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pythontensorflowcudakerasgpu

Keras does not use GPU - how to troubleshoot?

I'm trying to train a Keras model on the GPU, with Tensorflow as backend.

I have set everything up according to https://www.tensorflow.org/install/install_windows. This is my setup:

  • I'm working in a Jupyter notebook in a virtualenv environment.
  • The current virtualenv environment has tensorflow-gpu installed.
  • I have CUDA 9.1 and cudaDNN for CUDA 9.1 installed.
  • cuDNN64_7.dll is at a location which is accessible via the PATH variable.
  • I have an NVIDIA GeForce GTX 780 on my computer with the latest drivers.

However, Tensorflow does not see any usable GPU:

from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())

[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 5275203639471190827
]

Keras neither:

from keras import backend as K
K.tensorflow_backend._get_available_gpus()

[]

How can I debug this? How can I find out where the problem is?

Solution

  • Check
    nvcc -V
    and

    nvidia-smi

    and see if it shows our gpu or not.

    Assuming your cuda cudnn and everything checks out, you may just need to
    1. Uninstall keras
    2. Uninstall tensorflow
    3. uninstall tensorflow-gpu
    4. Install only tensorflow-gpu pip install tensorflow-gpu==1.5.0
    5. Install Keras now.

    I followed these steps, and keras now uses gpu.

    Hope it helps to some extent.