环境搭配 TensorFlow GPU

 

 

 

 

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显示 python，TensorFlow，CUDA，cuDNN， GPU 等版本型号

 

import os, sys
print(sys.executable) #
print(sys.version) ## python
print(sys.version_info)

import tensorflow as tf
print(tf. __version__) ## tensorflow

 

进入anaconda环境

1. 查看torch版本

python -c \”import torch; print(torch.__version__)\”

2. 查看cuda版本

python -c \”import torch; print(torch.version.cuda)\”

 

import torch
print(torch.version.cuda)

 

import torch
print(torch.backends.cudnn.version())

查看cudnn_version.h文件

include\cudnn.h
cudnn的include里有cudnn_version.h的情况：

locate cudnn_version.h 

 cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2
 
cudnn版本在8.0以前

locate cudnn.h 

cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

    1

cudnn版本在8.0以前，这个命令会输出。但是8.0版本后就没有输出，需要用下面的命令。
cudnn版本在8.0以后

在8.0版本之后用上面的命令就没有输出了。因为这个头文件内容变了。用下面的命令可以看到

cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2
————————————————
版权声明：本文为CSDN博主「巴啦啦魔仙变！！」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/qq_41726670/article/details/124764498

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Keras is included in TensorFlow 2.0 above. So

• remove import keras and
• replace from keras.module.module import class statement to --> from tensorflow.keras.module.module import class
• Maybe your GPU memory is filled. So use allow growth = True in GPU option. This is deprecated now. But use this below code snippet after imports may solve your problem.

import tensorflow as tf
from tensorflow.compat.v1.keras.backend import set_session
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True  # dynamically grow the memory used on the GPU
config.log_device_placement = True  # to log device placement (on which device the operation ran)
sess = tf.compat.v1.Session(config=config)
set_session(sess)

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环境搭配

python: 3.6.4.

Tensorflow Version: 1.12.0.

Keras Version: 2.2.4.

CUDA: V10.0.

cuDNN: V7.4.1.5.

NVIDIA GeForce GTX 1080.

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环境搭配