大服务器配置tensorflow环境
创建环境
(base) bim@bim-PowerEdge-R730:~$ conda create -n mask_rcnn_tf2 python==3.7
Solving environment: done
## Package Plan ##
environment location: /home/bim/anaconda3/envs/mask_rcnn_tf2
added / updated specs:
- python==3.7
The following packages will be downloaded:
package | build
---------------------------|-----------------
readline-7.0 | h7b6447c_5 392 KB http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
openssl-1.0.2u | h7b6447c_0 3.1 MB http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libedit-3.1.20210910 | h7f8727e_0 191 KB http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python-3.7.0 | h6e4f718_3 30.6 MB http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
sqlite-3.33.0 | h62c20be_0 2.0 MB http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
------------------------------------------------------------
Total: 36.3 MB
The following NEW packages will be INSTALLED:
_libgcc_mutex: 0.1-main http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ca-certificates: 2022.4.26-h06a4308_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
certifi: 2021.10.8-py37h06a4308_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libedit: 3.1.20210910-h7f8727e_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libffi: 3.2.1-1 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
libgcc-ng: 9.1.0-hdf63c60_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libstdcxx-ng: 9.1.0-hdf63c60_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ncurses: 6.3-h7f8727e_2 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
openssl: 1.0.2u-h7b6447c_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pip: 21.2.2-py37h06a4308_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python: 3.7.0-h6e4f718_3 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
readline: 7.0-h7b6447c_5 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
setuptools: 61.2.0-py37h06a4308_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
sqlite: 3.33.0-h62c20be_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
tk: 8.6.11-h1ccaba5_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
wheel: 0.37.1-pyhd3eb1b0_0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
xz: 5.2.5-h7f8727e_1 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
zlib: 1.2.11-0 http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
Proceed ([y]/n)? y
Downloading and Extracting Packages
readline-7.0 | 392 KB | ###################################################################################################################################################################################################### | 100%
openssl-1.0.2u | 3.1 MB | ###################################################################################################################################################################################################### | 100%
libedit-3.1.20210910 | 191 KB | ###################################################################################################################################################################################################### | 100%
python-3.7.0 | 30.6 MB | ###################################################################################################################################################################################################### | 100%
sqlite-3.33.0 | 2.0 MB | ###################################################################################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate mask_rcnn_tf2
#
# To deactivate an active environment, use
#
# $ conda deactivate
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$ uname -a
Linux bim-PowerEdge-R730 5.13.0-30-generic #33~20.04.1-Ubuntu SMP Mon Feb 7 14:25:10 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$
激活环境
conda activate mask_rcnn_tf2
安装tensorflow-gpu
(mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ pip install tensorflow-gpu==2.3.0 Collecting tensorflow-gpu==2.3.0 Downloading tensorflow_gpu-2.3.0-cp37-cp37m-manylinux2010_x86_64.whl (320.4 MB) |████████████████████████████████| 320.4 MB 57 kB/s Collecting h5py<2.11.0,>=2.10.0 Using cached h5py-2.10.0-cp37-cp37m-manylinux1_x86_64.whl (2.9 MB) Collecting absl-py>=0.7.0 Using cached absl_py-1.0.0-py3-none-any.whl (126 kB) Collecting tensorflow-estimator<2.4.0,>=2.3.0 Downloading tensorflow_estimator-2.3.0-py2.py3-none-any.whl (459 kB) |████████████████████████████████| 459 kB 4.7 MB/s Collecting google-pasta>=0.1.8 Using cached google_pasta-0.2.0-py3-none-any.whl (57 kB) Collecting opt-einsum>=2.3.2 Using cached opt_einsum-3.3.0-py3-none-any.whl (65 kB) Collecting tensorboard<3,>=2.3.0 Using cached tensorboard-2.9.0-py3-none-any.whl (5.8 MB) Collecting scipy==1.4.1 Downloading scipy-1.4.1-cp37-cp37m-manylinux1_x86_64.whl (26.1 MB) |████████████████████████████████| 26.1 MB 4.1 MB/s Collecting numpy<1.19.0,>=1.16.0 Downloading numpy-1.18.5-cp37-cp37m-manylinux1_x86_64.whl (20.1 MB) |████████████████████████████████| 20.1 MB 6.4 MB/s Collecting six>=1.12.0 Using cached six-1.16.0-py2.py3-none-any.whl (11 kB) Collecting keras-preprocessing<1.2,>=1.1.1 Using cached Keras_Preprocessing-1.1.2-py2.py3-none-any.whl (42 kB) Requirement already satisfied: wheel>=0.26 in ./anaconda3/envs/mask_rcnn_tf2/lib/python3.7/site-packages (from tensorflow-gpu==2.3.0) (0.37.1) Collecting wrapt>=1.11.1 Using cached wrapt-1.14.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (75 kB) Collecting termcolor>=1.1.0 Using cached termcolor-1.1.0-py3-none-any.whl Collecting gast==0.3.3 Using cached gast-0.3.3-py2.py3-none-any.whl (9.7 kB) Collecting protobuf>=3.9.2 Using cached protobuf-3.20.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.0 MB) Collecting grpcio>=1.8.6 Using cached grpcio-1.46.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.4 MB) Collecting astunparse==1.6.3 Using cached astunparse-1.6.3-py2.py3-none-any.whl (12 kB) Collecting werkzeug>=1.0.1 Using cached Werkzeug-2.1.2-py3-none-any.whl (224 kB) Collecting google-auth<3,>=1.6.3 Using cached google_auth-2.6.6-py2.py3-none-any.whl (156 kB) Collecting tensorboard-plugin-wit>=1.6.0 Using cached tensorboard_plugin_wit-1.8.1-py3-none-any.whl (781 kB) Requirement already satisfied: setuptools>=41.0.0 in ./anaconda3/envs/mask_rcnn_tf2/lib/python3.7/site-packages (from tensorboard<3,>=2.3.0->tensorflow-gpu==2.3.0) (61.2.0) Collecting tensorboard-data-server<0.7.0,>=0.6.0 Using cached tensorboard_data_server-0.6.1-py3-none-manylinux2010_x86_64.whl (4.9 MB) Collecting requests<3,>=2.21.0 Using cached requests-2.27.1-py2.py3-none-any.whl (63 kB) Collecting google-auth-oauthlib<0.5,>=0.4.1 Using cached google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB) Collecting markdown>=2.6.8 Using cached Markdown-3.3.7-py3-none-any.whl (97 kB) Collecting rsa<5,>=3.1.4 Using cached rsa-4.8-py3-none-any.whl (39 kB) Collecting cachetools<6.0,>=2.0.0 Using cached cachetools-5.1.0-py3-none-any.whl (9.2 kB) Collecting pyasn1-modules>=0.2.1 Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB) Collecting requests-oauthlib>=0.7.0 Using cached requests_oauthlib-1.3.1-py2.py3-none-any.whl (23 kB) Collecting importlib-metadata>=4.4 Using cached importlib_metadata-4.11.3-py3-none-any.whl (18 kB) Collecting typing-extensions>=3.6.4 Using cached typing_extensions-4.2.0-py3-none-any.whl (24 kB) Collecting zipp>=0.5 Using cached zipp-3.8.0-py3-none-any.whl (5.4 kB) Collecting pyasn1<0.5.0,>=0.4.6 Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB) Collecting charset-normalizer~=2.0.0 Using cached charset_normalizer-2.0.12-py3-none-any.whl (39 kB) Collecting urllib3<1.27,>=1.21.1 Using cached urllib3-1.26.9-py2.py3-none-any.whl (138 kB) Collecting idna<4,>=2.5 Using cached idna-3.3-py3-none-any.whl (61 kB) Requirement already satisfied: certifi>=2017.4.17 in ./anaconda3/envs/mask_rcnn_tf2/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<3,>=2.3.0->tensorflow-gpu==2.3.0) (2021.10.8) Collecting oauthlib>=3.0.0 Using cached oauthlib-3.2.0-py3-none-any.whl (151 kB) Installing collected packages: urllib3, pyasn1, idna, charset-normalizer, zipp, typing-extensions, six, rsa, requests, pyasn1-modules, oauthlib, cachetools, requests-oauthlib, importlib-metadata, google-auth, werkzeug, tensorboard-plugin-wit, tensorboard-data-server, protobuf, numpy, markdown, grpcio, google-auth-oauthlib, absl-py, wrapt, termcolor, tensorflow-estimator, tensorboard, scipy, opt-einsum, keras-preprocessing, h5py, google-pasta, gast, astunparse, tensorflow-gpu Successfully installed absl-py-1.0.0 astunparse-1.6.3 cachetools-5.1.0 charset-normalizer-2.0.12 gast-0.3.3 google-auth-2.6.6 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.46.1 h5py-2.10.0 idna-3.3 importlib-metadata-4.11.3 keras-preprocessing-1.1.2 markdown-3.3.7 numpy-1.18.5 oauthlib-3.2.0 opt-einsum-3.3.0 protobuf-3.20.1 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-2.27.1 requests-oauthlib-1.3.1 rsa-4.8 scipy-1.4.1 six-1.16.0 tensorboard-2.9.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-estimator-2.3.0 tensorflow-gpu-2.3.0 termcolor-1.1.0 typing-extensions-4.2.0 urllib3-1.26.9 werkzeug-2.1.2 wrapt-1.14.1 zipp-3.8.0 (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$
查看gpu是否可用
print(tf.test.is_gpu_available())
(mask_rcnn_tf2) bim@bim-PowerEdge-R730:~/tensorflow_project$ python Python 3.7.0 (default, Oct 9 2018, 10:31:47) [GCC 7.3.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> >>> >>> >>> >>> import tensorflow as tf 2022-05-17 20:51:25.689564: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 >>> >>> >>> >>> >>> >>> tf.__version__ '2.3.0' >>> >>> >>> >>> >>> >>> >>> print(tf.test.is_gpu_available()) WARNING:tensorflow:From <stdin>:1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.config.list_physical_devices('GPU')` instead. 2022-05-17 20:52:43.931591: I tensorflow/core/platform/cpu_feature_guard.cc:142] 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. 2022-05-17 20:52:43.963271: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2399985000 Hz 2022-05-17 20:52:43.964706: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x562dc2276bb0 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2022-05-17 20:52:43.964727: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2022-05-17 20:52:43.967131: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1 2022-05-17 20:52:45.327224: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x562dc13c0950 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2022-05-17 20:52:45.327271: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla P100-PCIE-12GB, Compute Capability 6.0 2022-05-17 20:52:45.327280: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (1): Tesla P100-PCIE-12GB, Compute Capability 6.0 2022-05-17 20:52:45.328289: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-12GB computeCapability: 6.0 coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 11.91GiB deviceMemoryBand 511.41GiB/s 2022-05-17 20:52:45.329022: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 1 with properties: pciBusID: 0000:82:00.0 name: Tesla P100-PCIE-12GB computeCapability: 6.0 coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 11.91GiB deviceMemoryBand 511.41GiB/s 2022-05-17 20:52:45.329055: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 2022-05-17 20:52:45.329317: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcublas.so.10'; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64 2022-05-17 20:52:45.354650: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10 2022-05-17 20:52:45.362046: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10 2022-05-17 20:52:45.362163: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcusolver.so.10'; dlerror: libcusolver.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64 2022-05-17 20:52:45.362260: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcusparse.so.10'; dlerror: libcusparse.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64 2022-05-17 20:52:45.362309: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7 2022-05-17 20:52:45.362319: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1753] 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... 2022-05-17 20:52:45.362340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix: 2022-05-17 20:52:45.362350: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0 1 2022-05-17 20:52:45.362358: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N N 2022-05-17 20:52:45.362365: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 1: N N False >>> >>> >>>
显示gpu不可用，提示：
Could not load dynamic library 'libcublas.so.10'; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
Could not load dynamic library 'libcufft.so.10'; dlerror: libcufft.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
Could not load dynamic library 'libcurand.so.10'; dlerror: libcurand.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
Could not load dynamic library 'libcusolver.so.10'; dlerror: libcusolver.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
