当前位置: 首页 > news >正文

RuntimeError: Unexpected error from cudaGetDeviceCount

RuntimeError: Unexpected error from cudaGetDeviceCount

  • 0. 引言
  • 1. 临时解决方法

0. 引言

使用 vllm-0.4.2 部署时,多卡正常运行。升级到 vllm-0.5.1 时,报错如下:

(VllmWorkerProcess pid=30692) WARNING 07-12 08:16:22 utils.py:562] Using 'pin_memory=False' as WSL is detected. This may slow down the performance.
(VllmWorkerProcess pid=30693) WARNING 07-12 08:16:22 utils.py:562] Using 'pin_memory=False' as WSL is detected. This may slow down the performance.
(VllmWorkerProcess pid=30694) WARNING 07-12 08:16:22 utils.py:562] Using 'pin_memory=False' as WSL is detected. This may slow down the performance.
WARNING 07-12 08:16:22 utils.py:562] Using 'pin_memory=False' as WSL is detected. This may slow down the performance.
(VllmWorkerProcess pid=30693) Process VllmWorkerProcess:
(VllmWorkerProcess pid=30693) Traceback (most recent call last):
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
(VllmWorkerProcess pid=30693)     self.run()
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 108, in run
(VllmWorkerProcess pid=30693)     self._target(*self._args, **self._kwargs)
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/multiproc_worker_utils.py", line 210, in _run_worker_process
(VllmWorkerProcess pid=30693)     worker = worker_factory()
(VllmWorkerProcess pid=30693)              ^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 68, in _create_worker
(VllmWorkerProcess pid=30693)     wrapper.init_worker(**self._get_worker_kwargs(local_rank, rank,
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker_base.py", line 334, in init_worker
(VllmWorkerProcess pid=30693)     self.worker = worker_class(*args, **kwargs)
(VllmWorkerProcess pid=30693)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker.py", line 85, in __init__
(VllmWorkerProcess pid=30693)     self.model_runner: GPUModelRunnerBase = ModelRunnerClass(
(VllmWorkerProcess pid=30693)                                             ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 217, in __init__
(VllmWorkerProcess pid=30693)     self.attn_backend = get_attn_backend(
(VllmWorkerProcess pid=30693)                         ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 45, in get_attn_backend
(VllmWorkerProcess pid=30693)     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
(VllmWorkerProcess pid=30693)               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 151, in which_attn_to_use
(VllmWorkerProcess pid=30693)     if torch.cuda.get_device_capability()[0] < 8:
(VllmWorkerProcess pid=30693)        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 430, in get_device_capability
(VllmWorkerProcess pid=30693)     prop = get_device_properties(device)
(VllmWorkerProcess pid=30693)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 444, in get_device_properties
(VllmWorkerProcess pid=30693)     _lazy_init()  # will define _get_device_properties
(VllmWorkerProcess pid=30693)     ^^^^^^^^^^^^
(VllmWorkerProcess pid=30693)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 293, in _lazy_init
(VllmWorkerProcess pid=30693)     torch._C._cuda_init()
(VllmWorkerProcess pid=30693) RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 2: out of memory
(VllmWorkerProcess pid=30692) Process VllmWorkerProcess:
(VllmWorkerProcess pid=30692) Traceback (most recent call last):
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
(VllmWorkerProcess pid=30692)     self.run()
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 108, in run
(VllmWorkerProcess pid=30692)     self._target(*self._args, **self._kwargs)
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/multiproc_worker_utils.py", line 210, in _run_worker_process
(VllmWorkerProcess pid=30692)     worker = worker_factory()
(VllmWorkerProcess pid=30692)              ^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 68, in _create_worker
(VllmWorkerProcess pid=30692)     wrapper.init_worker(**self._get_worker_kwargs(local_rank, rank,
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker_base.py", line 334, in init_worker
(VllmWorkerProcess pid=30692)     self.worker = worker_class(*args, **kwargs)
(VllmWorkerProcess pid=30692)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker.py", line 85, in __init__
(VllmWorkerProcess pid=30692)     self.model_runner: GPUModelRunnerBase = ModelRunnerClass(
