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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
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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=======================================================
Keras is included in TensorFlow 2.0 above. So
- remove
import kerasand - replace
from keras.module.module import classstatement 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)=======================================================
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