vllm/vllm/utils.py
Woosuk Kwon 37ca558103
Optimize model execution with CUDA graph (#1926)
Co-authored-by: Chen Shen <scv119@gmail.com>
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>
2023-12-16 21:12:08 -08:00

62 lines
1.4 KiB
Python

import enum
import socket
import uuid
from platform import uname
import psutil
import torch
from vllm._C import cuda_utils
class Device(enum.Enum):
GPU = enum.auto()
CPU = enum.auto()
class Counter:
def __init__(self, start: int = 0) -> None:
self.counter = start
def __next__(self) -> int:
i = self.counter
self.counter += 1
return i
def reset(self) -> None:
self.counter = 0
def is_hip() -> bool:
return torch.version.hip is not None
def get_max_shared_memory_bytes(gpu: int = 0) -> int:
"""Returns the maximum shared memory per thread block in bytes."""
# https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html
cudaDevAttrMaxSharedMemoryPerBlockOptin = 97 if not is_hip() else 74
max_shared_mem = cuda_utils.get_device_attribute(
cudaDevAttrMaxSharedMemoryPerBlockOptin, gpu)
return int(max_shared_mem)
def get_cpu_memory() -> int:
"""Returns the total CPU memory of the node in bytes."""
return psutil.virtual_memory().total
def random_uuid() -> str:
return str(uuid.uuid4().hex)
def in_wsl() -> bool:
# Reference: https://github.com/microsoft/WSL/issues/4071
return "microsoft" in " ".join(uname()).lower()
def get_open_port():
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.bind(("", 0))
return s.getsockname()[1]