基本都是本人實際過程中出現的情況。

採用的是Anaconda安裝方式（Anaconda是python科學計算的整合）

很多人不知道這個東西的意義：

介紹：Anaconda是一個用於科學計算的Python發行版，支援 Linux, Mac, Windows系統，提供了包管理與環境管理的功能，可以很方便地解決多版本python並存、切換以及各種第三方包安裝問題。Anaconda利用工具/命令conda來進行package和environment的管理，並且已經包含了Python和相關的配套工具。

簡單說，其有著強大而方便的包管理與環境管理的功能。

learn more:點選開啟連結

先說安裝過程：

裝Anaconda3(自帶python3.6)-->(隨手給你的python調一下環境變數)--->把（安裝路徑）...\Anaconda3\Scripts加入到你的path裡--->檢查conda

--->建立tensorflow空間，裝tensorflow --->進入python檢查tensorflow

--->如果tensorflow裝的是gpu版本的話，裝cuda 和 cudnn。（區別gpu和cpu兩個版本：gpu跑起來相當快，但需要你的顯示卡支援cuda）

注意啊，tensorflow1.4現在只支援CUDA8.0 +cudnn6.0  下載cuda9.0/cudnn5.1都是不能支援的

注意：

1. * TensorFlow 1.2.1 or earlier requires cuDNN 5.1. ('cudnn64_5.dll')  
2.   * TensorFlow 1.3 or later requires cuDNN 6. ('cudnn64_6.dll') 
    

用到的程式碼總結：

cmd--->

conda --version
conda info --envs
conda search --full-name python
conda create --name tensorflow python=3.6

(y)
activate tensorflow
python --version
(python -V)
pip install -ignore-installed --upgrade tensorflow-gpu
python
import tensorflow as tf

tf.__version__

tf.__path__
deactivate

檢查和幫助：

import ctypes  
import imp  
import sys  
  
  
def main():  
    try:  
        import tensorflow as tf  
        print("TensorFlow successfully installed.")  
        if tf.test.is_built_with_cuda():  
            print("The installed version of TensorFlow includes GPU support.")  
        else:  
            print("The installed version of TensorFlow does not include GPU support.")  
        sys.exit(0)  
    except ImportError:  
        print("ERROR: Failed to import the TensorFlow module.")  
  
    candidate_explanation = False  
  
    python_version = sys.version_info.major, sys.version_info.minor  
    print("\n- Python version is %d.%d." % python_version)  
    if not (python_version == (3, 5) or python_version == (3, 6)):  
        candidate_explanation = True  
        print("- The official distribution of TensorFlow for Windows requires "  
              "Python version 3.5 or 3.6.")  
  
    try:  
        _, pathname, _ = imp.find_module("tensorflow")  
        print("\n- TensorFlow is installed at: %s" % pathname)  
    except ImportError:  
        candidate_explanation = False  
        print(""" 
- No module named TensorFlow is installed in this Python environment. You may 
  install it using the command `pip install tensorflow`.""")  
  
    try:  
        msvcp140 = ctypes.WinDLL("msvcp140.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'msvcp140.dll'. TensorFlow requires that this DLL be 
  installed in a directory that is named in your %PATH% environment 
  variable. You may install this DLL by downloading Microsoft Visual 
  C++ 2015 Redistributable Update 3 from this URL: 
  https://www.microsoft.com/en-us/download/details.aspx?id=53587""")  
  
    try:  
        cudart64_80 = ctypes.WinDLL("cudart64_80.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'cudart64_80.dll'. The GPU version of TensorFlow 
  requires that this DLL be installed in a directory that is named in 
  your %PATH% environment variable. Download and install CUDA 8.0 from 
  this URL: https://developer.nvidia.com/cuda-toolkit""")  
  
    try:  
        nvcuda = ctypes.WinDLL("nvcuda.dll")  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'nvcuda.dll'. The GPU version of TensorFlow requires that 
  this DLL be installed in a directory that is named in your %PATH% 
  environment variable. Typically it is installed in 'C:\Windows\System32'. 
  If it is not present, ensure that you have a CUDA-capable GPU with the 
  correct driver installed.""")  
  
    cudnn5_found = False  
    try:  
        cudnn5 = ctypes.WinDLL("cudnn64_5.dll")  
        cudnn5_found = True  
    except OSError:  
        candidate_explanation = True  
        print(""" 
- Could not load 'cudnn64_5.dll'. The GPU version of TensorFlow 
  requires that this DLL be installed in a directory that is named in 
  your %PATH% environment variable. Note that installing cuDNN is a 
  separate step from installing CUDA, and it is often found in a 
  different directory from the CUDA DLLs. You may install the 
  necessary DLL by downloading cuDNN 5.1 from this URL: 
  https://developer.nvidia.com/cudnn""")  
  
    cudnn6_found = False  
    try:  
        cudnn = ctypes.WinDLL("cudnn64_6.dll")  
        cudnn6_found = True  
    except OSError:  
        candidate_explanation = True  
  
    if not cudnn5_found or not cudnn6_found:  
        print()  
        if not cudnn5_found and not cudnn6_found:  
            print("- Could not find cuDNN.")  
        elif not cudnn5_found:  
            print("- Could not find cuDNN 5.1.")  
        else:  
            print("- Could not find cuDNN 6.")  
            print(""" 
  The GPU version of TensorFlow requires that the correct cuDNN DLL be installed 
  in a directory that is named in your %PATH% environment variable. Note that 
  installing cuDNN is a separate step from installing CUDA, and it is often 
  found in a different directory from the CUDA DLLs. The correct version of 
  cuDNN depends on your version of TensorFlow: 
 
  * TensorFlow 1.2.1 or earlier requires cuDNN 5.1. ('cudnn64_5.dll') 
  * TensorFlow 1.3 or later requires cuDNN 6. ('cudnn64_6.dll') 
 
  You may install the necessary DLL by downloading cuDNN from this URL: 
  https://developer.nvidia.com/cudnn""")  
  
    if not candidate_explanation:  
        print(""" 
- All required DLLs appear to be present. Please open an issue on the 
  TensorFlow GitHub page: https://github.com/tensorflow/tensorflow/issues""")  
  
    sys.exit(-1)  
  
  
if __name__ == "__main__":  
    main()  

相關資料：

這三個看下來絕對能裝好了

tensorflow中文幫助文件+Linux安裝：（極客學院）

if 你安裝可能會出這樣的問題：