ZIP配置PyTorch环境在Anaconda中是一个相对简单的过程，因为Anaconda提供了包管理和环境隔离的功能，使得安装和配置 14.25KB

2401_87232220

资源文件列表:

anaconda配置pytorch环境.zip 大约有1个文件
  1. anaconda配置pytorch环境.docx 16.62KB

资源介绍:

anaconda配置pytorch环境配置PyTorch环境在Anaconda中是一个相对简单的过程，因为Anaconda提供了包管理和环境隔离的功能，使得安装和配置不同版本的库变得非常容易。下面是一个步骤指南，帮助你在Anaconda中配置PyTorch环境： 1. 安装Anaconda 如果你还没有安装Anaconda，你可以从Anaconda的官方网站下载并安装它。安装时，请按照安装向导的指示操作。 2. 创建新的环境 打开Anaconda Prompt（Windows）或终端（Mac/Linux），然后使用conda create命令来创建一个新的环境。你可以根据需要命名环境，并指定Python版本。例如，要创建一个名为pytorch_env的环境，并安装Python 3.8，你可以使用以下命令： bash conda create --name pytorch_env python=3.8 3. 激活新环境 创建环境后，你需要激活它才能在其中安装PyTorch。使用以下命令激活环境： bash conda activate pytorch_env 4. 安装PyTor
<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89738954/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89738954/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">配置<span class="_ _0"> </span><span class="ff2">PyTorch<span class="_"> </span></span>环境在<span class="_ _0"> </span><span class="ff2">Anaconda<span class="_"> </span></span>中是一个相对简单的过程，因为<span class="_ _0"> </span><span class="ff2">Anaconda<span class="_"> </span></span>提供了包</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">管理和环境隔离的功能，使得安装和配置不同版本的库变得非常容易。下面是一个步</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">骤指南，帮助你在<span class="_ _0"> </span><span class="ff2">Anaconda<span class="_"> </span></span>中配置<span class="_ _0"> </span><span class="ff2">PyTorch<span class="_"> </span></span>环境：</div><div class="t m0 x1 h3 y4 ff3 fs1 fc0 sc0 ls0 ws0">1. <span class="ff4 sc1">安装<span class="_ _1"> </span></span>Anaconda</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">如果你还没有安装<span class="_ _0"> </span><span class="ff2">Anaconda</span>，你可以从<span class="_ _0"> </span><span class="ff2 fc1">Anaconda<span class="_"> </span><span class="ff1">的官方网站</span></span>下载并安装它。安装</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">时，请按照安装向导的指示操作。</div><div class="t m0 x1 h3 y7 ff3 fs1 fc0 sc0 ls0 ws0">2. <span class="ff4 sc1">创建新的环<span class="_ _2"></span>境</span></div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">打开<span class="_ _0"> </span><span class="ff2">Anaconda Prompt</span>（<span class="ff2">Windows</span>）或终端（<span class="ff2">Mac/Linux</span>），然后使用<span class="_ _0"> </span><span class="ff5 fs2">conda create</span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">命令来创建一个新的环境。你可以根据需要命名环境，并指定<span class="_ _0"> </span><span class="ff2">Python<span class="_"> </span></span>版本。例如，</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">要创建一个名为<span class="_ _0"> </span><span class="ff5 fs2">pytorch_env<span class="_ _3"> </span></span>的环境，并安装<span class="_ _0"> </span><span class="ff2">Python 3.8</span>，你可以使用以下命令：</div><div class="t m0 x1 h4 yb ff6 fs3 fc2 sc0 ls0 ws0">bash<span class="_ _1"> </span><span class="ff1 fs4 fc0">复制代码</span></div><div class="c x2 yc w2 h5"><div class="t m0 x3 h2 yd ff7 fs0 fc3 sc0 ls0 ws0">conda </div><div