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@@ -813,6 +813,41 @@ <h1>Source code for torch.cuda.memory</h1><div class="highlight"><pre>
813813
<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">stats</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
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<span class="n">fmt_dict</span><span class="p">[</span><span class="n">k</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">&quot;.&quot;</span><span class="p">,</span> <span class="s2">&quot;-&quot;</span><span class="p">)]</span> <span class="o">=</span> <span class="n">v</span>
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<span class="k">return</span> <span class="s2">&quot;|&quot;</span> <span class="o">+</span> <span class="s2">&quot;|</span><span class="se">\n</span><span class="s2">|&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">lines</span><span class="p">)</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="o">**</span><span class="n">fmt_dict</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;|</span><span class="se">\n</span><span class="s2">&quot;</span></div>
816+
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<span class="k">def</span> <span class="nf">list_gpu_processes</span><span class="p">(</span><span class="n">device</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Device</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
819+
<span class="sa">r</span><span class="sd">&quot;&quot;&quot;Returns a human-readable printout of the running processes</span>
820+
<span class="sd"> and their GPU memory use for a given device.</span>
821+
822+
<span class="sd"> This can be useful to display periodically during training, or when</span>
823+
<span class="sd"> handling out-of-memory exceptions.</span>
824+
825+
<span class="sd"> Arguments:</span>
826+
<span class="sd"> device (torch.device or int, optional): selected device. Returns</span>
827+
<span class="sd"> printout for the current device, given by :func:`~torch.cuda.current_device`,</span>
828+
<span class="sd"> if :attr:`device` is ``None`` (default).</span>
829+
<span class="sd"> &quot;&quot;&quot;</span>
830+
831+
<span class="k">try</span><span class="p">:</span>
832+
<span class="kn">import</span> <span class="nn">pynvml</span> <span class="c1"># type: ignore</span>
833+
<span class="k">except</span> <span class="ne">ModuleNotFoundError</span><span class="p">:</span>
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<span class="k">return</span><span class="p">(</span><span class="s2">&quot;pynvml module not found, please install pynvml&quot;</span><span class="p">)</span>
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<span class="kn">from</span> <span class="nn">pynvml</span> <span class="kn">import</span> <span class="n">NVMLError_DriverNotLoaded</span>
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<span class="k">try</span><span class="p">:</span>
837+
<span class="n">pynvml</span><span class="o">.</span><span class="n">nvmlInit</span><span class="p">()</span>
838+
<span class="k">except</span> <span class="n">NVMLError_DriverNotLoaded</span><span class="p">:</span>
839+
<span class="k">return</span> <span class="p">(</span><span class="s2">&quot;cuda driver can&#39;t be loaded, is cuda enabled?&quot;</span><span class="p">)</span>
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<span class="n">device</span> <span class="o">=</span> <span class="n">_get_device_index</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="n">optional</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
841+
<span class="n">handle</span> <span class="o">=</span> <span class="n">pynvml</span><span class="o">.</span><span class="n">nvmlDeviceGetHandleByIndex</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
842+
<span class="n">procs</span> <span class="o">=</span> <span class="n">pynvml</span><span class="o">.</span><span class="n">nvmlDeviceGetComputeRunningProcesses</span><span class="p">(</span><span class="n">handle</span><span class="p">)</span>
843+
<span class="n">lines</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="n">lines</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;GPU:</span><span class="si">{</span><span class="n">device</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
845+
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">procs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
846+
<span class="n">lines</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">&quot;no processes are running&quot;</span><span class="p">)</span>
847+
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">procs</span><span class="p">:</span>
848+
<span class="n">mem</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">usedGpuMemory</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1024</span> <span class="o">*</span> <span class="mi">1024</span><span class="p">)</span>
849+
<span class="n">lines</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;process </span><span class="si">{</span><span class="n">p</span><span class="o">.</span><span class="n">pid</span><span class="si">:</span><span class="s2">&gt;10d</span><span class="si">}</span><span class="s2"> uses </span><span class="si">{</span><span class="n">mem</span><span class="si">:</span><span class="s2">&gt;12.3f</span><span class="si">}</span><span class="s2"> MB GPU memory&quot;</span><span class="p">)</span>
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<span class="k">return</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">lines</span><span class="p">)</span>
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</pre></div>
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