(VllmWorkerProcess pid=30692)                                             ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 217, in __init__
(VllmWorkerProcess pid=30692)     self.attn_backend = get_attn_backend(
(VllmWorkerProcess pid=30692)                         ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 45, in get_attn_backend
(VllmWorkerProcess pid=30692)     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
(VllmWorkerProcess pid=30692)               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 151, in which_attn_to_use
(VllmWorkerProcess pid=30692)     if torch.cuda.get_device_capability()[0] < 8:
(VllmWorkerProcess pid=30692)        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 430, in get_device_capability
(VllmWorkerProcess pid=30692)     prop = get_device_properties(device)
(VllmWorkerProcess pid=30692)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 444, in get_device_properties
(VllmWorkerProcess pid=30692)     _lazy_init()  # will define _get_device_properties
(VllmWorkerProcess pid=30692)     ^^^^^^^^^^^^
(VllmWorkerProcess pid=30692)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 293, in _lazy_init
(VllmWorkerProcess pid=30692)     torch._C._cuda_init()
(VllmWorkerProcess pid=30692) RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 2: out of memory
(VllmWorkerProcess pid=30694) Process VllmWorkerProcess:
(VllmWorkerProcess pid=30694) Traceback (most recent call last):
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
(VllmWorkerProcess pid=30694)     self.run()
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/multiprocessing/process.py", line 108, in run
(VllmWorkerProcess pid=30694)     self._target(*self._args, **self._kwargs)
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/multiproc_worker_utils.py", line 210, in _run_worker_process
(VllmWorkerProcess pid=30694)     worker = worker_factory()
(VllmWorkerProcess pid=30694)              ^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 68, in _create_worker
(VllmWorkerProcess pid=30694)     wrapper.init_worker(**self._get_worker_kwargs(local_rank, rank,
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker_base.py", line 334, in init_worker
(VllmWorkerProcess pid=30694)     self.worker = worker_class(*args, **kwargs)
(VllmWorkerProcess pid=30694)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/worker.py", line 85, in __init__
(VllmWorkerProcess pid=30694)     self.model_runner: GPUModelRunnerBase = ModelRunnerClass(
(VllmWorkerProcess pid=30694)                                             ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 217, in __init__
(VllmWorkerProcess pid=30694)     self.attn_backend = get_attn_backend(
(VllmWorkerProcess pid=30694)                         ^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 45, in get_attn_backend
(VllmWorkerProcess pid=30694)     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
(VllmWorkerProcess pid=30694)               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py", line 151, in which_attn_to_use
(VllmWorkerProcess pid=30694)     if torch.cuda.get_device_capability()[0] < 8:
(VllmWorkerProcess pid=30694)        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 430, in get_device_capability
(VllmWorkerProcess pid=30694)     prop = get_device_properties(device)
(VllmWorkerProcess pid=30694)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 444, in get_device_properties
(VllmWorkerProcess pid=30694)     _lazy_init()  # will define _get_device_properties
(VllmWorkerProcess pid=30694)     ^^^^^^^^^^^^
(VllmWorkerProcess pid=30694)   File "/root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/torch/cuda/__init__.py", line 293, in _lazy_init
(VllmWorkerProcess pid=30694)     torch._C._cuda_init()
(VllmWorkerProcess pid=30694) RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 2: out of memory
ERROR 07-12 08:16:26 multiproc_worker_utils.py:120] Worker VllmWorkerProcess pid 30693 died, exit code: 1
INFO 07-12 08:16:26 multiproc_worker_utils.py:123] Killing local vLLM worker processes

1. 临时解决方法

vi /root/miniconda3/envs/vllm2025/lib/python3.10/site-packages/vllm/attention/selector.py--- 设置成固定的 `backend = _Backend.XFORMERS`。# backend = which_attn_to_use(num_heads, head_size, num_kv_heads,#                           sliding_window, dtype, kv_cache_dtype,#                            block_size)backend = _Backend.XFORMERS
---

完结!

