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<li class="toctree-l1"><a class="reference internal" href="notes/amp_examples.html">CUDA Automatic Mixed Precision examples</a></li>
<li class="toctree-l1"><a class="reference internal" href="notes/autograd.html">Autograd mechanics</a></li>
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<span class="target" id="module-torch.package"></span><span class="target" id="module-torch.package.analyze"></span><section id="torch-package">
<h1>torch.package<a class="headerlink" href="#torch-package" title="Permalink to this heading">¶</a></h1>
<p><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> adds support for creating packages containing both artifacts and arbitrary
PyTorch code. These packages can be saved, shared, used to load and execute models
at a later date or on a different machine, and can even be deployed to production using
<code class="docutils literal notranslate"><span class="pre">torch::deploy</span></code>.</p>
<p>This document contains tutorials, how-to guides, explanations, and an API reference that
will help you learn more about <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> and how to use it.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>This module depends on the <code class="docutils literal notranslate"><span class="pre">pickle</span></code> module which is not secure. Only unpackage data you trust.</p>
<p>It is possible to construct malicious pickle data which will <strong>execute arbitrary code during unpickling</strong>.
Never unpackage data that could have come from an untrusted source, or that could have been tampered with.</p>
<p>For more information, review the <a class="reference external" href="https://docs.python.org/3/library/pickle.html">documentation</a> for the <code class="docutils literal notranslate"><span class="pre">pickle</span></code> module.</p>
</div>
<nav class="contents local" id="contents">
<ul class="simple">
<li><p><a class="reference internal" href="#tutorials" id="id1">Tutorials</a></p>
<ul>
<li><p><a class="reference internal" href="#packaging-your-first-model" id="id2">Packaging your first model</a></p></li>
</ul>
</li>
<li><p><a class="reference internal" href="#how-do-i" id="id3">How do I…</a></p>
<ul>
<li><p><a class="reference internal" href="#see-what-is-inside-a-package" id="id4">See what is inside a package?</a></p></li>
<li><p><a class="reference internal" href="#see-why-a-given-module-was-included-as-a-dependency" id="id5">See why a given module was included as a dependency?</a></p></li>
<li><p><a class="reference internal" href="#include-arbitrary-resources-with-my-package-and-access-them-later" id="id6">Include arbitrary resources with my package and access them later?</a></p></li>
<li><p><a class="reference internal" href="#customize-how-a-class-is-packaged" id="id7">Customize how a class is packaged?</a></p></li>
<li><p><a class="reference internal" href="#test-in-my-source-code-whether-or-not-it-is-executing-inside-a-package" id="id8">Test in my source code whether or not it is executing inside a package?</a></p></li>
<li><p><a class="reference internal" href="#patch-code-into-a-package" id="id9">Patch code into a package?</a></p></li>
<li><p><a class="reference internal" href="#access-package-contents-from-packaged-code" id="id10">Access package contents from packaged code?</a></p></li>
<li><p><a class="reference internal" href="#distinguish-between-packaged-code-and-non-packaged-code" id="id11">Distinguish between packaged code and non-packaged code?</a></p></li>
<li><p><a class="reference internal" href="#re-export-an-imported-object" id="id12">Re-export an imported object?</a></p></li>
<li><p><a class="reference internal" href="#package-a-torchscript-module" id="id13">Package a TorchScript module?</a></p></li>
</ul>
</li>
<li><p><a class="reference internal" href="#explanation" id="id14">Explanation</a></p>
<ul>
<li><p><a class="reference internal" href="#torch-package-format-overview" id="id15"><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> Format Overview</a></p></li>
<li><p><a class="reference internal" href="#how-torch-package-finds-your-code-s-dependencies" id="id16">How <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> finds your code’s dependencies</a></p></li>
<li><p><a class="reference internal" href="#dependency-management" id="id17">Dependency Management</a></p></li>
<li><p><a class="reference internal" href="#torch-package-sharp-edges" id="id18"><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> sharp edges</a></p></li>
<li><p><a class="reference internal" href="#how-torch-package-keeps-packages-isolated-from-each-other" id="id19">How <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> keeps packages isolated from each other</a></p></li>
</ul>
</li>
<li><p><a class="reference internal" href="#api-reference" id="id20">API Reference</a></p></li>
</ul>
</nav>
<section id="tutorials">
<h2><a class="toc-backref" href="#id1" role="doc-backlink">Tutorials</a><a class="headerlink" href="#tutorials" title="Permalink to this heading">¶</a></h2>
<section id="packaging-your-first-model">
<h3><a class="toc-backref" href="#id2" role="doc-backlink">Packaging your first model</a><a class="headerlink" href="#packaging-your-first-model" title="Permalink to this heading">¶</a></h3>
<p>A tutorial that guides you through packaging and unpackaging a simple model is available
<a class="reference external" href="https://colab.research.google.com/drive/1lFZkLyViGfXxB-m3jqlyTQuYToo3XLo-">on Colab</a>.
