使用anaconda安裝tensorflow （windows10環境）

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            <p>已有環境：python3.7.1<br></p><p>anaconda隔離管理多個環境，互不影響。這里，在anaconda中安裝最新的python3.6.5 版本。</p><p>linux環境下使用anaconda安裝tensorflow步驟見：<a href="https://blog.csdn.net/ebzxw/article/details/80693152" rel="nofollow" target="_blank">https://blog.csdn.net/ebzxw/article/details/80693152</a></p><p><strong>一. 安裝anaconda</strong></p><p>1. 下載地址：&nbsp;<a href="https://www.anaconda.com/download/#windows" rel="nofollow" target="_blank">https://www.anaconda.com/download/#windows</a></p><p><img src="https://img-blog.csdn.net/20180615101323644?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p>2.&nbsp; 執行下載文件&nbsp;&nbsp;Anaconda3-5.2.0-<a href="https://www.baidu.com/s?wd=Windows&amp;tn=24004469_oem_dg&amp;rsv_dl=gh_pl_sl_csd" target="_blank">Windows</a>-x86_64.exe， 默認配置安裝。</p><p><span style="background-color:rgb(255,255,255);">3.&nbsp; 檢查安裝結果。進入到windows中的命令模式：</span></p><p style="background-color:rgb(255,255,255);">（1）檢測anaconda環境是否安裝成功：conda --version</p><p style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615193442552?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p style="background-color:rgb(255,255,255);">（2）檢測目前安裝了哪些環境變量：conda info --envs</p><p style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615193459890?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p style="background-color:rgb(255,255,255);">（3） 查看當前有哪些可以使用的tensorflow版本：<strong>conda search&nbsp; --full -name tensorflow</strong></p><p><img src="https://img-blog.csdn.net/20180615193553707?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""></p><p><span style="background-color:rgb(255,255,255);">（4） 查看tensorflow包信息及依賴關系：<strong>conda&nbsp; info&nbsp; tensorflow</strong></span><br></p><p><span style="background-color:rgb(255,255,255);"><strong><img src="https://img-blog.csdn.net/2018061521501133?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></strong></span></p><p><span style="font-weight:bold;">二. 在anaconda中安裝tensorflow</span></p><p><span style="background-color:rgb(255,255,255);">1.&nbsp; 進入windows命令模式，創建tfenv環境，安裝python3.6：&nbsp;</span><span style="background-color:rgb(255,255,255);"><strong>conda create --name tfenv python=3.6</strong></span></p><div><img src="https://img-blog.csdn.net/20180615220036678?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></div><p><span style="background-color:rgb(255,255,255);">2 .&nbsp;<span style="background-color:rgb(255,255,255);">激活tensflow的tfenv環境： activate&nbsp; tfenv</span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615220551804?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">&nbsp; &nbsp; 檢測tfenv的環境添加到了Anaconda里面：conda info --envs</span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/2018061522080997?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">看到，已經創建成功。</span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">檢測當前環境中的python的版本：python --version</span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615221846949?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">退出tfenv的環境：deactivate</span><br></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615222102462?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">3.&nbsp; 在tfenv環境<a href="https://www.baidu.com/s?wd=%E4%B8%AD%E6%AD%A3%E5%BC%8F&amp;tn=24004469_oem_dg&amp;rsv_dl=gh_pl_sl_csd" target="_blank">中正式</a>安裝tensorflow包</span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">1）<span style="background-color:rgb(255,255,255);">激活tensflow的tfenv環境： activate&nbsp; tfenv</span></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">2）pip install --upgrade --ignore-installed tensorflow</span></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615222656314?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615224852188?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">3) 驗證功能正常：python 進入代碼環境</span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615225105865?