我使用的是NVIDIA GeForce 940M，并已按照指示正确安装here来安装Tensorflow GPU：
# Add NVIDIA package repositories
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo apt-get update
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt-get update
# Install NVIDIA driver
sudo apt-get install --no-install-recommends nvidia-driver-418
# Reboot. Check that GPUs are visible using the command: nvidia-smi
# Install development and runtime libraries (~4GB)
sudo apt-get install --no-install-recommends \
cuda-10-0 \
libcudnn7=7.6.2.24-1+cuda10.0 \
libcudnn7-dev=7.6.2.24-1+cuda10.0
# Install TensorRT. Requires that libcudnn7 is installed above.
sudo apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
libnvinfer-dev=5.1.5-1+cuda10.0
这是nvidia-smi的输出：
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce 940M On | 00000000:01:00.0 Off | N/A |
| N/A 52C P0 N/A / N/A | 238MiB / 4046MiB | 6% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1027 G /usr/lib/xorg/Xorg 24MiB |
| 0 1184 G /usr/bin/gnome-shell 46MiB |
| 0 1388 G /usr/lib/xorg/Xorg 110MiB |
| 0 1555 G /usr/bin/gnome-shell 52MiB |
+-----------------------------------------------------------------------------+
和nvcc -v：
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
并且我同时使用conda和pip安装了tensorflow-gpu（两者均无效）。
的输出
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
是：
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 9340164754758349370
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 3967057350071782501
physical_device_desc: "device: XLA_CPU device"
]
如图所示，tensorflow无法识别GPU。我该怎么办？