相关文章:

RuntimeError: Unexpected error from cudaGetDeviceCount

RuntimeError: Unexpected error from cudaGetDeviceCount 0. 引言1. 临时解决方法 0. 引言 使用 vllm-0.4.2 部署时&#xff0c;多卡正常运行。升级到 vllm-0.5.1 时&#xff0c;报错如下&#xff1a; (VllmWorkerProcess pid30692) WARNING 07-12 08:16:22 utils.py:562] U…...

uboot学习:(一)基础认知

目录 uboot是一个裸机程序&#xff08;bootloader&#xff09; 作用 要运行linux系统时&#xff0c;如何从外置的flash拷贝到DDR中&#xff0c;才能启动 uboot使用步骤 步骤1中的命令例子 注意 uboot源码获取方法 uboot是一个裸机程序&#xff08;bootloader&#xff09…...

每天一个数据分析题(四百二十六)- 总体方差

为了比较两个总体方差&#xff0c;我们通常检验两个总体的() A. 方差差 B. 方差比 C. 方差乘积 D. 方差和 数据分析认证考试介绍&#xff1a;点击进入 题目来源于CDA模拟题库 点击此处获取答案 数据分析专项练习题库 内容涵盖Python&#xff0c;SQL&#xff0c;统计学&a…...

【C++】设计一套基于C++与C#的视频播放软件

在开发一款集视频播放与丰富交互功能于一体的软件时&#xff0c;结合C的高性能与C#在界面开发上的便捷性&#xff0c;是一个高效且实用的选择。以下&#xff0c;我们将概述这样一个系统的架构设计、关键技术点以及各功能模块的详细实现思路。 一、系统架构设计 1. 架构概览 …...

数学建模中的辅助变量、中间变量、指示变量

在数学建模中&#xff0c;除了决策变量外&#xff0c;还有一些其他类型的变量&#xff0c;如中间变量、辅助变量和指示变量。每种变量在模型中都有特定的用途和意义。以下是对这些变量的详细解释&#xff1a; 1. 决策变量&#xff08;Decision Variables&#xff09; 定义&am…...

python的seek()和tell()

seek() seek() 是用来在文件中移动指针位置的方法。它的作用是将文件内部的当前位置设置为指定的位置。 seek(offset, whence) 参数说明 offset: 这是一个整数值&#xff0c;表示相对于起始位置的偏移量。如果是正数&#xff0c;表示向文件末尾方向移动&#xff1b;如果是负…...

Go泛型详解

引子 如果我们要写一个函数分别比较2个整数和浮点数的大小&#xff0c;我们就要写2个函数。如下&#xff1a; func Min(x, y float64) float64 {if x < y {return x}return y }func MinInt(x, y int) int {if x < y {return x}return y }2个函数&#xff0c;除了数据类…...

【每日一练】python之sum()求和函数实例讲解

在Python中&#xff0c; sum()是一个内置函数&#xff0c;用于计算可迭代对象&#xff08;如列表、元组等&#xff09;中所有元素的总和。如下实例&#xff1a; """ 收入支出统计小程序 知识点:用户输入获取列表元素添加sum()函数&#xff0c;统计作用 "&…...

打造智慧校园德育管理,提升学生操行基础分

智慧校园的德育管理系统内嵌的操行基础分功能&#xff0c;是对学生日常行为规范和道德素养进行量化评估的一个创新实践。该功能通过将抽象的道德品质转化为具体可量化的指标&#xff0c;如遵守纪律、尊师重道、团结协作、爱护环境及参与集体活动的积极性等&#xff0c;为每个学…...

自定义函数---随机数系列函数

大家有没有发现平常在写随机数的时候&#xff0c;需要引入很多的头文件&#xff0c;然后还需要用一些复杂的函数&#xff0c;大家可能不太习惯&#xff0c;于是我就制作了一个头文件 // random_number.h #ifndef RANDOM_NUMBER_H // 预处理指令&#xff0c;防止头文件被重复包含…...

