TensorFlow : Docker छवि का उपयोग करें (GPU)2023/09/21 |
TensorFlow स्थापित करें जो मशीन लर्निंग लाइब्रेरी है।
इस उदाहरण पर, GPU समर्थन के साथ TensorFlow आधिकारिक Docker छवि स्थापित करें और इसे कंटेनरों पर चलाएं।
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[1] | |
[2] | यह TensorFlow Docker (GPU) का उपयोग करने का उदाहरण है। |
root@dlp:~#
root@dlp:~# docker pull tensorflow/tensorflow:latest-gpu
docker images REPOSITORY TAG IMAGE ID CREATED SIZE tensorflow/tensorflow latest-gpu c8d4e2940044 34 hours ago 5.97GB tensorflow/tensorflow latest-jupyter c94342dbd1e8 34 hours ago 1.68GB tensorflow/tensorflow latest 976c17ec6daa 34 hours ago 1.46GB # चलाने के लिए सत्यापित करें [nvidia-smi] root@dlp:~# docker run --gpus all --rm tensorflow/tensorflow:latest-gpu nvidia-smi Thu Sep 8 05:51:34 2022 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 510.85.02 Driver Version: 510.85.02 CUDA Version: 11.6 | |-------------------------------+----------------------+----------------------+ | 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 GeForce ... Off | 00000000:05:00.0 Off | N/A | | 0% 49C P5 10W / 120W | 0MiB / 6144MiB | 1% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+ # TensorFlow चलाने के लिए सत्यापित करें root@dlp:~# docker run --gpus all --rm tensorflow/tensorflow:latest-gpu \ python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))" 2022-09-08 05:52:03.867257: 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 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-09-08 05:52:04.156322: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2022-09-08 05:52:06.594635: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:06.606274: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:06.606636: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:06.608431: 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 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-09-08 05:52:06.609355: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:06.609659: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:06.609866: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:07.346278: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:07.346796: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:07.346987: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:980] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-09-08 05:52:07.347152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 5381 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1060 6GB, pci bus id: 0000:05:00.0, compute capability: 6.1 tf.Tensor(502.0998, shape=(), dtype=float32) |
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