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<li class="toctree-l1 current"><a class="current reference internal" href="#">Installing C++ Distributions of PyTorch</a></li>
<li class="toctree-l1"><a class="reference internal" href="frontend.html">The C++ Frontend</a></li>
<li class="toctree-l1"><a class="reference internal" href="api/library_root.html">Library API</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notes/inference_mode.html">Inference Mode</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/maybe_owned.html">MaybeOwned<Tensor></a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/tensor_basics.html">Tensor Basics</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/tensor_creation.html">Tensor Creation API</a></li>
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<div class="section" id="installing-c-distributions-of-pytorch">
<h1>Installing C++ Distributions of PyTorch<a class="headerlink" href="#installing-c-distributions-of-pytorch" title="Permalink to this heading">¶</a></h1>
<p>We provide binary distributions of all headers, libraries and CMake
configuration files required to depend on PyTorch. We call this distribution
<em>LibTorch</em>, and you can download ZIP archives containing the latest LibTorch
distribution on <a class="reference external" href="https://pytorch.org/get-started/locally/">our website</a>. Below
is a small example of writing a minimal application that depends on LibTorch
and uses the <code class="docutils literal notranslate"><span class="pre">torch::Tensor</span></code> class which comes with the PyTorch C++ API.</p>
<div class="section" id="minimal-example">
<h2>Minimal Example<a class="headerlink" href="#minimal-example" title="Permalink to this heading">¶</a></h2>
<p>The first step is to download the LibTorch ZIP archive via the link above. For
example:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>wget<span class="w"> </span>https://download.pytorch.org/libtorch/nightly/cpu/libtorch-shared-with-deps-latest.zip
unzip<span class="w"> </span>libtorch-shared-with-deps-latest.zip
</pre></div>
</div>
<p>Note that the above link has CPU-only libtorch. If you would like to download a GPU-enabled
libtorch, find the right link in the link selector on <a class="reference external" href="https://pytorch.org">https://pytorch.org</a></p>
<p>If you’re a Windows developer and wouldn’t like to use CMake, you could jump to the Visual Studio
Extension section.</p>
<p>Next, we can write a minimal CMake build configuration to develop a small
application that depends on LibTorch. CMake is not a hard requirement for using
LibTorch, but it is the recommended and blessed build system and will be well
supported into the future. A most basic <cite>CMakeLists.txt</cite> file could look like
this:</p>
<div class="highlight-cmake notranslate"><div class="highlight"><pre><span></span><span class="nb">cmake_minimum_required</span><span class="p">(</span><span class="s">VERSION</span><span class="w"> </span><span class="s">3.18</span><span class="w"> </span><span class="s">FATAL_ERROR</span><span class="p">)</span>
<span class="nb">project</span><span class="p">(</span><span class="s">example-app</span><span class="p">)</span>
<span class="nb">find_package</span><span class="p">(</span><span class="s">Torch</span><span class="w"> </span><span class="s">REQUIRED</span><span class="p">)</span>
<span class="nb">set</span><span class="p">(</span><span class="s">CMAKE_CXX_FLAGS</span><span class="w"> </span><span class="s2">"${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}"</span><span class="p">)</span>
<span class="nb">add_executable</span><span class="p">(</span><span class="s">example-app</span><span class="w"> </span><span class="s">example-app.cpp</span><span class="p">)</span>
<span class="nb">target_link_libraries</span><span class="p">(</span><span class="s">example-app</span><span class="w"> </span><span class="s2">"${TORCH_LIBRARIES}"</span><span class="p">)</span>
<span class="nb">set_property</span><span class="p">(</span><span class="s">TARGET</span><span class="w"> </span><span class="s">example-app</span><span class="w"> </span><span class="s">PROPERTY</span><span class="w"> </span><span class="s">CXX_STANDARD</span><span class="w"> </span><span class="s">17</span><span class="p">)</span>
<span class="c"># The following code block is suggested to be used on Windows.</span>
