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<section id="windows-faq">
<h1>Windows FAQ<a class="headerlink" href="#windows-faq" title="Permalink to this heading">¶</a></h1>
<section id="building-from-source">
<h2>Building from source<a class="headerlink" href="#building-from-source" title="Permalink to this heading">¶</a></h2>
<section id="include-optional-components">
<h3>Include optional components<a class="headerlink" href="#include-optional-components" title="Permalink to this heading">¶</a></h3>
<p>There are two supported components for Windows PyTorch:
MKL and MAGMA. Here are the steps to build with them.</p>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span><span class="c1">REM Make sure you have 7z and curl installed.</span>
<span class="c1">REM Download MKL files</span>
curl https://s3.amazonaws.com/ossci-windows/mkl_2020.2.254.7z -k -O
7z x -aoa mkl_2020.2.254.7z -omkl
<span class="c1">REM Download MAGMA files</span>
<span class="c1">REM version available:</span>
<span class="c1">REM 2.5.4 (CUDA 10.1 10.2 11.0 11.1) x (Debug Release)</span>
<span class="c1">REM 2.5.3 (CUDA 10.1 10.2 11.0) x (Debug Release)</span>
<span class="c1">REM 2.5.2 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release)</span>
<span class="c1">REM 2.5.1 (CUDA 9.2 10.0 10.1 10.2) x (Debug Release)</span>
<span class="k">set</span> <span class="nv">CUDA_PREFIX</span><span class="p">=</span>cuda102
<span class="k">set</span> <span class="nv">CONFIG</span><span class="p">=</span>release
curl -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_<span class="nv">%CUDA_PREFIX%</span>_<span class="nv">%CONFIG%</span>.7z -o magma.7z
7z x -aoa magma.7z -omagma
<span class="c1">REM Setting essential environment variables</span>
<span class="k">set</span> <span class="s2">"CMAKE_INCLUDE_PATH=</span><span class="nv">%cd%</span><span class="s2">\mkl\include"</span>
<span class="k">set</span> <span class="s2">"LIB=</span><span class="nv">%cd%</span><span class="s2">\mkl\lib;</span><span class="nv">%LIB%</span><span class="s2">"</span>
<span class="k">set</span> <span class="s2">"MAGMA_HOME=</span><span class="nv">%cd%</span><span class="s2">\magma"</span>
</pre></div>
</div>
</section>
<section id="speeding-cuda-build-for-windows">
<h3>Speeding CUDA build for Windows<a class="headerlink" href="#speeding-cuda-build-for-windows" title="Permalink to this heading">¶</a></h3>
<p>Visual Studio doesn’t support parallel custom task currently.
As an alternative, we can use <code class="docutils literal notranslate"><span class="pre">Ninja</span></code> to parallelize CUDA
build tasks. It can be used by typing only a few lines of code.</p>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span><span class="c1">REM Let's install ninja first.</span>
pip install ninja
<span class="c1">REM Set it as the cmake generator</span>
<span class="k">set</span> <span class="nv">CMAKE_GENERATOR</span><span class="p">=</span>Ninja
</pre></div>
</div>
</section>
<section id="one-key-install-script">
<h3>One key install script<a class="headerlink" href="#one-key-install-script" title="Permalink to this heading">¶</a></h3>
<p>You can take a look at <a class="reference external" href="https://github.com/peterjc123/pytorch-scripts">this set of scripts</a>.
It will lead the way for you.</p>
</section>
</section>
<section id="extension">
<h2>Extension<a class="headerlink" href="#extension" title="Permalink to this heading">¶</a></h2>
<section id="cffi-extension">
<h3>CFFI Extension<a class="headerlink" href="#cffi-extension" title="Permalink to this heading">¶</a></h3>
<p>The support for CFFI Extension is very experimental. You must specify
additional <code class="docutils literal notranslate"><span class="pre">libraries</span></code> in <code class="docutils literal notranslate"><span class="pre">Extension</span></code> object to make it build on
Windows.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">ffi</span> <span class="o">=</span> <span class="n">create_extension</span><span class="p">(</span>
<span class="s1">'_ext.my_lib'</span><span class="p">,</span>
<span class="n">headers</span><span class="o">=</span><span class="n">headers</span><span class="p">,</span>
<span class="n">sources</span><span class="o">=</span><span class="n">sources</span><span class="p">,</span>
<span class="n">define_macros</span><span class="o">=</span><span class="n">defines</span><span class="p">,</span>
<span class="n">relative_to</span><span class="o">=</span><span class="vm">__file__</span><span class="p">,</span>
<span class="n">with_cuda</span><span class="o">=</span><span class="n">with_cuda</span><span class="p">,</span>
<span class="n">extra_compile_args</span><span class="o">=</span><span class="p">[</span><span class="s2">"-std=c99"</span><span class="p">],</span>
<span class="n">libraries</span><span class="o">=</span><span class="p">[</span><span class="s1">'ATen'</span><span class="p">,</span> <span class="s1">'_C'</span><span class="p">]</span> <span class="c1"># Append cuda libraries when necessary, like cudart</span>
<span class="p">)</span>
</pre></div>
</div>
</section>
<section id="cpp-extension">
<h3>Cpp Extension<a class="headerlink" href="#cpp-extension" title="Permalink to this heading">¶</a></h3>
<p>This type of extension has better support compared with
the previous one. However, it still needs some manual
configuration. First, you should open the
<strong>x86_x64 Cross Tools Command Prompt for VS 2017</strong>.
And then, you can start your compiling process.</p>
</section>
</section>
<section id="installation">
<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">¶</a></h2>
<section id="package-not-found-in-win-32-channel">
<h3>Package not found in win-32 channel.<a class="headerlink" href="#package-not-found-in-win-32-channel" title="Permalink to this heading">¶</a></h3>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span>Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- pytorch
Current channels:
- https://conda.anaconda.org/pytorch/win-32
- https://conda.anaconda.org/pytorch/noarch
- https://repo.continuum.io/pkgs/main/win-32
- https://repo.continuum.io/pkgs/main/noarch
- https://repo.continuum.io/pkgs/free/win-32
- https://repo.continuum.io/pkgs/free/noarch
- https://repo.continuum.io/pkgs/r/win-32
- https://repo.continuum.io/pkgs/r/noarch
- https://repo.continuum.io/pkgs/pro/win-32
- https://repo.continuum.io/pkgs/pro/noarch
- https://repo.continuum.io/pkgs/msys2/win-32
- https://repo.continuum.io/pkgs/msys2/noarch
</pre></div>
</div>
<p>PyTorch doesn’t work on 32-bit system. Please use Windows and
Python 64-bit version.</p>
</section>
<section id="import-error">
<h3>Import error<a class="headerlink" href="#import-error" title="Permalink to this heading">¶</a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">torch._C</span> <span class="kn">import</span> <span class="o">*</span>
<span class="ne">ImportError</span><span class="p">:</span> <span class="n">DLL</span> <span class="n">load</span> <span class="n">failed</span><span class="p">:</span> <span class="n">The</span> <span class="n">specified</span> <span class="n">module</span> <span class="n">could</span> <span class="ow">not</span> <span class="n">be</span> <span class="n">found</span><span class="o">.</span>
</pre></div>
</div>
<p>The problem is caused by the missing of the essential files. Actually,
we include almost all the essential files that PyTorch need for the conda
package except VC2017 redistributable and some mkl libraries.
You can resolve this by typing the following command.</p>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span>conda install -c peterjc123 vc vs2017_runtime
conda install mkl_fft intel_openmp numpy mkl
</pre></div>
</div>
<p>As for the wheels package, since we didn’t pack some libraries and VS2017
redistributable files in, please make sure you install them manually.
The <a class="reference external" href="https://aka.ms/vs/15/release/VC_redist.x64.exe">VS 2017 redistributable installer</a> can be downloaded.
And you should also pay attention to your installation of Numpy. Make sure it
uses MKL instead of OpenBLAS. You may type in the following command.</p>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span>pip install numpy mkl intel-openmp mkl_fft
</pre></div>
</div>
<p>Another possible cause may be you are using GPU version without NVIDIA
graphics cards. Please replace your GPU package with the CPU one.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">torch._C</span> <span class="kn">import</span> <span class="o">*</span>
<span class="ne">ImportError</span><span class="p">:</span> <span class="n">DLL</span> <span class="n">load</span> <span class="n">failed</span><span class="p">:</span> <span class="n">The</span> <span class="n">operating</span> <span class="n">system</span> <span class="n">cannot</span> <span class="n">run</span> <span class="o">%</span><span class="mf">1.</span>
</pre></div>
</div>
<p>This is actually an upstream issue of Anaconda. When you initialize your
environment with conda-forge channel, this issue will emerge. You may fix
the intel-openmp libraries through this command.</p>
<div class="highlight-bat notranslate"><div class="highlight"><pre><span></span>conda install -c defaults intel-openmp -f
</pre></div>
</div>
</section>
</section>
<section id="usage-multiprocessing">
<h2>Usage (multiprocessing)<a class="headerlink" href="#usage-multiprocessing" title="Permalink to this heading">¶</a></h2>
<section id="multiprocessing-error-without-if-clause-protection">
<h3>Multiprocessing error without if-clause protection<a class="headerlink" href="#multiprocessing-error-without-if-clause-protection" title="Permalink to this heading">¶</a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="ne">RuntimeError</span><span class="p">:</span>
<span class="n">An</span> <span class="n">attempt</span> <span class="n">has</span> <span class="n">been</span> <span class="n">made</span> <span class="n">to</span> <span class="n">start</span> <span class="n">a</span> <span class="n">new</span> <span class="n">process</span> <span class="n">before</span> <span class="n">the</span>
<span class="n">current</span> <span class="n">process</span> <span class="n">has</span> <span class="n">finished</span> <span class="n">its</span> <span class="n">bootstrapping</span> <span class="n">phase</span><span class="o">.</span>
<span class="n">This</span> <span class="n">probably</span> <span class="n">means</span> <span class="n">that</span> <span class="n">you</span> <span class="n">are</span> <span class="ow">not</span> <span class="n">using</span> <span class="n">fork</span> <span class="n">to</span> <span class="n">start</span> <span class="n">your</span>
<span class="n">child</span> <span class="n">processes</span> <span class="ow">and</span> <span class="n">you</span> <span class="n">have</span> <span class="n">forgotten</span> <span class="n">to</span> <span class="n">use</span> <span class="n">the</span> <span class="n">proper</span> <span class="n">idiom</span>
<span class="ow">in</span> <span class="n">the</span> <span class="n">main</span> <span class="n">module</span><span class="p">:</span>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
<span class="n">freeze_support</span><span class="p">()</span>
<span class="o">...</span>
<span class="n">The</span> <span class="s2">"freeze_support()"</span> <span class="n">line</span> <span class="n">can</span> <span class="n">be</span> <span class="n">omitted</span> <span class="k">if</span> <span class="n">the</span> <span class="n">program</span>
<span class="ow">is</span> <span class="ow">not</span> <span class="n">going</span> <span class="n">to</span> <span class="n">be</span> <span class="n">frozen</span> <span class="n">to</span> <span class="n">produce</span> <span class="n">an</span> <span class="n">executable</span><span class="o">.</span>
</pre></div>
</div>
<p>The implementation of <code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code> is different on Windows, which
uses <code class="docutils literal notranslate"><span class="pre">spawn</span></code> instead of <code class="docutils literal notranslate"><span class="pre">fork</span></code>. So we have to wrap the code with an
if-clause to protect the code from executing multiple times. Refactor
your code into the following structure.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">torch</span>
<span class="k">def</span> <span class="nf">main</span><span class="p">()</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">data</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">dataloader</span><span class="p">):</span>
<span class="c1"># do something here</span>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
<span class="n">main</span><span class="p">()</span>
</pre></div>
</div>
</section>
<section id="multiprocessing-error-broken-pipe">
<h3>Multiprocessing error “Broken pipe”<a class="headerlink" href="#multiprocessing-error-broken-pipe" title="Permalink to this heading">¶</a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">ForkingPickler</span><span class="p">(</span><span class="n">file</span><span class="p">,</span> <span class="n">protocol</span><span class="p">)</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
<span class="ne">BrokenPipeError</span><span class="p">:</span> <span class="p">[</span><span class="n">Errno</span> <span class="mi">32</span><span class="p">]</span> <span class="n">Broken</span> <span class="n">pipe</span>
</pre></div>
</div>
<p>This issue happens when the child process ends before the parent process
finishes sending data. There may be something wrong with your code. You
can debug your code by reducing the <code class="docutils literal notranslate"><span class="pre">num_worker</span></code> of
<a class="reference internal" href="../data.html#torch.utils.data.DataLoader" title="torch.utils.data.DataLoader"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataLoader</span></code></a> to zero and see if the issue persists.</p>
</section>
<section id="multiprocessing-error-driver-shut-down">
<h3>Multiprocessing error “driver shut down”<a class="headerlink" href="#multiprocessing-error-driver-shut-down" title="Permalink to this heading">¶</a></h3>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>Couldn’t open shared file mapping: <torch_14808_1591070686>, error code: <1455> at torch\lib\TH\THAllocator.c:154
[windows] driver shut down
</pre></div>
</div>
<p>Please update your graphics driver. If this persists, this may be that your
graphics card is too old or the calculation is too heavy for your card. Please
update the TDR settings according to this <a class="reference external" href="https://www.pugetsystems.com/labs/hpc/Working-around-TDR-in-Windows-for-a-better-GPU-computing-experience-777/">post</a>.</p>
</section>
<section id="cuda-ipc-operations">
<h3>CUDA IPC operations<a class="headerlink" href="#cuda-ipc-operations" title="Permalink to this heading">¶</a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">THCudaCheck</span> <span class="n">FAIL</span> <span class="n">file</span><span class="o">=</span><span class="n">torch</span>\<span class="n">csrc</span>\<span class="n">generic</span>\<span class="n">StorageSharing</span><span class="o">.</span><span class="n">cpp</span> <span class="n">line</span><span class="o">=</span><span class="mi">252</span> <span class="n">error</span><span class="o">=</span><span class="mi">63</span> <span class="p">:</span> <span class="n">OS</span> <span class="n">call</span> <span class="n">failed</span> <span class="ow">or</span> <span class="n">operation</span> <span class="ow">not</span> <span class="n">supported</span> <span class="n">on</span> <span class="n">this</span> <span class="n">OS</span>
</pre></div>
</div>
<p>They are not supported on Windows. Something like doing multiprocessing on CUDA
tensors cannot succeed, there are two alternatives for this.</p>
<p>1. Don’t use <code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code>. Set the <code class="docutils literal notranslate"><span class="pre">num_worker</span></code> of
<a class="reference internal" href="../data.html#torch.utils.data.DataLoader" title="torch.utils.data.DataLoader"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataLoader</span></code></a> to zero.</p>
<p>2. Share CPU tensors instead. Make sure your custom
<code class="xref py py-class docutils literal notranslate"><span class="pre">DataSet</span></code> returns CPU tensors.</p>
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