class="t m0 x3 h2 ye ff7 fs0 fc3 sc0 ls0 ws0">create --</div><div class="t m0 x3 h2 yf ff7 fs0 fc3 sc0 ls0 ws0">name </div><div class="t m0 x3 h2 y10 ff7 fs0 fc3 sc0 ls0 ws0">pytorch_env<span class="fc4 sc0"> </span></div><div class="t m0 x3 h2 y11 ff7 fs0 fc3 sc0 ls0 ws0">python=3.8</div></div><div class="t m0 x1 h3 y12 ff3 fs1 fc0 sc0 ls0 ws0">3. <span class="ff4 sc1">激活新环境</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">创建环境后，你需要激活它才能在其中安装<span class="_ _0"> </span><span class="ff2">PyTorch</span>。使用以下命令激活环境：</div><div class="t m0 x1 h4 y14 ff6 fs3 fc2 sc0 ls0 ws0">bash<span class="_ _1"> </span><span class="ff1 fs4 fc0">复制代码</span></div><div class="c x2 y15 w2 h6"><div class="t m0 x3 h2 y16 ff7 fs0 fc3 sc0 ls0 ws0">conda </div><div class="t m0 x3 h2 y10 ff7 fs0 fc3 sc0 ls0 ws0">activate </div><div class="t m0 x3 h2 y11 ff7 fs0 fc3 sc0 ls0 ws0">pytorch_env</div></div><div class="t m0 x1 h3 y17 ff3 fs1 fc0 sc0 ls0 ws0">4. <span class="ff4 sc1">安装<span class="_ _1"> </span></span>PyTorch</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">安<span class="_ _2"></span>装<span class="_ _4"> </span><span class="ff2">PyTorch<span class="_ _4"> </span></span>之<span class="_ _2"></span>前<span class="_ _5"></span>，<span class="_ _2"></span>你<span class="_ _2"></span>需<span class="_ _2"></span>要<span class="_ _2"></span>确<span class="_ _2"></span>定<span class="_ _5"></span>你<span class="_ _2"></span>的<span class="_ _4"> </span><span class="ff2">CUDA<span class="_ _4"> </span></span>版<span class="_ _2"></span>本<span class="_ _5"></span>（<span class="_ _2"></span>如<span class="_ _2"></span>果<span class="_ _2"></span>你<span class="_ _2"></span>打<span class="_ _2"></span>算<span class="_ _5"></span>使<span class="_ _2"></span>用<span class="_ _4"> </span><span class="ff2">GPU<span class="_ _4"> </span></span>加<span class="_ _2"></span>速<span class="_ _5"></span>的<span class="_ _2"></span>话<span class="_ _2"></span>）<span class="_ _2"></span>。</div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">你<span class="_ _2"></span>可以<span class="_ _2"></span>通<span class="_ _2"></span>过<span class="_ _2"></span>运<span class="_ _2"></span>行<span class="_ _4"> </span><span class="ff5 fs2">nvidia-smi</span>（<span class="_ _2"></span>如<span class="_ _2"></span>果<span class="_ _2"></span>你<span class="_ _2"></span>的<span class="_ _2"></span>机<span class="_ _2"></span>器<span class="_ _2"></span>有<span class="_ _4"> </span><span class="ff2">NVIDIA GPU<span class="_ _6"> </span></span>的<span class="_ _2"></span>话）<span class="_ _2"></span>来<span class="_ _2"></span>查<span class="_ _2"></span>看<span class="_ _4"> </span><span class="ff2">CUDA<span class="_"> </span></span>版<span class="_ _2"></span>本<span class="_ _2"></span>。</div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">然后，访问<span class="_ _0"> </span><span class="ff2 fc1">PyTorch<span class="_"> </span><span class="ff1">官网</span></span>的<span class="ff2">“Get Started”</span>页面，选择合适的安装命令。