<span class="c"># According to https://github.com/pytorch/pytorch/issues/25457,</span>
<span class="c"># the DLLs need to be copied to avoid memory errors.</span>
<span class="nb">if</span><span class="w"> </span><span class="p">(</span><span class="s">MSVC</span><span class="p">)</span>
<span class="w"> </span><span class="nb">file</span><span class="p">(</span><span class="s">GLOB</span><span class="w"> </span><span class="s">TORCH_DLLS</span><span class="w"> </span><span class="s2">"${TORCH_INSTALL_PREFIX}/lib/*.dll"</span><span class="p">)</span>
<span class="w"> </span><span class="nb">add_custom_command</span><span class="p">(</span><span class="s">TARGET</span><span class="w"> </span><span class="s">example-app</span>
<span class="w"> </span><span class="s">POST_BUILD</span>
<span class="w"> </span><span class="s">COMMAND</span><span class="w"> </span><span class="o">${</span><span class="nv">CMAKE_COMMAND</span><span class="o">}</span><span class="w"> </span><span class="s">-E</span><span class="w"> </span><span class="s">copy_if_different</span>
<span class="w"> </span><span class="o">${</span><span class="nv">TORCH_DLLS</span><span class="o">}</span>
<span class="w"> </span><span class="o">$<</span><span class="nv">TARGET_FILE_DIR:example-app</span><span class="o">></span><span class="p">)</span>
<span class="nb">endif</span><span class="w"> </span><span class="p">(</span><span class="s">MSVC</span><span class="p">)</span>
</pre></div>
</div>
<p>The implementation of our example will simply create a new <cite>torch::Tensor</cite> and
print it:</p>
<div class="highlight-cpp notranslate"><div class="highlight"><pre><span></span><span class="cp">#include</span><span class="w"> </span><span class="cpf"><torch/torch.h></span>
<span class="cp">#include</span><span class="w"> </span><span class="cpf"><iostream></span>
<span class="kt">int</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">torch</span><span class="o">::</span><span class="n">Tensor</span><span class="w"> </span><span class="n">tensor</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">torch</span><span class="o">::</span><span class="n">rand</span><span class="p">({</span><span class="mi">2</span><span class="p">,</span><span class="w"> </span><span class="mi">3</span><span class="p">});</span>
<span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">cout</span><span class="w"> </span><span class="o"><<</span><span class="w"> </span><span class="n">tensor</span><span class="w"> </span><span class="o"><<</span><span class="w"> </span><span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
<span class="p">}</span>
</pre></div>
</div>
<p>While there are more fine-grained headers you can include to access only parts
of the PyTorch C++ API, including <cite>torch/torch.h</cite> is the most sure-proof way of
including most of its functionality.</p>
<p>The last step is to build the application. For this, assume our example
directory is laid out like this:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>example-app/
<span class="w"> </span>CMakeLists.txt
<span class="w"> </span>example-app.cpp
</pre></div>
</div>
<p>We can now run the following commands to build the application from within the
<code class="docutils literal notranslate"><span class="pre">example-app/</span></code> folder:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>mkdir<span class="w"> </span>build
<span class="nb">cd</span><span class="w"> </span>build
cmake<span class="w"> </span>-DCMAKE_PREFIX_PATH<span class="o">=</span>/absolute/path/to/libtorch<span class="w"> </span>..
cmake<span class="w"> </span>--build<span class="w"> </span>.<span class="w"> </span>--config<span class="w"> </span>Release
</pre></div>
</div>
<p>where <code class="docutils literal notranslate"><span class="pre">/absolute/path/to/libtorch</span></code> should be the absolute (!) path to the unzipped LibTorch
distribution. If PyTorch was installed via conda or pip, <cite>CMAKE_PREFIX_PATH</cite> can be queried
using <cite>torch.utils.cmake_prefix_path</cite> variable. In that case CMake configuration step would look something like follows:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>cmake<span class="w"> </span>-DCMAKE_PREFIX_PATH<span class="o">=</span><span class="sb">`</span>python3<span class="w"> </span>-c<span class="w"> </span><span class="s1">'import torch;print(torch.utils.cmake_prefix_path)'</span><span class="sb">`</span><span class="w"> </span>..
</pre></div>
</div>
<p>If all goes well, it will look something like this:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>root@4b5a67132e81:/example-app#<span class="w"> </span>mkdir<span class="w"> </span>build
root@4b5a67132e81:/example-app#<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>build
root@4b5a67132e81:/example-app/build#<span class="w"> </span>cmake<span class="w"> </span>-DCMAKE_PREFIX_PATH<span class="o">=</span>/path/to/libtorch<span class="w"> </span>..
--<span class="w"> </span>The<span class="w"> </span>C<span class="w"> </span>compiler<span class="w"> </span>identification<span class="w"> </span>is<span class="w"> </span>GNU<span class="w"> </span><span class="m">5</span>.4.0
--<span class="w"> </span>The<span class="w"> </span>CXX<span class="w"> </span>compiler<span class="w"> </span>identification<span class="w"> </span>is<span class="w"> </span>GNU<span class="w"> </span><span class="m">5</span>.4.0
--<span class="w"> </span>Check<span class="w"> </span><span class="k">for</span><span class="w"> </span>working<span class="w"> </span>C<span class="w"> </span>compiler:<span class="w"> </span>/usr/bin/cc
--<span class="w"> </span>Check<span class="w"> </span><span class="k">for</span><span class="w"> </span>working<span class="w"> </span>C<span class="w"> </span>compiler:<span class="w"> </span>/usr/bin/cc<span class="w"> </span>--<span class="w"> </span>works
--<span class="w"> </span>Detecting<span class="w"> </span>C<span class="w"> </span>compiler<span class="w"> </span>ABI<span class="w"> </span>info
--<span class="w"> </span>Detecting<span class="w"> </span>C<span class="w"> </span>compiler<span class="w"> </span>ABI<span class="w"> </span>info<span class="w"> </span>-<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Detecting<span class="w"> </span>C<span class="w"> </span>compile<span class="w"> </span>features
--<span class="w"> </span>Detecting<span class="w"> </span>C<span class="w"> </span>compile<span class="w"> </span>features<span class="w"> </span>-<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Check<span class="w"> </span><span class="k">for</span><span class="w"> </span>working<span class="w"> </span>CXX<span class="w"> </span>compiler:<span class="w"> </span>/usr/bin/c++
--<span class="w"> </span>Check<span class="w"> </span><span class="k">for</span><span class="w"> </span>working<span class="w"> </span>CXX<span class="w"> </span>compiler:<span class="w"> </span>/usr/bin/c++<span class="w"> </span>--<span class="w"> </span>works
--<span class="w"> </span>Detecting<span class="w"> </span>CXX<span class="w"> </span>compiler<span class="w"> </span>ABI<span class="w"> </span>info
--<span class="w"> </span>Detecting<span class="w"> </span>CXX<span class="w"> </span>compiler<span class="w"> </span>ABI<span class="w"> </span>info<span class="w"> </span>-<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Detecting<span class="w"> </span>CXX<span class="w"> </span>compile<span class="w"> </span>features
--<span class="w"> </span>Detecting<span class="w"> </span>CXX<span class="w"> </span>compile<span class="w"> </span>features<span class="w"> </span>-<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread.h
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread.h<span class="w"> </span>-<span class="w"> </span>found
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create<span class="w"> </span>-<span class="w"> </span>not<span class="w"> </span>found
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create<span class="w"> </span><span class="k">in</span><span class="w"> </span>pthreads
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create<span class="w"> </span><span class="k">in</span><span class="w"> </span>pthreads<span class="w"> </span>-<span class="w"> </span>not<span class="w"> </span>found
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create<span class="w"> </span><span class="k">in</span><span class="w"> </span>pthread
--<span class="w"> </span>Looking<span class="w"> </span><span class="k">for</span><span class="w"> </span>pthread_create<span class="w"> </span><span class="k">in</span><span class="w"> </span>pthread<span class="w"> </span>-<span class="w"> </span>found
--<span class="w"> </span>Found<span class="w"> </span>Threads:<span class="w"> </span>TRUE
--<span class="w"> </span>Configuring<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Generating<span class="w"> </span><span class="k">done</span>
--<span class="w"> </span>Build<span class="w"> </span>files<span class="w"> </span>have<span class="w"> </span>been<span class="w"> </span>written<span class="w"> </span>to:<span class="w"> </span>/example-app/build
root@4b5a67132e81:/example-app/build#<span class="w"> </span>cmake<span class="w"> </span>--build<span class="w"> </span>.<span class="w"> </span>--config<span class="w"> </span>Release
Scanning<span class="w"> </span>dependencies<span class="w"> </span>of<span class="w"> </span>target<span class="w"> </span>example-app
<span class="o">[</span><span class="w"> </span><span class="m">50</span>%<span class="o">]</span><span class="w"> </span>Building<span class="w"> </span>CXX<span class="w"> </span>object<span class="w"> </span>CMakeFiles/example-app.dir/example-app.cpp.o
<span class="o">[</span><span class="m">100</span>%<span class="o">]</span><span class="w"> </span>Linking<span class="w"> </span>CXX<span class="w"> </span>executable<span class="w"> </span>example-app
<span class="o">[</span><span class="m">100</span>%<span class="o">]</span><span class="w"> </span>Built<span class="w"> </span>target<span class="w"> </span>example-app
</pre></div>
</div>
<p>Executing the resulting <code class="docutils literal notranslate"><span class="pre">example-app</span></code> binary found in the <code class="docutils literal notranslate"><span class="pre">build</span></code> folder
should now merrily print the tensor (exact output subject to randomness):</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>root@4b5a67132e81:/example-app/build#<span class="w"> </span>./example-app
<span class="m">0</span>.2063<span class="w"> </span><span class="m">0</span>.6593<span class="w"> </span><span class="m">0</span>.0866
<span class="m">0</span>.0796<span class="w"> </span><span class="m">0</span>.5841<span class="w"> </span><span class="m">0</span>.1569
<span class="o">[</span><span class="w"> </span>Variable<span class="o">[</span>CPUFloatType<span class="o">]{</span><span class="m">2</span>,3<span class="o">}</span><span class="w"> </span><span class="o">]</span>
</pre></div>
</div>
<div class="admonition tip">
<p class="admonition-title">Tip</p>
<p>On Windows, debug and release builds are not ABI-compatible. If you plan to
build your project in debug mode, please try the debug version of LibTorch.
Also, make sure you specify the correct configuration in the <code class="docutils literal notranslate"><span class="pre">cmake</span> <span class="pre">--build</span> <span class="pre">.</span></code>
line above.</p>
</div>
</div>
<div class="section" id="system-requirements">
<h2>System Requirements<a class="headerlink" href="#system-requirements" title="Permalink to this heading">¶</a></h2>
<p>To ensure smooth installation and usage of LibTorch, please ensure your system
meets the following requirements:</p>
<ol class="arabic simple">
<li><p><strong>GLIBC Version</strong>:</p></li>
</ol>
<blockquote>
<div><ul class="simple">
<li><p>GLIBC 2.29 or newer for cxx11 ABI version</p></li>
</ul>
</div></blockquote>
<ol class="arabic simple" start="2">
<li><p><strong>GCC Version</strong>:</p></li>
</ol>
<blockquote>
<div><ul class="simple">
<li><p>GCC 9 or newer for cxx11</p></li>
</ul>
</div></blockquote>
</div>
<div class="section" id="visual-studio-extension">
<h2>Visual Studio Extension<a class="headerlink" href="#visual-studio-extension" title="Permalink to this heading">¶</a></h2>
<p><a class="reference external" href="https://marketplace.visualstudio.com/items?itemName=YiZhang.LibTorch001">LibTorch Project Template</a> can help Windows developers
set all libtorch project settings and link options for debug and release.
It’s easy to use and you could check out the <a class="reference external" href="https://ossci-windows.s3.us-east-1.amazonaws.com/vsextension/demo.mp4">demo video</a>.
The only prerequisite is to download the libtorch on <a class="reference external" href="https://pytorch.org">https://pytorch.org</a></p>
</div>
<div class="section" id="support">
<h2>Support<a class="headerlink" href="#support" title="Permalink to this heading">¶</a></h2>
<p>If you run into any troubles with this installation and minimal usage guide,
please use our <a class="reference external" href="https://discuss.pytorch.org/">forum</a> or <a class="reference external" href="https://github.com/pytorch/pytorch/issues">GitHub issues</a> to get in touch.</p>
</div>
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