We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
[v0.2.0] Release Tracker
## Major changes

* Up to 60% performance improvement by optimizing de-tokenization and sampler
* Initial support for AWQ (performance not optimized)
* Support for RoPE scaling and LongChat
* Support for Mistral-7B

## PRs to be merged before the release

- [x] Vectorized sampler: #1048, #820 
- [x] LongChat: #555 
- [x] `TORCH_CUDA_ARCH_LIST` build option: #1074 
- [x] Support for Mistral-7B: #1196 
- [x] #1198  
- ~~[ ] FP32 RoPE kernel: #1061~~ (deferred to the next PR)

--- 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/__init__.py`
Content:
```
1 """vLLM: a high-throughput and memory-efficient inference engine for LLMs"""
2 
3 from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
4 from vllm.engine.async_llm_engine import AsyncLLMEngine
5 from vllm.engine.llm_engine import LLMEngine
6 from vllm.engine.ray_utils import initialize_cluster
7 from vllm.entrypoints.llm import LLM
8 from vllm.outputs import CompletionOutput, RequestOutput
9 from vllm.sampling_params import SamplingParams
10 
11 __version__ = "0.1.7"
12 
13 __all__ = [
14     "LLM",
15     "SamplingParams",
16     "RequestOutput",
17     "CompletionOutput",
18     "LLMEngine",
19     "EngineArgs",
20     "AsyncLLMEngine",
21     "AsyncEngineArgs",
22     "initialize_cluster",
23 ]
24
```
--- 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/__init__.py b/vllm/__init__.py
--- a/vllm/__init__.py
+++ b/vllm/__init__.py
@@ -8,7 +8,7 @@
 from vllm.outputs import CompletionOutput, RequestOutput
 from vllm.sampling_params import SamplingParams
 
-__version__ = "0.1.7"
+__version__ = "0.2.0"
 
 __all__ = [
     "LLM",

{"golden_diff": "diff --git a/vllm/__init__.py b/vllm/__init__.py\n--- a/vllm/__init__.py\n+++ b/vllm/__init__.py\n@@ -8,7 +8,7 @@\n from vllm.outputs import CompletionOutput, RequestOutput\n from vllm.sampling_params import SamplingParams\n \n-__version__ = \"0.1.7\"\n+__version__ = \"0.2.0\"\n \n __all__ = [\n     \"LLM\",\n", "issue": "[v0.2.0] Release Tracker\n## Major changes\r\n\r\n* Up to 60% performance improvement by optimizing de-tokenization and sampler\r\n* Initial support for AWQ (performance not optimized)\r\n* Support for RoPE scaling and LongChat\r\n* Support for Mistral-7B\r\n\r\n## PRs to be merged before the release\r\n\r\n- [x] Vectorized sampler: #1048, #820 \r\n- [x] LongChat: #555 \r\n- [x] `TORCH_CUDA_ARCH_LIST` build option: #1074 \r\n- [x] Support for Mistral-7B: #1196 \r\n- [x] #1198  \r\n- ~~[ ] FP32 RoPE kernel: #1061~~ (deferred to the next PR)\n", "before_files": [{"content": "\"\"\"vLLM: a high-throughput and memory-efficient inference engine for LLMs\"\"\"\n\nfrom vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs\nfrom vllm.engine.async_llm_engine import AsyncLLMEngine\nfrom vllm.engine.llm_engine import LLMEngine\nfrom vllm.engine.ray_utils import initialize_cluster\nfrom vllm.entrypoints.llm import LLM\nfrom vllm.outputs import CompletionOutput, RequestOutput\nfrom vllm.sampling_params import SamplingParams\n\n__version__ = \"0.1.7\"\n\n__all__ = [\n    \"LLM\",\n    \"SamplingParams\",\n    \"RequestOutput\",\n    \"CompletionOutput\",\n    \"LLMEngine\",\n    \"EngineArgs\",\n    \"AsyncLLMEngine\",\n    \"AsyncEngineArgs\",\n    \"initialize_cluster\",\n]\n", "path": "vllm/__init__.py"}], "after_files": [{"content": "\"\"\"vLLM: a high-throughput and memory-efficient inference engine for LLMs\"\"\"\n\nfrom vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs\nfrom vllm.engine.async_llm_engine import AsyncLLMEngine\nfrom vllm.engine.llm_engine import LLMEngine\nfrom vllm.engine.ray_utils import initialize_cluster\nfrom vllm.entrypoints.llm import LLM\nfrom vllm.outputs import CompletionOutput, RequestOutput\nfrom vllm.sampling_params import SamplingParams\n\n__version__ = \"0.2.0\"\n\n__all__ = [\n    \"LLM\",\n    \"SamplingParams\",\n    \"RequestOutput\",\n    \"CompletionOutput\",\n    \"LLMEngine\",\n    \"EngineArgs\",\n    \"AsyncLLMEngine\",\n    \"AsyncEngineArgs\",\n    \"initialize_cluster\",\n]\n", "path": "vllm/__init__.py"}]}