After completing this exercise, you will be familiar with the basic API for creating and using
Torch packages.</p>
</section>
</section>
<section id="how-do-i">
<h2><a class="toc-backref" href="#id3" role="doc-backlink">How do I…</a><a class="headerlink" href="#how-do-i" title="Permalink to this heading">¶</a></h2>
<section id="see-what-is-inside-a-package">
<h3><a class="toc-backref" href="#id4" role="doc-backlink">See what is inside a package?</a><a class="headerlink" href="#see-what-is-inside-a-package" title="Permalink to this heading">¶</a></h3>
<section id="treat-the-package-like-a-zip-archive">
<h4>Treat the package like a ZIP archive<a class="headerlink" href="#treat-the-package-like-a-zip-archive" title="Permalink to this heading">¶</a></h4>
<p>The container format for a <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> is ZIP, so any tools that work with standard ZIP files should
work for exploring the contents. Some common ways to interact with ZIP files:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">unzip</span> <span class="pre">my_package.pt</span></code> will unzip the <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> archive to disk, where you can freely inspect its contents.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ unzip my_package.pt && tree my_package
my_package
├── .data
│ ├── 94304870911616.storage
│ ├── 94304900784016.storage
│ ├── extern_modules
│ └── version
├── models
│ └── model_1.pkl
└── torchvision
└── models
├── resnet.py
└── utils.py
~ cd my_package && cat torchvision/models/resnet.py
...
</pre></div>
</div>
<ul class="simple">
<li><p>The Python <code class="docutils literal notranslate"><span class="pre">zipfile</span></code> module provides a standard way to read and write ZIP archive contents.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">zipfile</span> <span class="kn">import</span> <span class="n">ZipFile</span>
<span class="k">with</span> <span class="n">ZipFile</span><span class="p">(</span><span class="s2">"my_package.pt"</span><span class="p">)</span> <span class="k">as</span> <span class="n">myzip</span><span class="p">:</span>
<span class="n">file_bytes</span> <span class="o">=</span> <span class="n">myzip</span><span class="o">.</span><span class="n">read</span><span class="p">(</span><span class="s2">"torchvision/models/resnet.py"</span><span class="p">)</span>
<span class="c1"># edit file_bytes in some way</span>
<span class="n">myzip</span><span class="o">.</span><span class="n">writestr</span><span class="p">(</span><span class="s2">"torchvision/models/resnet.py"</span><span class="p">,</span> <span class="n">new_file_bytes</span><span class="p">)</span>
</pre></div>
</div>
<ul class="simple">
<li><p>vim has the ability to natively read ZIP archives. You can even edit files and :<code class="docutils literal notranslate"><span class="pre">write</span></code> them back into the archive!</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># add this to your .vimrc to treat `*.pt` files as zip files</span>
<span class="n">au</span> <span class="n">BufReadCmd</span> <span class="o">*.</span><span class="n">pt</span> <span class="n">call</span> <span class="nb">zip</span><span class="c1">#Browse(expand("<amatch>"))</span>
<span class="o">~</span> <span class="n">vi</span> <span class="n">my_package</span><span class="o">.</span><span class="n">pt</span>
</pre></div>
</div>
</section>
<section id="use-the-file-structure-api">
<h4>Use the <code class="docutils literal notranslate"><span class="pre">file_structure()</span></code> API<a class="headerlink" href="#use-the-file-structure-api" title="Permalink to this heading">¶</a></h4>
<p><a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> provides a <code class="docutils literal notranslate"><span class="pre">file_structure()</span></code> method, which will return a printable
and queryable <a class="reference internal" href="#torch.package.Directory" title="torch.package.Directory"><code class="xref py py-class docutils literal notranslate"><span class="pre">Directory</span></code></a> object. The <a class="reference internal" href="#torch.package.Directory" title="torch.package.Directory"><code class="xref py py-class docutils literal notranslate"><span class="pre">Directory</span></code></a> object is a simple directory structure that you can use to explore the
current contents of a <code class="docutils literal notranslate"><span class="pre">torch.package</span></code>.</p>
<p>The <a class="reference internal" href="#torch.package.Directory" title="torch.package.Directory"><code class="xref py py-class docutils literal notranslate"><span class="pre">Directory</span></code></a> object itself is directly printable and will print out a file tree representation. To filter what is returned,
use the glob-style <code class="docutils literal notranslate"><span class="pre">include</span></code> and <code class="docutils literal notranslate"><span class="pre">exclude</span></code> filtering arguments.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="s1">'my_package.pt'</span><span class="p">)</span> <span class="k">as</span> <span class="n">pe</span><span class="p">:</span>
<span class="n">pe</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s1">'models'</span><span class="p">,</span> <span class="s1">'model_1.pkl'</span><span class="p">,</span> <span class="n">mod</span><span class="p">)</span>
<span class="n">importer</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="s1">'my_package.pt'</span><span class="p">)</span>
<span class="c1"># can limit printed items with include/exclude args</span>
<span class="nb">print</span><span class="p">(</span><span class="n">importer</span><span class="o">.</span><span class="n">file_structure</span><span class="p">(</span><span class="n">include</span><span class="o">=</span><span class="p">[</span><span class="s2">"**/utils.py"</span><span class="p">,</span> <span class="s2">"**/*.pkl"</span><span class="p">],</span> <span class="n">exclude</span><span class="o">=</span><span class="s2">"**/*.storage"</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="n">importer</span><span class="o">.</span><span class="n">file_structure</span><span class="p">())</span> <span class="c1"># will print out all files</span>
</pre></div>
</div>
<p>Output:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span># filtered with glob pattern:
# include=["**/utils.py", "**/*.pkl"], exclude="**/*.storage"
─── my_package.pt
├── models
│ └── model_1.pkl
└── torchvision
└── models
└── utils.py
# all files
─── my_package.pt
├── .data
│ ├── 94304870911616.storage
│ ├── 94304900784016.storage
│ ├── extern_modules
│ └── version
├── models
│ └── model_1.pkl
└── torchvision
└── models
├── resnet.py
└── utils.py
</pre></div>
</div>
<p>You can also query <a class="reference internal" href="#torch.package.Directory" title="torch.package.Directory"><code class="xref py py-class docutils literal notranslate"><span class="pre">Directory</span></code></a> objects with the <code class="docutils literal notranslate"><span class="pre">has_file()</span></code> method.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">importer_file_structure</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">file_structure</span><span class="p">()</span>
