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gpu [2018/05/30 09:54]
vodrazka [Set-up CUDA and CUDNN] 		gpu [2018/06/12 12:08]
ufal [TensorFlow Environment]
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   fi   fi
  
-  * When not using Theano, just Tensorflow this can be simplified to ''export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/9.0/cudnn/7.0/lib64:/opt/cuda/8.0/lib64''.+  * When not using Theano, just Tensorflow this can be simplified to ''export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/9.0/lib64:/opt/cuda/9.0/cudnn/7.0/lib64''.
  
-  * There is no default and you always need to set ''LD_LIBRARY_PATH'' to suit explicitly.+  * There is no default and you always need to set ''LD_LIBRARY_PATH'' explicitly.
  
   * Note that ''cudnn'' library is compiled for specific version of ''cuda''. If you need specific version of ''cudnn'', you can look in ''/opt/cuda/$CUDA_version/cudnn/'' whether it is available for given ''$CUDA_version''.   * Note that ''cudnn'' library is compiled for specific version of ''cuda''. If you need specific version of ''cudnn'', you can look in ''/opt/cuda/$CUDA_version/cudnn/'' whether it is available for given ''$CUDA_version''.
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 And then you can activate your environment: And then you can activate your environment:
  
-  source activate tf1 +  source activate tf18 
-  source activate tf1cpu+  source activate tf18cpu
  
-This environment have TensorFlow 1.0 and all necessary requirements for NeuralMonkey.+This environment have TensorFlow 1.8.0 and all necessary requirements for NeuralMonkey.
  
 ==== Pytorch Environment ==== ==== Pytorch Environment ====

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