Upgrade to vllm 0.17.0 corex v4.1 overlay

vllm/platforms/cuda.py

@@ -6,10 +6,13 @@ pynvml. However, it should not initialize cuda context.
 
 import os
 from collections.abc import Callable
+from datetime import timedelta
 from functools import cache, wraps
 from typing import TYPE_CHECKING, TypeVar
 
 import torch
+from torch.distributed import PrefixStore, ProcessGroup
+from torch.distributed.distributed_c10d import is_nccl_available
 from typing_extensions import ParamSpec
 
 # import custom ops, trigger op registration
@@ -414,6 +417,7 @@ class CudaPlatformBase(Platform):
             AttentionBackendEnum.FLASH_ATTN,
             AttentionBackendEnum.TRITON_ATTN,
             AttentionBackendEnum.TORCH_SDPA,
+            AttentionBackendEnum.FLASHINFER,
         ]
 
     @classmethod
@@ -481,6 +485,37 @@ class CudaPlatformBase(Platform):
     def get_static_graph_wrapper_cls(cls) -> str:
         return "vllm.compilation.cuda_graph.CUDAGraphWrapper"
 
+    @classmethod
+    def stateless_init_device_torch_dist_pg(
+        cls,
+        backend: str,
+        prefix_store: PrefixStore,
+        group_rank: int,
+        group_size: int,
+        timeout: timedelta,
+    ) -> ProcessGroup:
+        assert is_nccl_available()
+        pg: ProcessGroup = ProcessGroup(
+            prefix_store,
+            group_rank,
+            group_size,
+        )
+        from torch.distributed.distributed_c10d import ProcessGroupNCCL
+
+        backend_options = ProcessGroupNCCL.Options()
+        backend_options._timeout = timeout
+
+        backend_class = ProcessGroupNCCL(
+            prefix_store, group_rank, group_size, backend_options
+        )
+        backend_type = ProcessGroup.BackendType.NCCL
+        device = torch.device("cuda")
+        pg._set_default_backend(backend_type)
+        backend_class._set_sequence_number_for_group()
+
+        pg._register_backend(device, backend_type, backend_class)
+        return pg
+
     @classmethod
     def device_count(cls) -> int:
         return cuda_device_count_stateless()
@@ -556,7 +591,7 @@ class NvmlCudaPlatform(CudaPlatformBase):
             physical_device_id = cls.device_id_to_physical_device_id(device_id)
             handle = pynvml.nvmlDeviceGetHandleByIndex(physical_device_id)
             major, minor = pynvml.nvmlDeviceGetCudaComputeCapability(handle)
-            return DeviceCapability(major=major, minor=minor)
+            return DeviceCapability(major=9, minor=0)
         except RuntimeError:
             return None