<span class="n">found</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">importer_file_structure</span><span class="o">.</span><span class="n">has_file</span><span class="p">(</span><span class="s2">"package_a/subpackage.py"</span><span class="p">)</span>
</pre></div>
</div>
</section>
</section>
<section id="see-why-a-given-module-was-included-as-a-dependency">
<h3><a class="toc-backref" href="#id5" role="doc-backlink">See why a given module was included as a dependency?</a><a class="headerlink" href="#see-why-a-given-module-was-included-as-a-dependency" title="Permalink to this heading">¶</a></h3>
<p>Say there is a given module <code class="docutils literal notranslate"><span class="pre">foo</span></code>, and you want to know why your <a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a> is pulling in <code class="docutils literal notranslate"><span class="pre">foo</span></code> as a dependency.</p>
<p><a class="reference internal" href="#torch.package.PackageExporter.get_rdeps" title="torch.package.PackageExporter.get_rdeps"><code class="xref py py-meth docutils literal notranslate"><span class="pre">PackageExporter.get_rdeps()</span></code></a> will return all modules that directly depend on <code class="docutils literal notranslate"><span class="pre">foo</span></code>.</p>
<p>If you would like to see how a given module <code class="docutils literal notranslate"><span class="pre">src</span></code> depends on <code class="docutils literal notranslate"><span class="pre">foo</span></code>, the <a class="reference internal" href="#torch.package.PackageExporter.all_paths" title="torch.package.PackageExporter.all_paths"><code class="xref py py-meth docutils literal notranslate"><span class="pre">PackageExporter.all_paths()</span></code></a> method will
return a DOT-formatted graph showing all the dependency paths between <code class="docutils literal notranslate"><span class="pre">src</span></code> and <code class="docutils literal notranslate"><span class="pre">foo</span></code>.</p>
<p>If you would just like to see the whole dependency graph of your <a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a>, you can use <a class="reference internal" href="#torch.package.PackageExporter.dependency_graph_string" title="torch.package.PackageExporter.dependency_graph_string"><code class="xref py py-meth docutils literal notranslate"><span class="pre">PackageExporter.dependency_graph_string()</span></code></a>.</p>
</section>
<section id="include-arbitrary-resources-with-my-package-and-access-them-later">
<h3><a class="toc-backref" href="#id6" role="doc-backlink">Include arbitrary resources with my package and access them later?</a><a class="headerlink" href="#include-arbitrary-resources-with-my-package-and-access-them-later" title="Permalink to this heading">¶</a></h3>
<p><a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a> exposes three methods, <code class="docutils literal notranslate"><span class="pre">save_pickle</span></code>, <code class="docutils literal notranslate"><span class="pre">save_text</span></code> and <code class="docutils literal notranslate"><span class="pre">save_binary</span></code> that allow you to save
Python objects, text, and binary data to a package.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">PackageExporter</span><span class="p">(</span><span class="s2">"package.pt"</span><span class="p">)</span> <span class="k">as</span> <span class="n">exporter</span><span class="p">:</span>
<span class="c1"># Pickles the object and saves to `my_resources/tensor.pkl` in the archive.</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s2">"my_resources"</span><span class="p">,</span> <span class="s2">"tensor.pkl"</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">4</span><span class="p">))</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_text</span><span class="p">(</span><span class="s2">"config_stuff"</span><span class="p">,</span> <span class="s2">"words.txt"</span><span class="p">,</span> <span class="s2">"a sample string"</span><span class="p">)</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_binary</span><span class="p">(</span><span class="s2">"raw_data"</span><span class="p">,</span> <span class="s2">"binary"</span><span class="p">,</span> <span class="n">my_bytes</span><span class="p">)</span>
</pre></div>
</div>
<p><a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> exposes complementary methods named <code class="docutils literal notranslate"><span class="pre">load_pickle</span></code>, <code class="docutils literal notranslate"><span class="pre">load_text</span></code> and <code class="docutils literal notranslate"><span class="pre">load_binary</span></code> that allow you to load
Python objects, text and binary data from a package.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">importer</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">PackageImporter</span><span class="p">(</span><span class="s2">"package.pt"</span><span class="p">)</span>
<span class="n">my_tensor</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s2">"my_resources"</span><span class="p">,</span> <span class="s2">"tensor.pkl"</span><span class="p">)</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_text</span><span class="p">(</span><span class="s2">"config_stuff"</span><span class="p">,</span> <span class="s2">"words.txt"</span><span class="p">)</span>
<span class="n">binary</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_binary</span><span class="p">(</span><span class="s2">"raw_data"</span><span class="p">,</span> <span class="s2">"binary"</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="customize-how-a-class-is-packaged">
<h3><a class="toc-backref" href="#id7" role="doc-backlink">Customize how a class is packaged?</a><a class="headerlink" href="#customize-how-a-class-is-packaged" title="Permalink to this heading">¶</a></h3>
<p><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> allows for the customization of how classes are packaged. This behavior is accessed through defining the method
<code class="docutils literal notranslate"><span class="pre">__reduce_package__</span></code> on a class and by defining a corresponding de-packaging function. This is similar to defining <code class="docutils literal notranslate"><span class="pre">__reduce__</span></code> for
Python’s normal pickling process.</p>
<p>Steps:</p>
<ol class="arabic simple">
<li><p>Define the method <code class="docutils literal notranslate"><span class="pre">__reduce_package__(self,</span> <span class="pre">exporter:</span> <span class="pre">PackageExporter)</span></code> on the target class. This method should do the work to save the class instance inside of the package, and should return a tuple of the corresponding de-packaging function with the arguments needed to invoke the de-packaging function. This method is called by the <code class="docutils literal notranslate"><span class="pre">PackageExporter</span></code> when it encounters an instance of the target class.</p></li>
<li><p>Define a de-packaging function for the class. This de-packaging function should do the work to reconstruct and return an instance of the class. The function signature’s first parameter should be a <code class="docutils literal notranslate"><span class="pre">PackageImporter</span></code> instance, and the rest of the parameters are user defined.</p></li>
</ol>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># foo.py [Example of customizing how class Foo is packaged]</span>
