export_shareable_handles,
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