常见错误

修复: Docker 找不到 GPU

解决 "could not select device driver" 或 "nvidia-container-cli" 错误

错误信息

docker: Error response from daemon: could not select device driver "" with capabilities: [[gpu]]

或

nvidia-container-cli: initialization error

或

torch.cuda.is_available() 返回 False

根本原因

Docker 无法访问宿主机 GPU。常见原因：

未安装 NVIDIA Container Toolkit - GPU 直通必需
Docker 守护进程未配置 - 缺少 nvidia runtime 配置
缺少 --gpus 参数 - 容器启动时未请求 GPU 访问
驱动未加载 - NVIDIA 内核模块未激活

解决方案

步骤 1: 验证 NVIDIA 驱动


nvidia-smi

应显示 GPU 和驱动版本。如果没有，请先安装 NVIDIA 驱动。

步骤 2: 安装 NVIDIA Container Toolkit

# 添加仓库

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg

curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \

sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \

sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

# 安装工具包

sudo apt-get update

sudo apt-get install -y nvidia-container-toolkit

步骤 3: 配置 Docker

sudo nvidia-ctk runtime configure --runtime=docker

sudo systemctl restart docker

步骤 4: 测试 GPU 访问


docker run --rm --gpus all nvidia/cuda:12.1.1-base-ubuntu22.04 nvidia-smi

步骤 5: 运行容器

始终使用 --gpus all 参数：


docker run --gpus all your-image python -c "import torch; print(torch.cuda.is_available())"

快速检查清单

宿主机 nvidia-smi 正常工作
已安装 nvidia-container-toolkit
安装后已重启 Docker 守护进程
使用 --gpus all 或 --gpus "device=0"

生成支持 GPU 的 Dockerfile

配置选项

部署目标

本地 GPU 或 CPU 环境

框架

版本

CUDA 版本

2025推荐，Blackwell(10.0)原生支持，官方cu128编译包

Python 版本

需要 NVIDIA 驱动版本 >=570.26.00

Dockerfile

1# syntax=docker/dockerfile:1
2# ^ Required for BuildKit cache mounts and advanced features
3 
4# Generated by DockerFit (https://tools.eastondev.com/docker)
5# PYTORCH 2.9.1 + CUDA 12.8 | Python 3.11
6# Multi-stage build for optimized image size
7 
8# ==============================================================================
9# Stage 1: Builder - Install dependencies and compile
10# ==============================================================================
11FROM nvidia/cuda:12.8.0-cudnn-devel-ubuntu24.04 AS builder
12 
13# Build arguments
14ARG DEBIAN_FRONTEND=noninteractive
15 
16# Environment variables
17ENV PYTHONUNBUFFERED=1
18ENV PYTHONDONTWRITEBYTECODE=1
19ENV TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9;9.0;10.0"
20 
21# Install Python 3.11 from deadsnakes PPA (Ubuntu 24.04)
22RUN apt-get update && apt-get install -y --no-install-recommends \
23    software-properties-common \
24    && add-apt-repository -y ppa:deadsnakes/ppa \
25    && apt-get update && apt-get install -y --no-install-recommends \
26    python3.11 \
27    python3.11-venv \
28    python3.11-dev \
29    build-essential \
30    git
31    && rm -rf /var/lib/apt/lists/*
32 
33# Create virtual environment
34ENV VIRTUAL_ENV=/opt/venv
35RUN python3.11 -m venv $VIRTUAL_ENV
36ENV PATH="$VIRTUAL_ENV/bin:$PATH"
37 
38# Upgrade pip
39RUN pip install --no-cache-dir --upgrade pip setuptools wheel
40 
41# Install PyTorch with BuildKit cache
42RUN --mount=type=cache,target=/root/.cache/pip \
43    pip install torch torchvision torchaudio \
44    --index-url https://download.pytorch.org/whl/cu128
45 
46# Install project dependencies
47COPY requirements.txt .
48RUN --mount=type=cache,target=/root/.cache/pip \
49    pip install -r requirements.txt
50 
51# ==============================================================================
52# Stage 2: Runtime - Minimal production image
53# ==============================================================================
54FROM nvidia/cuda:12.8.0-cudnn-runtime-ubuntu24.04 AS runtime
55 
56# Labels
57LABEL maintainer="Generated by DockerFit"
58LABEL version="2.9.1"
59LABEL description="PYTORCH 2.9.1 + CUDA 12.8"
60 
61# Environment variables
62ENV PYTHONUNBUFFERED=1
63ENV PYTHONDONTWRITEBYTECODE=1
64ENV NVIDIA_VISIBLE_DEVICES=all
65ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
66 
67# Install Python 3.11 runtime from deadsnakes PPA (Ubuntu 24.04)
68RUN apt-get update && apt-get install -y --no-install-recommends \
69    software-properties-common \
70    && add-apt-repository -y ppa:deadsnakes/ppa \
71    && apt-get update && apt-get install -y --no-install-recommends \
72    python3.11 \
73    libgomp1
74    && apt-get remove -y software-properties-common \
75    && apt-get autoremove -y \
76    && rm -rf /var/lib/apt/lists/*
77 
78# Create non-root user for security
79ARG USERNAME=appuser
80ARG USER_UID=1000
81ARG USER_GID=$USER_UID
82RUN groupadd --gid $USER_GID $USERNAME \
83    && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
84 
85# Copy virtual environment from builder
86COPY --from=builder --chown=$USERNAME:$USERNAME /opt/venv /opt/venv
87ENV VIRTUAL_ENV=/opt/venv
88ENV PATH="$VIRTUAL_ENV/bin:$PATH"
89 
90# Set working directory
91WORKDIR /app
92 
93# Copy application code
94COPY --chown=$USERNAME:$USERNAME . .
95 
96# Switch to non-root user
97USER $USERNAME
98 
99# Expose port
100EXPOSE 8000
101 
102# Default command
103CMD ["python", "main.py"]

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