<span class="kn">from</span> <span class="nn">torch.package</span> <span class="kn">import</span> <span class="n">PackageExporter</span><span class="p">,</span> <span class="n">PackageImporter</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="k">class</span> <span class="nc">Foo</span><span class="p">:</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">my_string</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">my_string</span> <span class="o">=</span> <span class="n">my_string</span>
<span class="bp">self</span><span class="o">.</span><span class="n">time_imported</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">time_exported</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">def</span> <span class="nf">__reduce_package__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exporter</span><span class="p">:</span> <span class="n">PackageExporter</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Called by ``torch.package.PackageExporter``'s Pickler's ``persistent_id`` when</span>
<span class="sd"> saving an instance of this object. This method should do the work to save this</span>
<span class="sd"> object inside of the ``torch.package`` archive.</span>
<span class="sd"> Returns function w/ arguments to load the object from a</span>
<span class="sd"> ``torch.package.PackageImporter``'s Pickler's ``persistent_load`` function.</span>
<span class="sd"> """</span>
<span class="c1"># use this pattern to ensure no naming conflicts with normal dependencies,</span>
<span class="c1"># anything saved under this module name shouldn't conflict with other</span>
<span class="c1"># items in the package</span>
<span class="n">generated_module_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"foo-generated._</span><span class="si">{</span><span class="n">exporter</span><span class="o">.</span><span class="n">get_unique_id</span><span class="p">()</span><span class="si">}</span><span class="s2">"</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_text</span><span class="p">(</span>
<span class="n">generated_module_name</span><span class="p">,</span>
<span class="s2">"foo.txt"</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">my_string</span> <span class="o">+</span> <span class="s2">", with exporter modification!"</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">time_exported</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">clock_gettime</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="c1"># returns de-packaging function w/ arguments to invoke with</span>
<span class="k">return</span> <span class="p">(</span><span class="n">unpackage_foo</span><span class="p">,</span> <span class="p">(</span><span class="n">generated_module_name</span><span class="p">,</span> <span class="n">time_exported</span><span class="p">,))</span>
<span class="k">def</span> <span class="nf">unpackage_foo</span><span class="p">(</span>
<span class="n">importer</span><span class="p">:</span> <span class="n">PackageImporter</span><span class="p">,</span> <span class="n">generated_module_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">time_exported</span><span class="p">:</span> <span class="nb">float</span>
<span class="p">)</span> <span class="o">-></span> <span class="n">Foo</span><span class="p">:</span>
<span class="sd">"""</span>
<span class="sd"> Called by ``torch.package.PackageImporter``'s Pickler's ``persistent_load`` function</span>
<span class="sd"> when depickling a Foo object.</span>
<span class="sd"> Performs work of loading and returning a Foo instance from a ``torch.package`` archive.</span>
<span class="sd"> """</span>
<span class="n">time_imported</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">clock_gettime</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="n">foo</span> <span class="o">=</span> <span class="n">Foo</span><span class="p">(</span><span class="n">importer</span><span class="o">.</span><span class="n">load_text</span><span class="p">(</span><span class="n">generated_module_name</span><span class="p">,</span> <span class="s2">"foo.txt"</span><span class="p">))</span>
<span class="n">foo</span><span class="o">.</span><span class="n">time_imported</span> <span class="o">=</span> <span class="n">time_imported</span>
<span class="n">foo</span><span class="o">.</span><span class="n">time_exported</span> <span class="o">=</span> <span class="n">time_exported</span>
<span class="k">return</span> <span class="n">foo</span>
</pre></div>
</div>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># example of saving instances of class Foo</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torch.package</span> <span class="kn">import</span> <span class="n">PackageImporter</span><span class="p">,</span> <span class="n">PackageExporter</span>
<span class="kn">import</span> <span class="nn">foo</span>
<span class="n">foo_1</span> <span class="o">=</span> <span class="n">foo</span><span class="o">.</span><span class="n">Foo</span><span class="p">(</span><span class="s2">"foo_1 initial string"</span><span class="p">)</span>
<span class="n">foo_2</span> <span class="o">=</span> <span class="n">foo</span><span class="o">.</span><span class="n">Foo</span><span class="p">(</span><span class="s2">"foo_2 initial string"</span><span class="p">)</span>
<span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="s1">'foo_package.pt'</span><span class="p">)</span> <span class="k">as</span> <span class="n">pe</span><span class="p">:</span>
<span class="c1"># save as normal, no extra work necessary</span>
<span class="n">pe</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s1">'foo_collection'</span><span class="p">,</span> <span class="s1">'foo1.pkl'</span><span class="p">,</span> <span class="n">foo_1</span><span class="p">)</span>
<span class="n">pe</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s1">'foo_collection'</span><span class="p">,</span> <span class="s1">'foo2.pkl'</span><span class="p">,</span> <span class="n">foo_2</span><span class="p">)</span>
<span class="n">pi</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="s1">'foo_package.pt'</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">pi</span><span class="o">.</span><span class="n">file_structure</span><span class="p">())</span>
<span class="n">imported_foo</span> <span class="o">=</span> <span class="n">pi</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s1">'foo_collection'</span><span class="p">,</span> <span class="s1">'foo1.pkl'</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"foo_1 string: '</span><span class="si">{</span><span class="n">imported_foo</span><span class="o">.</span><span class="n">my_string</span><span class="si">}</span><span class="s2">'"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"foo_1 export time: </span><span class="si">{</span><span class="n">imported_foo</span><span class="o">.</span><span class="n">time_exported</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"foo_1 import time: </span><span class="si">{</span><span class="n">imported_foo</span><span class="o">.</span><span class="n">time_imported</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
</pre></div>
</div>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span># output of running above script
─── foo_package
├── foo-generated
│ ├── _0
│ │ └── foo.txt
│ └── _1
│ └── foo.txt
├── foo_collection
│ ├── foo1.pkl
│ └── foo2.pkl
└── foo.py
foo_1 string: 'foo_1 initial string, with reduction modification!'
foo_1 export time: 9857706.650140837
foo_1 import time: 9857706.652698385
</pre></div>
</div>
</section>
<section id="test-in-my-source-code-whether-or-not-it-is-executing-inside-a-package">
<h3><a class="toc-backref" href="#id8" role="doc-backlink">Test in my source code whether or not it is executing inside a package?</a><a class="headerlink" href="#test-in-my-source-code-whether-or-not-it-is-executing-inside-a-package" title="Permalink to this heading">¶</a></h3>
<p>A <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> will add the attribute <code class="docutils literal notranslate"><span class="pre">__torch_package__</span></code> to every module that it initializes. Your code can check for the
presence of this attribute to determine whether it is executing in a packaged context or not.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># In foo/bar.py:</span>
<span class="k">if</span> <span class="s2">"__torch_package__"</span> <span class="ow">in</span> <span class="nb">dir</span><span class="p">():</span> <span class="c1"># true if the code is being loaded from a package</span>
<span class="k">def</span> <span class="nf">is_in_package</span><span class="p">():</span>
<span class="k">return</span> <span class="kc">True</span>
<span class="n">UserException</span> <span class="o">=</span> <span class="ne">Exception</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">def</span> <span class="nf">is_in_package</span><span class="p">():</span>
<span class="k">return</span> <span class="kc">False</span>
<span class="n">UserException</span> <span class="o">=</span> <span class="n">UnpackageableException</span>
</pre></div>
</div>
<p>Now, the code will behave differently depending on whether it’s imported normally through your Python environment or imported from a
<code class="docutils literal notranslate"><span class="pre">torch.package</span></code>.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">foo.bar</span> <span class="kn">import</span> <span class="n">is_in_package</span>
<span class="nb">print</span><span class="p">(</span><span class="n">is_in_package</span><span class="p">())</span> <span class="c1"># False</span>
<span class="n">loaded_module</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="n">my_package</span><span class="p">)</span><span class="o">.</span><span class="n">import_module</span><span class="p">(</span><span class="s2">"foo.bar"</span><span class="p">)</span>
<span class="n">loaded_module</span><span class="o">.</span><span class="n">is_in_package</span><span class="p">()</span> <span class="c1"># True</span>
</pre></div>
</div>
<p><strong>Warning</strong>: in general, it’s bad practice to have code that behaves differently depending on whether it’s packaged or not. This can lead to
hard-to-debug issues that are sensitive to how you imported your code. If your package is intended to be heavily used, consider restructuring
your code so that it behaves the same way no matter how it was loaded.</p>
</section>
<section id="patch-code-into-a-package">
<h3><a class="toc-backref" href="#id9" role="doc-backlink">Patch code into a package?</a><a class="headerlink" href="#patch-code-into-a-package" title="Permalink to this heading">¶</a></h3>
<p><a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a> offers a <code class="docutils literal notranslate"><span class="pre">save_source_string()</span></code> method that allows one to save arbitrary Python source code to a module of your choosing.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="n">f</span><span class="p">)</span> <span class="k">as</span> <span class="n">exporter</span><span class="p">:</span>
<span class="c1"># Save the my_module.foo available in your current Python environment.</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_module</span><span class="p">(</span><span class="s2">"my_module.foo"</span><span class="p">)</span>
<span class="c1"># This saves the provided string to my_module/foo.py in the package archive.</span>
<span class="c1"># It will override the my_module.foo that was previously saved.</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_source_string</span><span class="p">(</span><span class="s2">"my_module.foo"</span><span class="p">,</span> <span class="n">textwrap</span><span class="o">.</span><span class="n">dedent</span><span class="p">(</span>
<span class="sd">"""\</span>
<span class="sd"> def my_function():</span>
<span class="sd"> print('hello world')</span>
<span class="sd"> """</span>
<span class="p">))</span>
<span class="c1"># If you want to treat my_module.bar as a package</span>
<span class="c1"># (e.g. save to `my_module/bar/__init__.py` instead of `my_module/bar.py)</span>
<span class="c1"># pass is_package=True,</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_source_string</span><span class="p">(</span><span class="s2">"my_module.bar"</span><span class="p">,</span>
<span class="s2">"def foo(): print('hello')</span><span class="se">\n</span><span class="s2">"</span><span class="p">,</span>
<span class="n">is_package</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">importer</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="n">importer</span><span class="o">.</span><span class="n">import_module</span><span class="p">(</span><span class="s2">"my_module.foo"</span><span class="p">)</span><span class="o">.</span><span class="n">my_function</span><span class="p">()</span> <span class="c1"># prints 'hello world'</span>
</pre></div>
</div>
</section>
<section id="access-package-contents-from-packaged-code">
<h3><a class="toc-backref" href="#id10" role="doc-backlink">Access package contents from packaged code?</a><a class="headerlink" href="#access-package-contents-from-packaged-code" title="Permalink to this heading">¶</a></h3>
<p><a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> implements the
<a class="reference external" href="https://docs.python.org/3/library/importlib.html#module-importlib.resources">importlib.resources</a>
API for accessing resources from inside a package.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="n">f</span><span class="p">)</span> <span class="k">as</span> <span class="n">exporter</span><span class="p">:</span>
<span class="c1"># saves text to my_resource/a.txt in the archive</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_text</span><span class="p">(</span><span class="s2">"my_resource"</span><span class="p">,</span> <span class="s2">"a.txt"</span><span class="p">,</span> <span class="s2">"hello world!"</span><span class="p">)</span>
<span class="c1"># saves the tensor to my_pickle/obj.pkl</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s2">"my_pickle"</span><span class="p">,</span> <span class="s2">"obj.pkl"</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
<span class="c1"># see below for module contents</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_module</span><span class="p">(</span><span class="s2">"foo"</span><span class="p">)</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_module</span><span class="p">(</span><span class="s2">"bar"</span><span class="p">)</span>
</pre></div>
</div>
<p>The <code class="docutils literal notranslate"><span class="pre">importlib.resources</span></code> API allows access to resources from within packaged code.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># foo.py:</span>
<span class="kn">import</span> <span class="nn">importlib.resources</span>
<span class="kn">import</span> <span class="nn">my_resource</span>
<span class="c1"># returns "hello world!"</span>
<span class="k">def</span> <span class="nf">get_my_resource</span><span class="p">():</span>
<span class="k">return</span> <span class="n">importlib</span><span class="o">.</span><span class="n">resources</span><span class="o">.</span><span class="n">read_text</span><span class="p">(</span><span class="n">my_resource</span><span class="p">,</span> <span class="s2">"a.txt"</span><span class="p">)</span>
</pre></div>
</div>
<p>Using <code class="docutils literal notranslate"><span class="pre">importlib.resources</span></code> is the recommended way to access package contents from within packaged code, since it complies
with the Python standard. However, it is also possible to access the parent <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> instance itself from within
packaged code.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># bar.py:</span>
<span class="kn">import</span> <span class="nn">torch_package_importer</span> <span class="c1"># this is the PackageImporter that imported this module.</span>
<span class="c1"># Prints "hello world!", equivalent to importlib.resources.read_text</span>
<span class="k">def</span> <span class="nf">get_my_resource</span><span class="p">():</span>
<span class="k">return</span> <span class="n">torch_package_importer</span><span class="o">.</span><span class="n">load_text</span><span class="p">(</span><span class="s2">"my_resource"</span><span class="p">,</span> <span class="s2">"a.txt"</span><span class="p">)</span>
<span class="c1"># You also do things that the importlib.resources API does not support, like loading</span>
<span class="c1"># a pickled object from the package.</span>
<span class="k">def</span> <span class="nf">get_my_pickle</span><span class="p">():</span>
<span class="k">return</span> <span class="n">torch_package_importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s2">"my_pickle"</span><span class="p">,</span> <span class="s2">"obj.pkl"</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="distinguish-between-packaged-code-and-non-packaged-code">
<h3><a class="toc-backref" href="#id11" role="doc-backlink">Distinguish between packaged code and non-packaged code?</a><a class="headerlink" href="#distinguish-between-packaged-code-and-non-packaged-code" title="Permalink to this heading">¶</a></h3>
<p>To tell if an object’s code is from a <code class="docutils literal notranslate"><span class="pre">torch.package</span></code>, use the <code class="docutils literal notranslate"><span class="pre">torch.package.is_from_package()</span></code> function.
Note: if an object is from a package but its definition is from a module marked <code class="docutils literal notranslate"><span class="pre">extern</span></code> or from <code class="docutils literal notranslate"><span class="pre">stdlib</span></code>,
this check will return <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">importer</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="n">mod</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">import_module</span><span class="p">(</span><span class="s1">'foo'</span><span class="p">)</span>
<span class="n">obj</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s1">'model'</span><span class="p">,</span> <span class="s1">'model.pkl'</span><span class="p">)</span>
<span class="n">txt</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_text</span><span class="p">(</span><span class="s1">'text'</span><span class="p">,</span> <span class="s1">'my_test.txt'</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">is_from_package</span><span class="p">(</span><span class="n">mod</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">is_from_package</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
<span class="k">assert</span> <span class="ow">not</span> <span class="n">is_from_package</span><span class="p">(</span><span class="n">txt</span><span class="p">)</span> <span class="c1"># str is from stdlib, so this will return False</span>
</pre></div>
</div>
</section>
<section id="re-export-an-imported-object">
<h3><a class="toc-backref" href="#id12" role="doc-backlink">Re-export an imported object?</a><a class="headerlink" href="#re-export-an-imported-object" title="Permalink to this heading">¶</a></h3>
<p>To re-export an object that was previously imported by a <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a>, you must make the new <a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a>
aware of the original <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> so that it can find source code for your object’s dependencies.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">importer</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="n">obj</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s2">"model"</span><span class="p">,</span> <span class="s2">"model.pkl"</span><span class="p">)</span>
<span class="c1"># re-export obj in a new package</span>
<span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="n">f2</span><span class="p">,</span> <span class="n">importer</span><span class="o">=</span><span class="p">(</span><span class="n">importer</span><span class="p">,</span> <span class="n">sys_importer</span><span class="p">))</span> <span class="k">as</span> <span class="n">exporter</span><span class="p">:</span>
<span class="n">exporter</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s2">"model"</span><span class="p">,</span> <span class="s2">"model.pkl"</span><span class="p">,</span> <span class="n">obj</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="package-a-torchscript-module">
<h3><a class="toc-backref" href="#id13" role="doc-backlink">Package a TorchScript module?</a><a class="headerlink" href="#package-a-torchscript-module" title="Permalink to this heading">¶</a></h3>
<p>To package a TorchScript model, use the same <code class="docutils literal notranslate"><span class="pre">save_pickle</span></code> and <code class="docutils literal notranslate"><span class="pre">load_pickle</span></code> APIs as you would with any other object.
Saving TorchScript objects that are attributes or submodules is supported as well with no extra work.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># save TorchScript just like any other object</span>
<span class="k">with</span> <span class="n">PackageExporter</span><span class="p">(</span><span class="n">file_name</span><span class="p">)</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="n">e</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s2">"res"</span><span class="p">,</span> <span class="s2">"script_model.pkl"</span><span class="p">,</span> <span class="n">scripted_model</span><span class="p">)</span>
<span class="n">e</span><span class="o">.</span><span class="n">save_pickle</span><span class="p">(</span><span class="s2">"res"</span><span class="p">,</span> <span class="s2">"mixed_model.pkl"</span><span class="p">,</span> <span class="n">python_model_with_scripted_submodule</span><span class="p">)</span>
<span class="c1"># load as normal</span>
<span class="n">importer</span> <span class="o">=</span> <span class="n">PackageImporter</span><span class="p">(</span><span class="n">file_name</span><span class="p">)</span>
<span class="n">loaded_script</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s2">"res"</span><span class="p">,</span> <span class="s2">"script_model.pkl"</span><span class="p">)</span>
<span class="n">loaded_mixed</span> <span class="o">=</span> <span class="n">importer</span><span class="o">.</span><span class="n">load_pickle</span><span class="p">(</span><span class="s2">"res"</span><span class="p">,</span> <span class="s2">"mixed_model.pkl"</span>
</pre></div>
</div>
</section>
</section>
<section id="explanation">
<h2><a class="toc-backref" href="#id14" role="doc-backlink">Explanation</a><a class="headerlink" href="#explanation" title="Permalink to this heading">¶</a></h2>
<section id="torch-package-format-overview">
<h3><a class="toc-backref" href="#id15" role="doc-backlink"><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> Format Overview</a><a class="headerlink" href="#torch-package-format-overview" title="Permalink to this heading">¶</a></h3>
<p>A <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> file is a ZIP archive which conventionally uses the <code class="docutils literal notranslate"><span class="pre">.pt</span></code> extension. Inside the ZIP archive, there are two kinds of files:</p>
<ul class="simple">
<li><p>Framework files, which are placed in the <code class="docutils literal notranslate"><span class="pre">.data/</span></code>.</p></li>
<li><p>User files, which is everything else.</p></li>
</ul>
<p>As an example, this is what a fully packaged ResNet model from <code class="docutils literal notranslate"><span class="pre">torchvision</span></code> looks like:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>resnet
├── .data # All framework-specific data is stored here.
│ │ # It's named to avoid conflicts with user-serialized code.
│ ├── 94286146172688.storage # tensor data
│ ├── 94286146172784.storage
│ ├── extern_modules # text file with names of extern modules (e.g. 'torch')
│ ├── version # version metadata
│ ├── ...
├── model # the pickled model
│ └── model.pkl
└── torchvision # all code dependencies are captured as source files
└── models
├── resnet.py
└── utils.py
</pre></div>
</div>
<section id="framework-files">
<h4>Framework files<a class="headerlink" href="#framework-files" title="Permalink to this heading">¶</a></h4>
<p>The <code class="docutils literal notranslate"><span class="pre">.data/</span></code> directory is owned by torch.package, and its contents are considered to be a private implementation detail.
The <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> format makes no guarantees about the contents of <code class="docutils literal notranslate"><span class="pre">.data/</span></code>, but any changes made will be backward compatible
(that is, newer version of PyTorch will always be able to load older <code class="docutils literal notranslate"><span class="pre">torch.packages</span></code>).</p>
<p>Currently, the <code class="docutils literal notranslate"><span class="pre">.data/</span></code> directory contains the following items:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">version</span></code>: a version number for the serialized format, so that the <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> import infrastructures knows how to load this package.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">extern_modules</span></code>: a list of modules that are considered <code class="docutils literal notranslate"><span class="pre">extern:class:`PackageImporter`.</span> <span class="pre">``extern</span></code> modules will be imported using the loading environment’s system importer.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">*.storage</span></code>: serialized tensor data.</p></li>
</ul>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>.data
├── 94286146172688.storage
├── 94286146172784.storage
├── extern_modules
├── version
├── ...
</pre></div>
</div>
</section>
<section id="user-files">
<h4>User files<a class="headerlink" href="#user-files" title="Permalink to this heading">¶</a></h4>
<p>All other files in the archive were put there by a user. The layout is identical to a Python
<a class="reference external" href="https://docs.python.org/3/reference/import.html#regular-packages">regular package</a>. For a deeper dive in how Python packaging works,
please consult <a class="reference external" href="https://www.python.org/doc/essays/packages/">this essay</a> (it’s slightly out of date, so double-check implementation details
with the <a class="reference external" href="https://docs.python.org/3/library/importlib.html">Python reference documentation</a>).</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><package root>
├── model # the pickled model
│ └── model.pkl
├── another_package
│ ├── __init__.py
│ ├── foo.txt # a resource file , see importlib.resources
│ └── ...