一文了解5G新通话技术演进与业务模型

5G新通话简介 5G新通话&#xff0c;也被称为VoNR&#xff0c;是基于R16及后续协议产生的一种增强型语音通话业务。 它在IMS网络里新增数据通道&#xff08;Data Channel&#xff09;&#xff0c;承载通话时的文本、图片、涂鸦、菜单等信息。它能在传统话音业务基础上提供更多服…...

视频使用操作说明书-T80002系列视频编码器如何对接海康NVR硬盘录像机,包括T80002系列高清HDMI编码器、4K超高清HDMI编码器

视频使用操作说明书-T80002系列视频编码器如何对接海康NVR硬盘录像机&#xff0c;包括T80002系列高清HDMI编码器、4K超高清HDMI编码器。 视频使用操作说明书-T80002系列视频编码器如何对接海康NVR硬盘录像机&#xff0c;包括T80002系列高清HDMI编码器、4K超高清HDMI编码器 同三…...

el-input-number计数器change事件校验数据,改变绑定数据值后change方法失效问题的原因及解决方法

在change事件中如果对el-input-number绑定的数据进行更改&#xff0c;会出现change事件失效的问题 试过&#xff1a;this.$set()及赋值等方法&#xff0c;都无法解决 解决方法&#xff1a;用$nextTick函数对绑定值进行更改&#xff08; this.$nextTick(() > { this.绑定…...

将vue项目整合到springboot项目中并在阿里云上运行

第一步&#xff0c;使用springboot中的thymeleaf模板引擎 导入依赖 <!-- thymeleaf 模板 --><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-thymeleaf</artifactId></dependency> 在r…...

AC修炼计划(AtCoder Regular Contest 179)A~C

A - Partition A题传送门 这道题不难发现&#xff0c;如果数字最终的和大于等于K&#xff0c;我们可以把这个原数列从大到小排序&#xff0c;得到最终答案。 如果和小于K&#xff0c;则从小到大排序&#xff0c;同时验证是否符合要求。 #pragma GCC optimize(3) //O2优化开启…...

开发编码规范笔记

前言 &#xff08;1&#xff09;该博客仅用于个人笔记 格式转换 &#xff08;1&#xff09;查看是 LF 行尾还是CRLF 行尾。 # 单个文件&#xff0c;\n 表示 LF 行尾。\r\n 表示 CRLF 行尾。 hexdump -c <yourfile> # 单个文件&#xff0c;$ 表示 LF 行尾。^M$ 表示 CRLF …...

spring boot easyexcel

1.pom <!-- easyexcel 依赖 --><dependency><groupId>com.alibaba</groupId><artifactId>easyexcel</artifactId><version>3.1.1</version></dependency><dependency><groupId>org.projectlombok</group…...

Docker 部署 ShardingSphere-Proxy 数据库中间件

文章目录 Github官网文档ShardingSphere-Proxymysql-connector-java 驱动下载conf 配置global.yamldatabase-sharding.yamldatabase-readwrite-splitting.yamldockerdocker-compose.yml Apache ShardingSphere 是一款分布式的数据库生态系统&#xff0c; 可以将任意数据库转换为…...

Qt常用快捷键

Qt中的常用快捷键 F1查看帮助F2快速到变量声明 从cpp→hShift F2 函数的声明和定义之间快速切换 &#xff1b;选中函数名 &#xff0c;从h→cppF4在 cpp 和 h 文件切换 Shift F4在cpp/h文件与 界面文件中切换Ctrl /注释当前行 或者选中的区域Ctrl I自动缩进当前…...

关于RiboSeq分析流程的总结

最近关注了一下RiboSeq的分析方法&#xff0c;方法挺多的&#xff0c;但是无论哪种软件&#xff0c;都会存在或多或少的问题&#xff0c;一点问题不存在的软件不存在&#xff0c;问题的原因出在&#xff0c;1.有的脚本是用python2编写的&#xff0c;目前python2已经不能用了 2.…...

