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‎assets/quick-start-module.js

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"# PyTorch does not support Python 2.7 on Windows. Please install with Python 3.",
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"stable,conda,windows,cuda8,python3.5":
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"conda install pytorch cuda80 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda80 -c pytorch",
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"stable,conda,windows,cuda9.0,python3.5":
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"conda install pytorch -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision -c pytorch ",
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"stable,conda,windows,cuda10.0,python3.5":
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"conda install pytorch cuda100 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda100 -c pytorch",
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"stable,conda,windows,cudanone,python3.5":
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"conda install pytorch-cpu -c pytorch<br />pip3 install torchvision",
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"conda install pytorch-cpu torchvision-cpu -c pytorch",
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"stable,conda,windows,cuda8,python3.6":
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"conda install pytorch cuda80 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda80 -c pytorch",
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"stable,conda,windows,cuda9.0,python3.6":
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"conda install pytorch -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision -c pytorch",
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"stable,conda,windows,cuda10.0,python3.6":
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"conda install pytorch cuda100 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda100 -c pytorch",
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"stable,conda,windows,cudanone,python3.6":
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"conda install pytorch-cpu -c pytorch<br />pip3 install torchvision",
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"conda install pytorch-cpu torchvision-cpu -c pytorch",
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"stable,conda,windows,cuda8,python3.7":
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"conda install pytorch cuda80 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda80 -c pytorch",
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"stable,conda,windows,cuda9.0,python3.7":
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"conda install pytorch -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision -c pytorch",
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"stable,conda,windows,cuda10.0,python3.7":
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"conda install pytorch cuda100 -c pytorch<br />pip3 install torchvision",
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"conda install pytorch torchvision cuda100 -c pytorch",
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"stable,conda,windows,cudanone,python3.7":
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"conda install pytorch-cpu -c pytorch<br />pip3 install torchvision",
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"conda install pytorch-cpu torchvision-cpu -c pytorch",
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"stable,pip,macos,cuda8,python2.7":
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"pip install torch torchvision<br /># MacOS Binaries dont support CUDA, install from source if CUDA is needed",

‎feed.xml

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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.7.3">Jekyll</generator><link href="https://pytorch.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://pytorch.org/" rel="alternate" type="text/html" /><updated>2018-12-08T12:01:30-08:00</updated><id>https://pytorch.org/</id><title type="html">PyTorch Website</title><subtitle>Scientific Computing...</subtitle><author><name>Facebook</name></author><entry><title type="html">The road to 1.0: production ready PyTorch</title><link href="https://pytorch.org/blog/the-road-to-1_0/" rel="alternate" type="text/html" title="The road to 1.0: production ready PyTorch" /><published>2018-05-02T00:00:00-07:00</published><updated>2018-05-02T00:00:00-07:00</updated><id>https://pytorch.org/blog/the-road-to-1_0</id><content type="html" xml:base="https://pytorch.org/blog/the-road-to-1_0/">&lt;p&gt;We would like to give you a preview of the roadmap for PyTorch 1.0 , the next release of PyTorch. Over the last year, we’ve had 0.2, 0.3 and 0.4 transform PyTorch from a [Torch+Chainer]-like interface into something cleaner, adding double-backwards, numpy-like functions, advanced indexing and removing Variable boilerplate. At this time, we’re confident that the API is in a reasonable and stable state to confidently release a 1.0.&lt;/p&gt;
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<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.7.3">Jekyll</generator><link href="https://pytorch.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://pytorch.org/" rel="alternate" type="text/html" /><updated>2018-12-08T14:38:52-08:00</updated><id>https://pytorch.org/</id><title type="html">PyTorch Website</title><subtitle>Scientific Computing...</subtitle><author><name>Facebook</name></author><entry><title type="html">The road to 1.0: production ready PyTorch</title><link href="https://pytorch.org/blog/the-road-to-1_0/" rel="alternate" type="text/html" title="The road to 1.0: production ready PyTorch" /><published>2018-05-02T00:00:00-07:00</published><updated>2018-05-02T00:00:00-07:00</updated><id>https://pytorch.org/blog/the-road-to-1_0</id><content type="html" xml:base="https://pytorch.org/blog/the-road-to-1_0/">&lt;p&gt;We would like to give you a preview of the roadmap for PyTorch 1.0 , the next release of PyTorch. Over the last year, we’ve had 0.2, 0.3 and 0.4 transform PyTorch from a [Torch+Chainer]-like interface into something cleaner, adding double-backwards, numpy-like functions, advanced indexing and removing Variable boilerplate. At this time, we’re confident that the API is in a reasonable and stable state to confidently release a 1.0.&lt;/p&gt;
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&lt;p&gt;However, 1.0 isn’t just about stability of the interface.&lt;/p&gt;
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‎get-started/locally/index.html

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<p>To install PyTorch via Anaconda, and do not have a CUDA-capable[LINK] system or do not require CUDA, use the following <code class="highlighter-rouge">conda</code> command.</p>
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch-cpu <span class="nt">-c</span> pytorch
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pip3 install torchvision
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch-cpu torchvision-cpu <span class="nt">-c</span> pytorch
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</code></pre></div></div>
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<h4 id="cuda-90">CUDA 9.0</h4>
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<p>To install PyTorch via Anaconda, and you are using CUDA 9.0, use the following <code class="highlighter-rouge">conda</code> command:</p>
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch <span class="nt">-c</span> pytorch
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pip3 install torchvision
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch torchvision <span class="nt">-c</span> pytorch
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</code></pre></div></div>
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<h4 id="cuda-8x">CUDA 8.x</h4>
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch cuda80 <span class="nt">-c</span> pytorch
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pip3 install torchvision
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch torchvision cuda80 <span class="nt">-c</span> pytorch
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<h4 id="cuda-100">CUDA 10.0</h4>
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch cuda100 <span class="nt">-c</span> pytorch
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pip3 install torchvision
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<div class="language-bash highlighter-rouge"><div class="highlight"><pre class="highlight"><code>conda install pytorch torchvision cuda100 <span class="nt">-c</span> pytorch
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<h3 id="pip-1">pip</h3>

‎get_started/installation/windows.md

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To install PyTorch via Anaconda, and do not have a CUDA-capable[LINK] system or do not require CUDA, use the following `conda` command.
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```bash
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conda install pytorch-cpu -c pytorch
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pip3 install torchvision
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conda install pytorch-cpu torchvision-cpu -c pytorch
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```
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#### CUDA 9.0
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To install PyTorch via Anaconda, and you are using CUDA 9.0, use the following `conda` command:
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```bash
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conda install pytorch -c pytorch
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pip3 install torchvision
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conda install pytorch torchvision -c pytorch
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#### CUDA 8.x
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```bash
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conda install pytorch cuda80 -c pytorch
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conda install pytorch torchvision cuda80 -c pytorch
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```
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#### CUDA 10.0
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```bash
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conda install pytorch torchvision cuda100 -c pytorch
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### pip

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