Question

我正在运行kaggle_otto_nn.py的{{1}} Keras，后端为theano。

在下面的第5行打印中，有些内容表示：

CNMeM启用初始大小：90.0％的内存，CuDNN不可用

我想知道，因为GPU设备是可检测到的，这个CuDNN not available是否重要？我是否正确地在GPU上运行我的程序？或者它实际上没有在GPU上运行。

cliu@cliu-ubuntu:keras-examples$ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32,lib.cnmem=0.9 python kaggle_otto_nn.py
Using Theano backend.
/usr/local/lib/python2.7/dist-packages/Theano-0.8.0rc1-py2.7.egg/theano/tensor/signal/downsample.py:6: UserWarning: downsample module has been moved to the theano.tensor.signal.pool module.
  "downsample module has been moved to the theano.tensor.signal.pool module.")
Using gpu device 0: Quadro K610M (CNMeM is enabled with initial size: 90.0% of memory, CuDNN not available)
Loading data...
9 classes
93 dims
Building model...
Training model...
Train on 52596 samples, validate on 9282 samples
Epoch 1/20
52596/52596 [==============================] - 6s - loss: 0.9420 - val_loss: 0.6269
Epoch 2/20
52596/52596 [==============================] - 6s - loss: 0.6955 - val_loss: 0.5817
...
Epoch 20/20
52596/52596 [==============================] - 6s - loss: 0.4866 - val_loss: 0.4819
Generating submission...
144368/144368 [==============================] - 1s     
Wrote submission to file keras-otto.csv.

Answer 1

cuDNN是NVidia的一个库，可以提高GPU上神经网络的性能。所以你的程序仍然可以在GPU上运行，但比安装了cuDNN时要慢得多。

Keras：CuDNN不可用？

1 个答案: