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<div class="section" id="serialization-semantics">
<h1>Serialization semantics<a class="headerlink" href="#serialization-semantics" title="Permalink to this headline">¶</a></h1>
<div class="section" id="best-practices">
<h2>Best practices<a class="headerlink" href="#best-practices" title="Permalink to this headline">¶</a></h2>
<div class="section" id="recommended-approach-for-saving-a-model">
<span id="recommend-saving-models"></span><h3>Recommended approach for saving a model<a class="headerlink" href="#recommended-approach-for-saving-a-model" title="Permalink to this headline">¶</a></h3>
<p>There are two main approaches for serializing and restoring a model.</p>
<p>The first (recommended) saves and loads only the model parameters:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">the_model</span><span class="o">.</span><span class="n">state_dict</span><span class="p">(),</span> <span class="n">PATH</span><span class="p">)</span>
</pre></div>
</div>
<p>Then later:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">the_model</span> <span class="o">=</span> <span class="n">TheModelClass</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">the_model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">PATH</span><span class="p">))</span>
</pre></div>
</div>
<p>The second saves and loads the entire model:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">the_model</span><span class="p">,</span> <span class="n">PATH</span><span class="p">)</span>
</pre></div>
</div>
<p>Then later:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">the_model</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">PATH</span><span class="p">)</span>
</pre></div>
</div>
<p>However in this case, the serialized data is bound to the specific classes
and the exact directory structure used, so it can break in various ways when
used in other projects, or after some serious refactors.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The 1.6 release of PyTorch switched <code class="docutils literal notranslate"><span class="pre">torch.save</span></code> to use a new
zipfile-based file format. <code class="docutils literal notranslate"><span class="pre">torch.load</span></code> still retains the ability to
load files in the old format. If for any reason you want <code class="docutils literal notranslate"><span class="pre">torch.save</span></code>
to use the old format, pass the kwarg <code class="docutils literal notranslate"><span class="pre">_use_new_zipfile_serialization=False</span></code>.</p>
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