[英]Keras: CuDNN not available?
I am running the example kaggle_otto_nn.py
of Keras
with backend of theano
.我运行的例子
kaggle_otto_nn.py
的Keras
与后端theano
。
In the following print out, line 5, something says:在下面的打印输出中,第 5 行说:
CNMeM is enabled with initial size: 90.0% of memory, CuDNN not available
CNMeM 启用初始大小:90.0% 内存,CuDNN 不可用
I am wondering, does this CuDNN not available
matter since the GPU device is detectable?我想知道,由于可检测到 GPU 设备,因此此
CuDNN not available
重要? Am I running my program on GPU correctly?我是否在 GPU 上正确运行我的程序? Or it's actually not running on GPU.
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.
cuDNN is a library by NVidia which increases the performance of neural networks on GPU. cuDNN 是 NVidia 的一个库,它提高了 GPU 上神经网络的性能。 So your program still runs on GPU but much slower than it could have been if you had installed cuDNN.
所以你的程序仍然在 GPU 上运行,但比安装 cuDNN 时慢得多。
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