DDR爱好者之家 Design By 杰米

问题描述:我通过控制台使用tensorflow-gpu没问题,但是通过pycharm使用却不可以,如下所示:

通过控制台:

answer@answer-desktop:/$ python
Python 3.7.0 (default, Jun 28 2018, 13:15:42) 
[GCC 7.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
> import tensorflow as tf
2020-02-04 21:37:12.964610: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer.so.6'; dlerror: libnvinfer.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-10.1/lib64:/usr/local/cuda-10.1/lib64
2020-02-04 21:37:12.964749: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libnvinfer_plugin.so.6'; dlerror: libnvinfer_plugin.so.6: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-10.1/lib64:/usr/local/cuda-10.1/lib64
2020-02-04 21:37:12.964777: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:30] Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
> 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.
2020-02-04 21:37:37.267421: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 1795795000 Hz
2020-02-04 21:37:37.268461: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55913b67a840 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-02-04 21:37:37.268516: I tensorflow/compiler/xla/service/service.cc:176]  StreamExecutor device (0): Host, Default Version
2020-02-04 21:37:37.272139: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-02-04 21:37:37.481038: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.481712: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55913b6eb960 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-02-04 21:37:37.481755: I tensorflow/compiler/xla/service/service.cc:176]  StreamExecutor device (0): GeForce GTX 1060 3GB, Compute Capability 6.1
2020-02-04 21:37:37.482022: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.482528: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: 
pciBusID: 0000:03:00.0 name: GeForce GTX 1060 3GB computeCapability: 6.1
coreClock: 1.7085GHz coreCount: 9 deviceMemorySize: 5.93GiB deviceMemoryBandwidth: 178.99GiB/s
2020-02-04 21:37:37.482953: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-02-04 21:37:37.485492: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2020-02-04 21:37:37.487486: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-02-04 21:37:37.487927: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-02-04 21:37:37.490469: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-02-04 21:37:37.491950: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2020-02-04 21:37:37.499031: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-02-04 21:37:37.499301: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.500387: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.500847: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2020-02-04 21:37:37.500941: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2020-02-04 21:37:37.502172: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-02-04 21:37:37.502212: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102]   0 
2020-02-04 21:37:37.502229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0:  N 
2020-02-04 21:37:37.502436: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.503003: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-04 21:37:37.503593: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/device:GPU:0 with 2934 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 3GB, pci bus id: 0000:03:00.0, compute capability: 6.1)
True
>

返回的True,说明可以

通过pycharm却不行,如下图,返回False

解决Ubuntu18中的pycharm不能调用tensorflow-gpu的问题

解决办法:

1.修改~/.bashrc

将pycahrm的路径加到环境中,示例如下:

alias pycharm="bash /home/answer/文档/pycharm-professional-2019.3.2/pycharm-2019.3.2/bin/pycharm.sh"

刷新生效:

source ~/.bashrc

2.修改pycharm中的环境变量

选择pycharm 菜单栏Run ——> Run-Edit Configurations ——> Environment variables——> 将cuda的路径加进去 例如:LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64

解决Ubuntu18中的pycharm不能调用tensorflow-gpu的问题

在运行就可以了

DDR爱好者之家 Design By 杰米
广告合作:本站广告合作请联系QQ:858582 申请时备注:广告合作(否则不回)
免责声明:本站资源来自互联网收集,仅供用于学习和交流,请遵循相关法律法规,本站一切资源不代表本站立场,如有侵权、后门、不妥请联系本站删除!
DDR爱好者之家 Design By 杰米

《魔兽世界》大逃杀!60人新游玩模式《强袭风暴》3月21日上线

暴雪近日发布了《魔兽世界》10.2.6 更新内容,新游玩模式《强袭风暴》即将于3月21 日在亚服上线,届时玩家将前往阿拉希高地展开一场 60 人大逃杀对战。

艾泽拉斯的冒险者已经征服了艾泽拉斯的大地及遥远的彼岸。他们在对抗世界上最致命的敌人时展现出过人的手腕,并且成功阻止终结宇宙等级的威胁。当他们在为即将于《魔兽世界》资料片《地心之战》中来袭的萨拉塔斯势力做战斗准备时,他们还需要在熟悉的阿拉希高地面对一个全新的敌人──那就是彼此。在《巨龙崛起》10.2.6 更新的《强袭风暴》中,玩家将会进入一个全新的海盗主题大逃杀式限时活动,其中包含极高的风险和史诗级的奖励。

《强袭风暴》不是普通的战场,作为一个独立于主游戏之外的活动,玩家可以用大逃杀的风格来体验《魔兽世界》,不分职业、不分装备(除了你在赛局中捡到的),光是技巧和战略的强弱之分就能决定出谁才是能坚持到最后的赢家。本次活动将会开放单人和双人模式,玩家在加入海盗主题的预赛大厅区域前,可以从强袭风暴角色画面新增好友。游玩游戏将可以累计名望轨迹,《巨龙崛起》和《魔兽世界:巫妖王之怒 经典版》的玩家都可以获得奖励。