TensorFlow 2.10.0无法识别GPU的问题排查与解决求助

环境与安装步骤 #

通过conda创建环境并安装TensorFlow：

conda create -n foo python=3.10
conda activate foo
conda install mamba
mamba install tensorflow -c conda-forge
mamba install cudnn cudatoolkit

安装完成后TensorFlow版本为2.10.0，本地已预装CUDA 11.2和cuDNN 8.1。

问题现象 #

运行以下代码时，GPU列表为空：

import tensorflow as tf
print(f"GPUs available: {tf.config.list_physical_devices('GPU')}")

测试代码及日志显示当前使用纯CPU版本TensorFlow：
测试代码：

import tensorflow as tf
import numpy as np

def make_nn():
    model = tf.keras.models.Sequential()
    model.add(tf.keras.layers.Dense(1, input_shape=(1,)))
    model.compile(loss='mean_squared_error', optimizer='sgd')
    return model

def dataset():
    x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
    y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
    return tf.data.Dataset.from_tensor_slices((x, y)).batch(1)

def main():
    model = make_nn()
    model.fit(dataset(), epochs=1, steps_per_epoch=9)

if __name__ == '__main__':
    print(f"GPUs available: {tf.config.list_physical_devices('GPU')}")
    print(f"Built with cuda: {tf.test.is_built_with_cuda()}")
    main()

输出日志：

GPUs available: []
Built with cuda: False
2023-02-06 09:47:32.744450: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-06 09:47:32.779280: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.

系统与硬件信息 #

• 系统：Windows 10
• 显卡：RTX 3060Ti
• nvidia-smi输出：

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 528.24       Driver Version: 528.24       CUDA Version: 12.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ... WDDM  | 00000000:09:00.0  On |                  N/A |
| 30%   43C    P8    16W / 200W |    809MiB /  8192MiB |      3%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      7176    C+G   ...perience\NVIDIA Share.exe    N/A      |
|    0   N/A  N/A      9240    C+G   C:\Windows\explorer.exe         N/A      |
|    0   N/A  N/A     12936    C+G   ...cw5n1h2txyewy\LockApp.exe    N/A      |
|    0   N/A  N/A     13652    C+G   ...e\PhoneExperienceHost.exe    N/A      |
|    0   N/A  N/A     14020    C+G   ...2txyewy\TextInputHost.exe    N/A      |
|    0   N/A  N/A     14888    C+G   ...ser\Application\brave.exe    N/A      |
|    0   N/A  N/A     15112    C+G   ...5n1h2txyewy\SearchApp.exe    N/A      |
|    0   N/A  N/A     16516    C+G   ...oft OneDrive\OneDrive.exe    N/A      |
|    0   N/A  N/A     18296    C+G   ...aming\Spotify\Spotify.exe    N/A      |
|    0   N/A  N/A     18624    C+G   ...in7x64\steamwebhelper.exe    N/A      |
|    0   N/A  N/A     18672    C+G   ...\app-1.0.9010\Discord.exe    N/A      |
|    0   N/A  N/A     18828    C+G   ...lPanel\SystemSettings.exe    N/A      |
|    0   N/A  N/A     19284    C+G   ...Central\Razer Central.exe    N/A      |
|    0   N/A  N/A     20020    C+G   ...arp.BrowserSubprocess.exe    N/A      |
|    0   N/A  N/A     22912    C+G   ...8wekyb3d8bbwe\Cortana.exe    N/A      |
|    0   N/A  N/A     24848    C+G   ...ontend\Docker Desktop.exe    N/A      |
|    0   N/A  N/A     25804    C+G   ...y\ShellExperienceHost.exe    N/A      |
|    0   N/A  N/A     27064    C+G   ...8bbwe\WindowsTerminal.exe    N/A      |
+-----------------------------------------------------------------------------+

• nvcc -V输出：

Copyright (c) 2005-2021 NVIDIA Corporation
Built on Sun_Feb_14_22:08:44_Pacific_Standard_Time_2021
Cuda compilation tools, release 11.2, V11.2.152
Build cuda_11.2.r11.2/compiler.29618528_0

解决方案 #

1. 匹配TensorFlow与CUDA版本 #

TensorFlow 2.10.0官方要求CUDA 11.2、cuDNN 8.1.0，先检查conda环境内的CUDA组件版本：

conda list cudatoolkit

若版本不符，重新安装指定版本：

mamba install cudatoolkit=11.2 cudnn=8.1 -c conda-forge

2. 安装GPU版TensorFlow #

当前安装的是纯CPU版，卸载后重新安装GPU专属包：

mamba remove tensorflow
mamba install tensorflow-gpu=2.10.0 -c conda-forge

注：TensorFlow 2.10是conda-forge上最后一个单独提供tensorflow-gpu包的版本，后续版本统一使用tensorflow包，但2.10版本需单独安装GPU版。

3. 配置环境变量（Windows） #

确保conda环境内的CUDA库被优先识别，激活环境后执行：

set PATH=%CONDA_PREFIX%\Library\bin;%PATH%

也可手动添加系统环境变量：

• 新增CUDA_PATH变量，值为你的conda环境路径\Library（例如C:\Users\你的用户名\.conda\envs\foo\Library）
• 将%CUDA_PATH%\bin添加到系统PATH最前端

4. 验证GPU支持 #

重新激活环境后，运行以下代码确认：

import tensorflow as tf
print(tf.test.is_built_with_cuda())
print(tf.config.list_physical_devices('GPU'))
print(tf.test.gpu_device_name())

若输出能识别到GPU，说明配置成功。

5. 检查驱动兼容性 #

当前驱动版本528.24支持CUDA 12.0，虽向下兼容CUDA 11.2，若仍有问题，可尝试降级到CUDA 11.2对应的驱动版本（如460.x系列）。

内容的提问来源于stack exchange，提问作者João Areias