Tensorflow安装GPU版本的一些问题处理

好的习惯还是在虚拟环境中安装，先使用conda创建一个
conda create -n tfgpu python=3.7

然后进入环境
activate tfgpu

安装带GPU的Tensorflow，当然也可以指定版本来安装，指定镜像站点要快
pip install -i http://pypi.douban.com/simple/ --trusted-host pypi.douban.com --trusted-host pypi.douban.com tensorflow_gpu

然后就来测试下是否安装成功

import tensorflow as tf
# 查看gpu和cpu的数量
gpus = tf.config.experimental.list_physical_devices(device_type='GPU')
cpus = tf.config.experimental.list_physical_devices(device_type='CPU')
print(gpus, cpus)

 不出所料的话，一般都是如下的错误信息：

2022-10-21 12:39:38.439442: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2022-10-21 12:39:38.439689: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1934] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...

cudnn64_8.dll没有找到，我们可以来到这个地方复制：

C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\bin

当然这里看自己安装的版本不一样有点区别，我这里是v10.2版本，你们根据自己的情况去找。

将cudnn64_8.dll文件拷贝到 C:\Windows\System

[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')] [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')] 

 如果还不可以的话，那就重新安装cudnn
conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0

from tensorflow.python.client import device_lib
# 列出全部的本地机器设备
local_device_protos = device_lib.list_local_devices()
print(local_device_protos)
'''
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 1203727834508357835
xla_global_id: -1
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 1389330023
locality {
  bus_id: 1
  links {
  }
}
incarnation: 4726776883789372381
physical_device_desc: "device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1"
xla_global_id: 416903419
]
'''

# 只打印GPU设备
[x for x in local_device_protos if x.device_type == 'GPU']
'''
[name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 1389330023
locality {
  bus_id: 1
  links {
  }
}
incarnation: 4726776883789372381
physical_device_desc: "device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1"
xla_global_id: 416903419
]
'''