init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

examples/offline_inference_sleep_mode_npu.py

@@ -20,16 +20,17 @@ import os
 
 import torch
 from vllm import LLM, SamplingParams
-from vllm.utils import GiB_bytes
+from vllm.utils.mem_constants import GiB_bytes
 
 os.environ["VLLM_USE_MODELSCOPE"] = "True"
 os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
 
+
 def main():
     prompt = "How are you?"
 
     free, total = torch.npu.mem_get_info()
-    print(f"Free memory before sleep: {free / 1024 ** 3:.2f} GiB")
+    print(f"Free memory before sleep: {free / 1024**3:.2f} GiB")
     # record npu memory use baseline in case other process is running
     used_bytes_baseline = total - free
     llm = LLM("Qwen/Qwen2.5-0.5B-Instruct", enable_sleep_mode=True)
@@ -39,9 +40,7 @@ def main():
     llm.sleep(level=1)
 
     free_npu_bytes_after_sleep, total = torch.npu.mem_get_info()
-    print(
-        f"Free memory after sleep: {free_npu_bytes_after_sleep / 1024 ** 3:.2f} GiB"
-    )
+    print(f"Free memory after sleep: {free_npu_bytes_after_sleep / 1024**3:.2f} GiB")
     used_bytes = total - free_npu_bytes_after_sleep - used_bytes_baseline
     # now the memory usage should be less than the model weights
     # (0.5B model, 1GiB weights)