Windows系統下，深度學習安裝指令

1，升級pip

（1）在prompt中，以管理員權限運行
pip install --upgrade pip
（2）在cmd中，以管理員運行
python -m pip install --upgrade pip

錯誤：
Script file ‘D:\Users\Administrator\Anaconda3\Scripts\pip-script.py’ is not present.

解決方法：easy_install pip

2，anaconda中添加channel

(1)清華鏡像

(D:\Users\Administrator\Anaconda3) C:\Users\Administrator>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

(D:\Users\Administrator\Anaconda3) C:\Users\Administrator>conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/

(D:\Users\Administrator\Anaconda3) C:\Users\Administrator>conda config --set show_channel_urls yes

（2）中科大鏡像

(D:\Users\Administrator\Anaconda3) C:\Users\Administrator>conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/

(D:\Users\Administrator\Anaconda3) C:\Users\Administrator>conda config --set show_channel_urls yes

3，遇到問題ERROR: tensorboard 1.14.0 has requirement setuptools>=41.0.0, but you’ll have setuptools 36.4.0 which is incompatible.：

在安裝：

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==1.14

解決辦法：

pip install tensorboard

註釋：最後出了問題：
import tensorboard.lazy as _lazy
AttributeError: module ‘tensorboard’ has no attribute ‘lazy’
解決辦法：

pip uninstall tensorboard
pip uninstall tensorflow-gpu

重新裝：

pip install -i https://pypi.tuna.tsinghua.edu.cn/simple tensorflow-gpu==1.14

現在測試成功：

>>> import tensorflow
>>> from tensorflow.python.client import device_lib
>>> print(device_lib.list_local_devices())
2019-07-21 09:59:39.657281: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-07-21 09:59:39.661258: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library nvcuda.dll
2019-07-21 09:59:40.617377: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.62
pciBusID: 0000:01:00.0
2019-07-21 09:59:40.621751: I tensorflow/stream_executor/platform/default/dlopen_checker_stub.cc:25] GPU libraries are statically linked, skip dlopen check.
2019-07-21 09:59:40.629822: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-07-21 09:59:41.207582: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-07-21 09:59:41.210105: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0
2019-07-21 09:59:41.211590: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N
2019-07-21 09:59:41.220506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/device:GPU:0 with 3001 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 17227910178020249398
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 3146829004
locality {
  bus_id: 1
  links {
  }
}
incarnation: 13565572337421704331
physical_device_desc: "device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1"
]
>>>

上述結果：環境：win10+cuda10.0+cudnn7.6.1+tensorflow1.14

4 ,遇到：ModuleNotFoundError: No module named ‘skimage’

解決方法：

pip install scikit-image