We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[Feature]: Cannot use FlashAttention backend for Volta and Turing GPUs. (but FlashAttention v1.0.9 supports Turing GPU.)
### 🚀 The feature, motivation and pitch

Turing GPU can use FlashAttention v1.0.9 which can reduce use of vram significantly.

FlashAttention has no plan to support Turing GPU in FlashAttention v2 actually.
so please support FlashAttention v1.0.9. thanks a lot!

many friends having 8*2080ti need this help.

### Alternatives

_No response_

### Additional context

_No response_

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `vllm/attention/selector.py`
Content:
```
1 import enum
2 import os
3 from functools import lru_cache
4 from typing import Type
5 
6 import torch
7 
8 from vllm.attention.backends.abstract import AttentionBackend
9 from vllm.logger import init_logger
10 from vllm.utils import is_cpu, is_hip
11 
12 logger = init_logger(__name__)
13 
14 VLLM_ATTENTION_BACKEND = "VLLM_ATTENTION_BACKEND"
15 
16 
17 class _Backend(enum.Enum):
18     FLASH_ATTN = enum.auto()
19     XFORMERS = enum.auto()
20     ROCM_FLASH = enum.auto()
21     TORCH_SDPA = enum.auto()
22 
23 
24 @lru_cache(maxsize=None)
25 def get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:
26     backend = _which_attn_to_use(dtype)
27     if backend == _Backend.FLASH_ATTN:
28         logger.info("Using FlashAttention backend.")
29         from vllm.attention.backends.flash_attn import (  # noqa: F401
30             FlashAttentionBackend)
31         return FlashAttentionBackend
32     elif backend == _Backend.XFORMERS:
33         logger.info("Using XFormers backend.")
34         from vllm.attention.backends.xformers import (  # noqa: F401
35             XFormersBackend)
36         return XFormersBackend
37     elif backend == _Backend.ROCM_FLASH:
38         logger.info("Using ROCmFlashAttention backend.")
39         from vllm.attention.backends.rocm_flash_attn import (  # noqa: F401
40             ROCmFlashAttentionBackend)
41         return ROCmFlashAttentionBackend
42     elif backend == _Backend.TORCH_SDPA:
43         logger.info("Using Torch SDPA backend.")
44         from vllm.attention.backends.torch_sdpa import TorchSDPABackend
45         return TorchSDPABackend
46     else:
47         raise ValueError("Invalid attention backend.")
48 
49 
50 def _which_attn_to_use(dtype: torch.dtype) -> _Backend:
51     """Returns which flash attention backend to use."""
52     if is_cpu():
53         return _Backend.TORCH_SDPA
54 
55     if is_hip():
56         # AMD GPUs.
57         if torch.cuda.get_device_capability()[0] != 9:
58             # not Instinct series GPUs.
59             logger.info("flash_atten is not supported on NAVI GPUs.")
60         return _Backend.ROCM_FLASH
61 
62     # NVIDIA GPUs.
63     if torch.cuda.get_device_capability()[0] < 8:
64         # Volta and Turing NVIDIA GPUs.
65         logger.info("Cannot use FlashAttention backend for Volta and Turing "
66                     "GPUs.")
67         return _Backend.XFORMERS
68 
69     if dtype not in (torch.float16, torch.bfloat16):
70         logger.info("Cannot use FlashAttention backend for dtype other than "
71                     "torch.float16 or torch.bfloat16.")
72         return _Backend.XFORMERS
73 
74     try:
75         import flash_attn  # noqa: F401
76     except ImportError:
77         logger.info(
78             "Cannot use FlashAttention backend because the flash_attn package "
79             "is not found. Please install it for better performance.")
80         return _Backend.XFORMERS
81 
82     backend_by_env_var = os.getenv(VLLM_ATTENTION_BACKEND)
83     if backend_by_env_var is not None:
84         return _Backend[backend_by_env_var]
85 
86     # Default case.
87     return _Backend.FLASH_ATTN
88
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/vllm/attention/selector.py b/vllm/attention/selector.py
--- a/vllm/attention/selector.py
+++ b/vllm/attention/selector.py
@@ -25,7 +25,7 @@
 def get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:
     backend = _which_attn_to_use(dtype)
     if backend == _Backend.FLASH_ATTN:
-        logger.info("Using FlashAttention backend.")
+        logger.info("Using FlashAttention-2 backend.")
         from vllm.attention.backends.flash_attn import (  # noqa: F401
             FlashAttentionBackend)
         return FlashAttentionBackend
@@ -62,12 +62,12 @@
     # NVIDIA GPUs.
     if torch.cuda.get_device_capability()[0] < 8:
         # Volta and Turing NVIDIA GPUs.
-        logger.info("Cannot use FlashAttention backend for Volta and Turing "
+        logger.info("Cannot use FlashAttention-2 backend for Volta and Turing "
                     "GPUs.")