XCTF-web-easyupload

试了试php&#xff0c;php7&#xff0c;pht&#xff0c;phtml等&#xff0c;都没有用 尝试.user.ini 抓包修改将.user.ini修改为jpg图片 在上传一个123.jpg 用蚁剑连接&#xff0c;得到flag...

OkHttp 中实现断点续传 demo

在 OkHttp 中实现断点续传主要通过以下步骤完成&#xff0c;核心是利用 HTTP 协议的 Range 请求头指定下载范围&#xff1a; 实现原理 Range 请求头&#xff1a;向服务器请求文件的特定字节范围&#xff08;如 Range: bytes1024-&#xff09; 本地文件记录&#xff1a;保存已…...

Java线上CPU飙高问题排查全指南

一、引言 在Java应用的线上运行环境中&#xff0c;CPU飙高是一个常见且棘手的性能问题。当系统出现CPU飙高时&#xff0c;通常会导致应用响应缓慢&#xff0c;甚至服务不可用&#xff0c;严重影响用户体验和业务运行。因此&#xff0c;掌握一套科学有效的CPU飙高问题排查方法&…...

短视频矩阵系统文案创作功能开发实践,定制化开发

在短视频行业迅猛发展的当下&#xff0c;企业和个人创作者为了扩大影响力、提升传播效果&#xff0c;纷纷采用短视频矩阵运营策略&#xff0c;同时管理多个平台、多个账号的内容发布。然而&#xff0c;频繁的文案创作需求让运营者疲于应对&#xff0c;如何高效产出高质量文案成…...

PAN/FPN

import torch import torch.nn as nn import torch.nn.functional as F import mathclass LowResQueryHighResKVAttention(nn.Module):"""方案 1: 低分辨率特征 (Query) 查询高分辨率特征 (Key, Value).输出分辨率与低分辨率输入相同。"""def __…...

华为OD机考-机房布局

import java.util.*;public class DemoTest5 {public static void main(String[] args) {Scanner in new Scanner(System.in);// 注意 hasNext 和 hasNextLine 的区别while (in.hasNextLine()) { // 注意 while 处理多个 caseSystem.out.println(solve(in.nextLine()));}}priv…...

CVPR2025重磅突破:AnomalyAny框架实现单样本生成逼真异常数据,破解视觉检测瓶颈!

本文介绍了一种名为AnomalyAny的创新框架&#xff0c;该方法利用Stable Diffusion的强大生成能力&#xff0c;仅需单个正常样本和文本描述&#xff0c;即可生成逼真且多样化的异常样本&#xff0c;有效解决了视觉异常检测中异常样本稀缺的难题&#xff0c;为工业质检、医疗影像…...

react-pdf(pdfjs-dist)如何兼容老浏览器(chrome 49)

之前都是使用react-pdf来渲染pdf文件&#xff0c;这次有个需求是要兼容xp环境&#xff0c;xp上chrome最高支持到49&#xff0c;虽然说iframe或者embed都可以实现预览pdf&#xff0c;但为了后续的定制化需求&#xff0c;还是需要使用js库来渲染。 chrome 49测试环境 能用的测试…...

NineData数据库DevOps功能全面支持百度智能云向量数据库 VectorDB,助力企业 AI 应用高效落地

NineData 的数据库 DevOps 解决方案已完成对百度智能云向量数据库 VectorDB 的全链路适配&#xff0c;成为国内首批提供 VectorDB 原生操作能力的服务商。此次合作聚焦 AI 开发核心场景&#xff0c;通过标准化 SQL 工作台与细粒度权限管控两大能力&#xff0c;助力企业安全高效…...

今日行情明日机会——20250609

上证指数放量上涨&#xff0c;接近3400点&#xff0c;个股涨多跌少。 深证放量上涨&#xff0c;但有个小上影线&#xff0c;相对上证走势更弱。 2025年6月9日涨停股主要行业方向分析&#xff08;基于最新图片数据&#xff09; 1. 医药&#xff08;11家涨停&#xff09; 代表标…...