cuDNN Error: CUDNN_STATUS_NOT_INITIALIZED src/cytonLib/Global.cu 67

[ZhuXingJune]

The problem when I train a model after compiling will be like this:

A.L.E: Arcade Learning Environment (version 0.6.0)
[Powered by Stella]
Use -help for help screen.
Warning: couldn't load settings file: ./ale.cfg
version 1.0
mode: train
batchSize: 32
dueling: 1
env: roms/breakout.bin
gamma: 0.99
inputFrames: 4
learningRate: 0.0000625
learnStart: 50000
loadModel:
maxEpisodeSteps: 18000
maxSteps: 100000000
optimizer: RMSprop
priorityAlpha: 0.6
priorityBeta: 0.4
progPeriod: 10000
replayMemory: 1000000
saveModel: model/model
savePeriod: 1000000
showScreen: 0
targetQ: 30000
testEGreedy: 0.001
testEpisodes: 100
testMaxEpisodeSteps: 18000
testPeriod: 5000000
updatePeriod: 4
networkSize: 32:64:64:512
eGreedy: 1.0:0.01:5000000
cuDNN Error: CUDNN_STATUS_NOT_INITIALIZED src/cytonLib/Global.cu 67
cytonRl: src/cytonLib/basicHeads.cu:52: cudnnStatus_t cytonLib::checkError_(cudnnStatus_t, const char*, int): Assertion `false' failed.
Aborted (core dumped)

And my Driver Version is: NVIDIA-SMI 396.26, cuda=9.2.88, cudnn=7.1.4
What's wrong with it?

Well, I will really appreciate your answer. @arthurxlw

[arthurxlw]

Hi June, It looks like an environment setting problem. Maybe first check whether the versions of CUDA and CUDNN match. Then check whether the memory of GPU is big enough.

[ZhuXingJune]

Thank for your answer! But I have used "cuda=8.0 , cudnn=6.0" and "cuda=9.2.88, cudnn=7.1.4", and there is the same bug for both of them.
In addition, I find that in line 66 of Global.cu, "cudnnCreate(&cudnnHandle)" return 1, which is "CUDNN_STATUS_NOT_INITIALIZED". Is it also the problem of environment setting?
@arthurxlw

[ZhuXingJune]

Oh, I think I made a stupid mistake, and the problem is my wrong operation on my server.