         return _Backend.XFORMERS
 
     if dtype not in (torch.float16, torch.bfloat16):
-        logger.info("Cannot use FlashAttention backend for dtype other than "
+        logger.info("Cannot use FlashAttention-2 backend for dtype other than "
                     "torch.float16 or torch.bfloat16.")
         return _Backend.XFORMERS
 
@@ -75,8 +75,8 @@
         import flash_attn  # noqa: F401
     except ImportError:
         logger.info(
-            "Cannot use FlashAttention backend because the flash_attn package "
-            "is not found. Please install it for better performance.")
+            "Cannot use FlashAttention-2 backend because the flash_attn "
+            "package is not found. Please install it for better performance.")
         return _Backend.XFORMERS
 
     backend_by_env_var = os.getenv(VLLM_ATTENTION_BACKEND)

{"golden_diff": "diff --git a/vllm/attention/selector.py b/vllm/attention/selector.py\n--- a/vllm/attention/selector.py\n+++ b/vllm/attention/selector.py\n@@ -25,7 +25,7 @@\n def get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:\n     backend = _which_attn_to_use(dtype)\n     if backend == _Backend.FLASH_ATTN:\n-        logger.info(\"Using FlashAttention backend.\")\n+        logger.info(\"Using FlashAttention-2 backend.\")\n         from vllm.attention.backends.flash_attn import (  # noqa: F401\n             FlashAttentionBackend)\n         return FlashAttentionBackend\n@@ -62,12 +62,12 @@\n     # NVIDIA GPUs.\n     if torch.cuda.get_device_capability()[0] < 8:\n         # Volta and Turing NVIDIA GPUs.\n-        logger.info(\"Cannot use FlashAttention backend for Volta and Turing \"\n+        logger.info(\"Cannot use FlashAttention-2 backend for Volta and Turing \"\n                     \"GPUs.\")\n         return _Backend.XFORMERS\n \n     if dtype not in (torch.float16, torch.bfloat16):\n-        logger.info(\"Cannot use FlashAttention backend for dtype other than \"\n+        logger.info(\"Cannot use FlashAttention-2 backend for dtype other than \"\n                     \"torch.float16 or torch.bfloat16.\")\n         return _Backend.XFORMERS\n \n@@ -75,8 +75,8 @@\n         import flash_attn  # noqa: F401\n     except ImportError:\n         logger.info(\n-            \"Cannot use FlashAttention backend because the flash_attn package \"\n-            \"is not found. Please install it for better performance.\")\n+            \"Cannot use FlashAttention-2 backend because the flash_attn \"\n+            \"package is not found. Please install it for better performance.\")\n         return _Backend.XFORMERS\n \n     backend_by_env_var = os.getenv(VLLM_ATTENTION_BACKEND)\n", "issue": "[Feature]: Cannot use FlashAttention backend for Volta and Turing GPUs. (but FlashAttention v1.0.9 supports Turing GPU.)\n### \ud83d\ude80 The feature, motivation and pitch\r\n\r\nTuring GPU can use FlashAttention v1.0.9 which can reduce use of vram significantly.\r\n\r\nFlashAttention has no plan to support Turing GPU in FlashAttention v2 actually.\r\nso please support FlashAttention v1.0.9. thanks a lot!\r\n\r\nmany friends having 8*2080ti need this help.\r\n\r\n### Alternatives\r\n\r\n_No response_\r\n\r\n### Additional context\r\n\r\n_No response_\n", "before_files": [{"content": "import enum\nimport os\nfrom functools import lru_cache\nfrom typing import Type\n\nimport torch\n\nfrom vllm.attention.backends.abstract import AttentionBackend\nfrom vllm.logger import init_logger\nfrom vllm.utils import is_cpu, is_hip\n\nlogger = init_logger(__name__)\n\nVLLM_ATTENTION_BACKEND = \"VLLM_ATTENTION_BACKEND\"\n\n\nclass _Backend(enum.Enum):\n    FLASH_ATTN = enum.auto()\n    XFORMERS = enum.auto()\n    ROCM_FLASH = enum.auto()\n    TORCH_SDPA = enum.auto()\n\n\n@lru_cache(maxsize=None)\ndef get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:\n    backend = _which_attn_to_use(dtype)\n    if backend == _Backend.FLASH_ATTN:\n        logger.info(\"Using FlashAttention backend.\")\n        from vllm.attention.backends.flash_attn import (  # noqa: F401\n            FlashAttentionBackend)\n        return FlashAttentionBackend\n    elif backend == _Backend.XFORMERS:\n        logger.info(\"Using XFormers backend.\")\n        from vllm.attention.backends.xformers import (  # noqa: F401\n            XFormersBackend)\n        return XFormersBackend\n    elif backend == _Backend.ROCM_FLASH:\n        logger.info(\"Using ROCmFlashAttention backend.\")\n        from vllm.attention.backends.rocm_flash_attn import (  # noqa: F401\n            ROCmFlashAttentionBackend)\n        return ROCmFlashAttentionBackend\n    elif backend == _Backend.TORCH_SDPA:\n        logger.info(\"Using Torch SDPA backend.