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docs/0.3.1/index.html

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<div class="toctree-wrapper compound">
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<p class="caption"><span class="caption-text">torchvision Reference</span></p>
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<ul>
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<li class="toctree-l1"><a class="reference internal" href="torchvision/index.html">torchvision</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="torchvision/datasets.html">torchvision.datasets</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torchvision/models.html">torchvision.models</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torchvision/transforms.html">torchvision.transforms</a></li>
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<li class="toctree-l2"><a class="reference internal" href="torchvision/utils.html">torchvision.utils</a></li>
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</ul>
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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>2018-09-24T19:36:33-07:00</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>2018-09-24T19:44:13-07:00</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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