問題1: 程式只要 import keras 就會掛掉!!
解法==> conda update keras
conda update tensorflow
問題2: UDA driver version is insufficient for CUDA runtime version
\Anaconda3\lib\site-packages\tensorflow\python\client\session.py in __init__(self, target, graph, config) 674 try: 675 # pylint: disable=protected-access --> 676 self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts) 677 # pylint: enable=protected-access 678 finally: InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
解法==> 就是要讓 cuda driver和 cudnn 匹配. 若是在Anaconda , 因為Anaconda 會去做軟體版本匹配的整合, 所以最簡單的作法就是直接執行 conda update --all
若tensorflow 要使用底層GPU架構,要安裝對應的軟體.
Keras --> Tensorflow --> cuDNN --> CUDA Driver --> GPU graphic card
cuDNN [1]: The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK.
