今天发现一个怪现象，在训练keras时，发现不使用GPU进行计算，而是采用CPU进行计算，导致计算速度很慢。
用如下代码可检测tensorflow的能使用设备情况：
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices()) 可用设备为：
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}] 原来只有一个CPU设备可用了。于是检查下tensorflow的版本情况：
pip3 list各应用版本为：
tensorflow 1.10.1
tensorflow-gpu 1.9.0原来我升级了tensorflow版本，忘记了升级tensorflow-gpu版本，现在两个版本有代差，而tensorflow默认选择版本高的CPU版本来计算了。
那就升级tensorflow-gpu吧：
pip3 install --index-url http://pypi.douban.com/simple --trusted-host pypi.douban.com --upgrade tensorflow-gpu再次检测可用设备情况，结果如下：
2018-09-04 10:51:22.996654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties:
name: GeForce GTX 1060 5GB major: 6 minor: 1 memoryClockRate(GHz): 1.7085
pciBusID: 0000:01:00.0
totalMemory: 4.94GiB freeMemory: 4.23GiB
2018-09-04 10:51:22.996666: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-09-04 10:51:23.189923: I tensorflow/core/common_runtime/gpu/gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-09-04 10:51:23.189953: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0
2018-09-04 10:51:23.189959: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] 0: N
2018-09-04 10:51:23.190105: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1097] Created TensorFlow device (/device:GPU:0 with 3969 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 5GB, pci bus id: 0000:01:00.0, compute capability: 6.1)
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 15761951721866580392
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 4161994752
locality {
bus_id: 1
links {
}
}
incarnation: 16066826866269340415
physical_device_desc: "device: 0, name: GeForce GTX 1060 5GB, pci bus id: 0000:01:00.0, compute capability: 6.1"
]
