Докер Tensorflow не использует графический процессор ⇐ Python

[Anonymous]

Я пытаюсь заставить Tensorflow работать на моем Ubuntu 24.04.1 с графическим процессором.
Согласно этой странице:

Docker — это самый простой способ запустить TensorFlow на графическом процессоре, поскольку для хост-компьютера требуется только драйвер NVIDIA®.

Поэтому я пытаюсь использовать Docker.
Я проверяю, работает ли мой графический процессор с Docker, запустив docker run --gpus all --rm nvidia/cuda:12.6.2-cudnn-runtime-ubuntu24.04 nvidia-smi . Результат этого:

Код: Выделить всё

==========
== CUDA ==
==========

CUDA Version 12.6.2

Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.

Sat Oct 26 01:16:50 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 560.35.03              Driver Version: 560.35.03      CUDA Version: 12.6     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA TITAN RTX               Off |   00000000:01:00.0 Off |                  N/A |
| 41%   40C    P8             24W /  280W |       1MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

(Примечание: я не использую предложенную ими команду, потому что docker run --gpus all --rm nvidia/cuda nvidia-smi не работает из-за nvidia/cuda больше не имеет тега «последняя версия»)
Так что, похоже, все работает. Однако когда я бегу:

Код: Выделить всё

docker run --gpus all -it --rm tensorflow/tensorflow:latest-gpu \
python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

Вывод:

Код: Выделить всё

2024-10-26 01:20:51.021242: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1729905651.033544       1 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1729905651.037491       1 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-10-26 01:20:51.050486: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
W0000 00:00:1729905652.350499       1 gpu_device.cc:2344] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
[]

Это означает, что Tensorflow не обнаружил графического процессора.
Что я здесь делаю не так?

Подробнее здесь: https://stackoverflow.com/questions/791 ... -using-gpu