</div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">例如，如果你的<span class="_ _0"> </span><span class="ff2">CUDA<span class="_"> </span></span>版本是<span class="_ _3"> </span><span class="ff2">11.1</span>，并且你想要安装支持<span class="_ _0"> </span><span class="ff2">CUDA<span class="_"> </span></span>的<span class="_ _0"> </span><span class="ff2">PyTorch<span class="_"> </span></span>版本，你</div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">可能会看到类似于下面的命令（注意：这只是一个示例，你需要根据<span class="_ _0"> </span><span class="ff2">PyTorch<span class="_"> </span></span>官网提</div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">供的命令进行操作）：</div><div class="t m0 x1 h4 y1e ff6 fs3 fc2 sc0 ls0 ws0">bash<span class="_ _6"> </span><span class="ff1 fs4 fc0">复制代码</span></div><div class="c x2 y1f w3 h7"><div class="t m0 x3 h2 y20 ff7 fs0 fc3 sc0 ls0 ws0">conda install </div><div class="t m0 x3 h2 y21 ff7 fs0 fc3 sc0 ls0 ws0">pytorch </div><div class="t m0 x3 h2 ye ff7 fs0 fc3 sc0 ls0 ws0">torchvision </div><div class="t m0 x3 h2 yf ff7 fs0 fc3 sc0 ls0 ws0">torchaudio </div><div class="t m0 x3 h2 y10 ff7 fs0 fc3 sc0 ls0 ws0">cudatoolkit=11.1<span class="fc4 sc0"> </span></div><div class="t m0 x3 h2 y11 ff7 fs0 fc3 sc0 ls0 ws0">-c pytorch</div></div><div class="t m0 x1 h2 y22 ff1 fs0 fc0 sc0 ls0 ws0">如果你<span class="_ _2"></span>没有<span class="_ _0"> </span><span class="ff2">NVIDIA <span class="_ _2"></span>GPU</span>，或<span class="_ _2"></span>者你不<span class="_ _2"></span>需要<span class="_ _0"> </span><span class="ff2">GPU<span class="_ _4"> </span></span>加<span class="_ _2"></span>速，你<span class="_ _2"></span>可以安<span class="_ _2"></span>装<span class="_ _0"> </span><span class="ff2">CPU<span class="_"> </span></span>版<span class="_ _2"></span>本的<span class="_ _0"> </span><span class="ff2">PyTorch</span>，</div><div class="t m0 x1 h2 y23 ff1 fs0 fc0 sc0 ls0 ws0">命令可能如下：</div><div class="t m0 x1 h4 y24 ff6 fs3 fc2 sc0 ls0 ws0">bash<span class="_ _6"> </span><span class="ff1 fs4 fc0">复制代码</span></div><div class="c x4 y25 w4 h8"><div class="t m0 x3 h2 y26 ff7 fs0 fc3 sc0 ls0 ws0">conda </div><div class="t m0 x3 h2 y27 ff7 fs0 fc3 sc0 ls0 ws0">install </div><div class="t m0 x3 h2 y21 ff7 fs0 fc3 sc0 ls0 ws0">pytorch </div><div class="t m0 x3 h2 ye ff7 fs0 fc3 sc0 ls0 ws0">torchvision<span class="fc4 sc0"> </span></div><div class="t m0 x3 h2 yf ff7 fs0 fc3 sc0 ls0 ws0">torchaudio </div><div class="t m0 x3 h2 y10 ff7 fs0 fc3 sc0 ls0 ws0">cpuonly -c </div><div class="t m0 x3 h2 y11 ff7 fs0 fc3 sc0 ls0 ws0">pytorch</div></div><div class="t m0 x5 h9 y28 ff3 fs1 fc0 sc0 ls0 ws0">5</div><div class="t m0 x5 h9 y29 ff3 fs1 fc0 sc0 ls0 ws0">.