\")\n        from vllm.attention.backends.torch_sdpa import TorchSDPABackend\n        return TorchSDPABackend\n    else:\n        raise ValueError(\"Invalid attention backend.\")\n\n\ndef _which_attn_to_use(dtype: torch.dtype) -> _Backend:\n    \"\"\"Returns which flash attention backend to use.\"\"\"\n    if is_cpu():\n        return _Backend.TORCH_SDPA\n\n    if is_hip():\n        # AMD GPUs.\n        if torch.cuda.get_device_capability()[0] != 9:\n            # not Instinct series GPUs.\n            logger.info(\"flash_atten is not supported on NAVI GPUs.\")\n        return _Backend.ROCM_FLASH\n\n    # NVIDIA GPUs.\n    if torch.cuda.get_device_capability()[0] < 8:\n        # Volta and Turing NVIDIA GPUs.\n        logger.info(\"Cannot use FlashAttention backend for Volta and Turing \"\n                    \"GPUs.\")\n        return _Backend.XFORMERS\n\n    if dtype not in (torch.float16, torch.bfloat16):\n        logger.info(\"Cannot use FlashAttention backend for dtype other than \"\n                    \"torch.float16 or torch.bfloat16.\")\n        return _Backend.XFORMERS\n\n    try:\n        import flash_attn  # noqa: F401\n    except ImportError:\n        logger.info(\n            \"Cannot use FlashAttention backend because the flash_attn package \"\n            \"is not found. Please install it for better performance.\")\n        return _Backend.XFORMERS\n\n    backend_by_env_var = os.getenv(VLLM_ATTENTION_BACKEND)\n    if backend_by_env_var is not None:\n        return _Backend[backend_by_env_var]\n\n    # Default case.\n    return _Backend.FLASH_ATTN\n", "path": "vllm/attention/selector.py"}], "after_files": [{"content": "import enum\nimport os\nfrom functools import lru_cache\nfrom typing import Type\n\nimport torch\n\nfrom vllm.attention.backends.abstract import AttentionBackend\nfrom vllm.logger import init_logger\nfrom vllm.utils import is_cpu, is_hip\n\nlogger = init_logger(__name__)\n\nVLLM_ATTENTION_BACKEND = \"VLLM_ATTENTION_BACKEND\"\n\n\nclass _Backend(enum.Enum):\n    FLASH_ATTN = enum.auto()\n    XFORMERS = enum.auto()\n    ROCM_FLASH = enum.auto()\n    TORCH_SDPA = enum.auto()\n\n\n@lru_cache(maxsize=None)\ndef get_attn_backend(dtype: torch.dtype) -> Type[AttentionBackend]:\n    backend = _which_attn_to_use(dtype)\n    if backend == _Backend.FLASH_ATTN:\n        logger.info(\"Using FlashAttention-2 backend.\")\n        from vllm.attention.backends.flash_attn import (  # noqa: F401\n            FlashAttentionBackend)\n        return FlashAttentionBackend\n    elif backend == _Backend.XFORMERS:\n        logger.info(\"Using XFormers backend.\")\n        from vllm.attention.backends.xformers import (  # noqa: F401\n            XFormersBackend)\n        return XFormersBackend\n    elif backend == _Backend.ROCM_FLASH:\n        logger.info(\"Using ROCmFlashAttention backend.\")\n        from vllm.attention.backends.rocm_flash_attn import (  # noqa: F401\n            ROCmFlashAttentionBackend)\n        return ROCmFlashAttentionBackend\n    elif backend == _Backend.TORCH_SDPA:\n        logger.info(\"Using Torch SDPA backend.\")\n        from vllm.attention.backends.torch_sdpa import TorchSDPABackend\n        return TorchSDPABackend\n    else:\n        raise ValueError(\"Invalid attention backend.\")\n\n\ndef _which_attn_to_use(dtype: torch.dtype) -> _Backend:\n    \"\"\"Returns which flash attention backend to use.\"\"\"\n    if is_cpu():\n        return _Backend.TORCH_SDPA\n\n    if is_hip():\n        # AMD GPUs.\n        if torch.cuda.get_device_capability()[0] != 9:\n            # not Instinct series GPUs.\n            logger.info(\"flash_atten is not supported on NAVI GPUs.\")\n        return _Backend.ROCM_FLASH\n\n    # NVIDIA GPUs.\n    if torch.cuda.get_device_capability()[0] < 8:\n        # Volta and Turing NVIDIA GPUs.\n        logger.info(\"Cannot use FlashAttention-2 backend for Volta and Turing \"\n                    \"GPUs.\")\n        return _Backend.XFORMERS\n\n    if dtype not in (torch.float16, torch.bfloat16):\n        logger.info(\"Cannot use FlashAttention-2 backend for dtype other than \"\n                    \"torch.float16 or torch.bfloat16.\")\n        return _Backend.XFORMERS\n\n    try:\n        import flash_attn  # noqa: F401\n    except ImportError:\n        logger.info(\n            \"Cannot use FlashAttention-2 backend because the flash_attn \"\n            \"package is not found. Please install it for better performance.\")\n        return _Backend.XFORMERS\n\n    backend_by_env_var = os.getenv(VLLM_ATTENTION_BACKEND)\n    if backend_by_env_var is not None:\n        return _Backend[backend_by_env_var]\n\n    # Default case.\n    return _Backend.FLASH_ATTN\n", "path": "vllm/attention/selector.py"}]}