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></span></p><pre onclick="hljs.copyCode(event)"><code class="language-python hljs"><ol class="hljs-ln"><li><div class="hljs-ln-numbers"><div class="hljs-ln-line hljs-ln-n" data-line-number="1"></div></div><div class="hljs-ln-code"><div class="hljs-ln-line"><span class="hljs-keyword">import</span> tensorflow <span class="hljs-keyword">as</span> tf</div></div></li><li><div class="hljs-ln-numbers"><div class="hljs-ln-line hljs-ln-n" data-line-number="2"></div></div><div class="hljs-ln-code"><div class="hljs-ln-line">hello = tf.constant(<span class="hljs-string">'hello,tf'</span>)</div></div></li><li><div class="hljs-ln-numbers"><div class="hljs-ln-line hljs-ln-n" data-line-number="3"></div></div><div class="hljs-ln-code"><div class="hljs-ln-line">sess = tf.Session()</div></div></li><li><div class="hljs-ln-numbers"><div class="hljs-ln-line hljs-ln-n" data-line-number="4"></div></div><div class="hljs-ln-code"><div class="hljs-ln-line">print(sess.run(hello))</div></div></li></ol></code><div class="hljs-button" data-title="復制"></div></pre><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><img src="https://img-blog.csdn.net/20180615225701383?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);">可以看到， 該環境下 tensorflow 工作正常。</span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="font-weight:700;">三.&nbsp; 安裝可能的異常</span><br></span></span></span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"></span></span></span></span></p><p style="background-color:rgb(255,255,255);"><span><span style="color:rgb(255,0,0);">溫馨提示：如果你的conda和tensorflow環境都是安裝成功的，但是一用測試代碼進行跑的時候就出問題了，那么注意，這個原因你由於你在安裝tensorflow的時候，是直接在cmd下，而不是在你用conda激活的一個環境，所以導致，tensorflow並沒有直接嵌入到conda環境，所以，就導致無法導入模塊的一個錯誤；</span></span></p><p style="background-color:rgb(255,255,255);"><span><span style="color:rgb(255,0,0);">解決方法：（1）只需要在activate&nbsp; tfenv</span></span></p><p style="background-color:rgb(255,255,255);"><span><span style="color:rgb(255,0,0);">（2）然后再使用&nbsp;<span style="background-color:rgb(255,255,255);">pip install --upgrade --ignore-installed tensorflow&nbsp;</span>命令安裝就可以了</span></span></p><p><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="background-color:rgb(255,255,255);"><span style="font-weight:700;background-color:rgb(255,255,255);">四.&nbsp; 將tensorflow嵌入到IDE中</span></span></span></span></span></p><p>這里的關鍵是配置后，IDE使用的python環境包含tensorflow就可以。</p><p>1. windows操作命令下設置默認python環境</p><p>可通過環境變量的順序來設置。（這里是之前就有的python3.6.1環境和在anaconda中裝的python3.6.5）</p><p><img src="https://img-blog.csdn.net/20180616100818536?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p>“系統屬性”頁面，點擊“環境變量”&nbsp; ，選中PATH，點“編輯”</p><p><img src="https://img-blog.csdn.net/20180616100952319?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p>選中希望優先執行的python版本路徑，“上移”到頂。 這里是把anaconda安裝后默認在最上面，改為原來的3.6.1版本了。</p><p><img src="https://img-blog.csdn.net/20180616101110912?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p><strong>結果驗證與環境切換：</strong></p><p><img src="https://img-blog.csdn.net/20180616101310565?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p><img src="https://img-blog.csdn.net/20180616101403452?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p>2.&nbsp; VSCODE里設置默認python環境 （演示設置為原來python3.6.1）<br></p><p>打開編輯器。 文件 - 首選項 - 設置</p><p>找到“用戶工作區設置”，更改 python.pythonPath 配置變量即可。</p><p></p><div style="color:rgb(212,212,212);background-color:rgb(30,30,30);font-family:Consolas, 'Courier New', monospace;font-size:14px;line-height:19px;white-space:pre;"><div>    <span style="color:#9cdcfe;">"python.pythonPath"</span>: <span style="color:#ce9178;">"C:</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">Users</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">user</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">AppData</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">Local</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">Programs</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">python</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">Python36</span><span style="color:#d7ba7d;">\\</span><span style="color:#ce9178;">python.exe"</span></div><div><span style="color:#608b4e;">//    "python.pythonPath": "C:\\Users\\user\\Anaconda3\\python.exe"    </span></div><div></div></div>界面如下圖：<p><img src="https://img-blog.csdn.net/20180616101653664?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Vienh3/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70" alt=""><br></p><p>重啟vscode即可。</p>            </div>
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posted @ 2019-01-27 13:34  蘭翔  閱讀( 4563)  評論( 2)  編輯  收藏