Could not load dynamic library 'libcusparse.so.10'; dlerror: libcusparse.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
Could not load dynamic library 'libcudnn.so.7'; dlerror: libcudnn.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.4/lib64:/usr/local/cuda-11.4/lib64::/usr/local/cuda/lib64
libcublas.so.10 libcufft.so.10 libcurand.so.10 libcusolver.so.10 libcusparse.so.10 libcudnn.so.7 文件都无法找到
使用root账户，进入
cd /usr/local/cuda-11.4/lib64
运行以下命令
ln -sf libcublas.so.11.5.2.43 libcublas.so.10
ln -sf libcufft.so.10.5.0.43 libcufft.so.10
ln -sf libcurand.so.10.2.5.43 libcurand.so.10
ln -sf libcusolver.so.11.2.0.43 libcusolver.so.10
ln -sf libcusparse.so.11.6.0.43 libcusparse.so.10
ln -sf libcudnn.so.8 libcudnn.so.7
然后再运行
(mask_rcnn_tf2) bim@bim-PowerEdge-R730:~$ python Python 3.7.0 (default, Oct 9 2018, 10:31:47) [GCC 7.3.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> >>> >>> >>> import tensorflow as tf 2022-05-17 21:56:44.976375: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 >>> >>> >>> >>> >>> >>> print(tf.test.is_gpu_available()) WARNING:tensorflow:From <stdin>:1: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.config.list_physical_devices('GPU')` instead. 2022-05-17 21:56:49.260798: I tensorflow/core/platform/cpu_feature_guard.cc:142] 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. 2022-05-17 21:56:49.291322: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2399975000 Hz 2022-05-17 21:56:49.292677: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x561584bd1c90 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2022-05-17 21:56:49.292698: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2022-05-17 21:56:49.294936: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1 2022-05-17 21:56:49.698527: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5615825c83f0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2022-05-17 21:56:49.698580: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla P100-PCIE-12GB, Compute Capability 6.0 2022-05-17 21:56:49.698596: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (1): Tesla P100-PCIE-12GB, Compute Capability 6.0 2022-05-17 21:56:49.700391: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties: pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-12GB computeCapability: 6.0 coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 11.91GiB deviceMemoryBand 511.41GiB/s 2022-05-17 21:56:49.701804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 1 with properties: pciBusID: 0000:82:00.0 name: Tesla P100-PCIE-12GB computeCapability: 6.0 coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 11.91GiB deviceMemoryBand 511.41GiB/s 2022-05-17 21:56:49.701858: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 2022-05-17 21:56:49.709602: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10 2022-05-17 21:56:49.712853: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10 2022-05-17 21:56:49.713111: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10 2022-05-17 21:56:49.713657: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10 2022-05-17 21:56:49.714620: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10 2022-05-17 21:56:49.714756: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7 2022-05-17 21:56:49.717598: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0, 1 2022-05-17 21:56:49.717635: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1 2022-05-17 21:56:50.512900: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix: 2022-05-17 21:56:50.512958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0 1 2022-05-17 21:56:50.512968: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N N 2022-05-17 21:56:50.512973: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 1: N N 2022-05-17 21:56:50.515585: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/device:GPU:0 with 11112 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-12GB, pci bus id: 0000:04:00.0, compute capability: 6.0) 2022-05-17 21:56:50.516767: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/device:GPU:1 with 11112 MB memory) -> physical GPU (device: 1, name: Tesla P100-PCIE-12GB, pci bus id: 0000:82:00.0, compute capability: 6.0) True >>> >>> >>>
显示两块显卡都在
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