</div><div class="t m0 x5 h9 y2a ff3 fs1 fc0 sc0 ls0 ws0"> </div><div class="t m0 x5 h3 y2b ff4 fs1 fc0 sc1 ls0 ws0">验</div><div class="t m0 x5 h3 y2c ff4 fs1 fc0 sc1 ls0 ws0">证</div><div class="t m0 x5 h3 y2d ff4 fs1 fc0 sc1 ls0 ws0">安</div><div class="t m0 x5 h3 y2e ff4 fs1 fc0 sc1 ls0 ws0">装</div><div class="t m0 x5 h2 y2f ff1 fs0 fc0 sc0 ls0 ws0">安</div><div class="t m0 x5 h2 y30 ff1 fs0 fc0 sc0 ls0 ws0">装</div><div class="t m0 x5 h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">完</div><div class="t m0 x5 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">成</div><div class="t m0 x5 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">后</div><div class="t m0 x5 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">，</div><div class="t m0 x5 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">你</div><div class="t m0 x5 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">可</div><div class="t m0 x5 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">以</div><div class="t m0 x5 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">通</div><div class="t m0 x5 h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">过</div><div class="t m0 x5 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">运</div><div class="t m0 x5 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">行</div><div class="t m0 x5 ha y3c ff2 fs0 fc0 sc0 ls0 ws0">P</div><div class="t m0 x5 ha y3d ff2 fs0 fc0 sc0 ls0 ws0">y</div><div class="t m0 x5 ha y3e ff2 fs0 fc0 sc0 ls0 ws0">t</div><div class="t m0 x5 ha y3f ff2 fs0 fc0 sc0 ls0 ws0">h</div><div class="t m0 x5 ha y40 ff2 fs0 fc0 sc0 ls0 ws0">o</div><div class="t m0 x5 ha y41 ff2 fs0 fc0 sc0 ls0 ws0">n</div><div class="t m0 x5 h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">并</div><div class="t m0 x5 h2 y43 ff1 fs0 fc0 sc0 ls0 ws0">尝</div><div class="t m0 x5 h2 y44 ff1 fs0 fc0 sc0 ls0 ws0">试</div><div class="t m0 x5 h2 y45 ff1 fs0 fc0 sc0 ls0 ws0">导</div><div class="t m0 x5 h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">入</div><div class="t m0 x5 ha y47 ff2 fs0 fc0 sc0 ls0 ws0">P</div><div class="t m0 x5 ha y48 ff2 fs0 fc0 sc0 ls0 ws0">y</div><div class="t m0 x5 ha y49 ff2 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x5 ha y4a ff2 fs0 fc0 sc0 ls0 ws0">o</div><div class="t m0 x5 ha y4b ff2 fs0 fc0 sc0 ls0 ws0">r</div><div class="t m0 x5 ha y4c ff2 fs0 fc0 sc0 ls0 ws0">c</div><div class="t m0 x5 ha y4d ff2 fs0 fc0 sc0 ls0 ws0">h</div><a class="l"><div class="d m1"></div></a><a class="l"><div class="d m1"></div></a></div><div class="pi" data-data='{"ctm":[1.611639,0.000000,0.000000,1.611639,0.000000,0.000000]}'></div></div>
100+评论
captcha
    相关资源
    类型标题大小时间
    ZIP二相混合式步进电机闭环矢量SVPWM控制simulink仿真模型参考文献：1 两相混合式步进电机高?性能闭环驱动?系统研102.09KB7月前
    ZIPMATLAB轴承动力学代码（正常、外圈故障、内圈故障、滚动体故障），根据滚动轴承故障机理建模（含数学方程建立和公式推导）并在MA1.29MB7月前
    ZIPSVMD源程序及信号分解实例（Matlab完整源码和数据)738.83KB7月前
    ZIPexcel文件比对软件93MB7月前
    ZIP在Visual Studio Code（VSCode）中配置Python环境是一个相对简单且灵活的过程 以下是一步一步的指导，帮15.03KB7月前
    ZIPView UI Plus基于vue的基础工程211.77KB7月前
    ZIP500W 无桥PFC开关电源设计资料，C语言源码 硬件原理 500W 无桥PFC开关电源设计资料，C语言源码 硬件原理52.28KB7月前
    ZIP在PyCharm中配置Python环境是一个相对简单且直观的过程，以下是详细的步骤说明：一、准备工作确保您已经安装了Pyt14.16KB7月前