└── torchvision
└── models
├── resnet.py # torchvision.models.resnet
└── utils.py # torchvision.models.utils
</pre></div>
</div>
</section>
</section>
<section id="how-torch-package-finds-your-code-s-dependencies">
<h3><a class="toc-backref" href="#id16" role="doc-backlink">How <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> finds your code’s dependencies</a><a class="headerlink" href="#how-torch-package-finds-your-code-s-dependencies" title="Permalink to this heading">¶</a></h3>
<section id="analyzing-an-object-s-dependencies">
<h4>Analyzing an object’s dependencies<a class="headerlink" href="#analyzing-an-object-s-dependencies" title="Permalink to this heading">¶</a></h4>
<p>When you issue a <code class="docutils literal notranslate"><span class="pre">save_pickle(obj,</span> <span class="pre">...)</span></code> call, <a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a> will pickle the object normally. Then, it uses the
<code class="docutils literal notranslate"><span class="pre">pickletools</span></code> standard library module to parse the pickle bytecode.</p>
<p>In a pickle, an object is saved along with a <code class="docutils literal notranslate"><span class="pre">GLOBAL</span></code> opcode that describes where to find the implementation of the object’s type, like:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">GLOBAL</span> <span class="s1">'torchvision.models.resnet Resnet`</span>
</pre></div>
</div>
<p>The dependency resolver will gather up all <code class="docutils literal notranslate"><span class="pre">GLOBAL</span></code> ops and mark them as dependencies of your pickled object.
For more information about pickling and the pickle format, please consult <a class="reference external" href="https://docs.python.org/3/library/pickle.html">the Python docs</a>.</p>
</section>
<section id="analyzing-a-module-s-dependencies">
<h4>Analyzing a module’s dependencies<a class="headerlink" href="#analyzing-a-module-s-dependencies" title="Permalink to this heading">¶</a></h4>
<p>When a Python module is identified as a dependency, <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> walks the module’s python AST representation and looks for import statements with
full support for the standard forms: <code class="docutils literal notranslate"><span class="pre">from</span> <span class="pre">x</span> <span class="pre">import</span> <span class="pre">y</span></code>, <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">z</span></code>, <code class="docutils literal notranslate"><span class="pre">from</span> <span class="pre">w</span> <span class="pre">import</span> <span class="pre">v</span> <span class="pre">as</span> <span class="pre">u</span></code>, etc. When one of these import statements are
encountered, <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> registers the imported modules as dependencies that are then themselves parsed in the same AST walking way.</p>
<p><strong>Note</strong>: AST parsing has limited support for the <code class="docutils literal notranslate"><span class="pre">__import__(...)</span></code> syntax and does not support <code class="docutils literal notranslate"><span class="pre">importlib.import_module</span></code> calls. In general, you should
not expect dynamic imports to be detected by <code class="docutils literal notranslate"><span class="pre">torch.package</span></code>.</p>
</section>
</section>
<section id="dependency-management">
<h3><a class="toc-backref" href="#id17" role="doc-backlink">Dependency Management</a><a class="headerlink" href="#dependency-management" title="Permalink to this heading">¶</a></h3>
<p><code class="docutils literal notranslate"><span class="pre">torch.package</span></code> automatically finds the Python modules that your code and objects depend on. This process is called dependency resolution.
For each module that the dependency resolver finds, you must specify an <em>action</em> to take.</p>
<p>The allowed actions are:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">intern</span></code>: put this module into the package.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">extern</span></code>: declare this module as an external dependency of the package.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">mock</span></code>: stub out this module.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">deny</span></code>: depending on this module will raise an error during package export.</p></li>
</ul>
<p>Finally, there is one more important action that is not technically part of <code class="docutils literal notranslate"><span class="pre">torch.package</span></code>:</p>
<ul class="simple">
<li><p>Refactoring: remove or change the dependencies in your code.</p></li>
</ul>
<p>Note that actions are only defined on entire Python modules. There is no way to package “just” a function or class from a module and leave the rest out.
This is by design. Python does not offer clean boundaries between objects defined in a module. The only defined unit of dependency organization is a
module, so that’s what <code class="docutils literal notranslate"><span class="pre">torch.package</span></code> uses.</p>
<p>Actions are applied to modules using patterns. Patterns can either be module names (<code class="docutils literal notranslate"><span class="pre">"foo.bar"</span></code>) or globs (like <code class="docutils literal notranslate"><span class="pre">"foo.**"</span></code>). You associate a pattern
with an action using methods on <a class="reference internal" href="#torch.package.PackageExporter" title="torch.package.PackageExporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageExporter</span></code></a>, e.g.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">my_exporter</span><span class="o">.</span><span class="n">intern</span><span class="p">(</span><span class="s2">"torchvision.**"</span><span class="p">)</span>
<span class="n">my_exporter</span><span class="o">.</span><span class="n">extern</span><span class="p">(</span><span class="s2">"numpy"</span><span class="p">)</span>
</pre></div>
</div>
<p>If a module matches a pattern, the corresponding action is applied to it. For a given module, patterns will be checked in the order that they were defined,
and the first action will be taken.</p>
<section id="intern">
<h4><code class="docutils literal notranslate"><span class="pre">intern</span></code><a class="headerlink" href="#intern" title="Permalink to this heading">¶</a></h4>
<p>If a module is <code class="docutils literal notranslate"><span class="pre">intern</span></code>-ed, it will be placed into the package.</p>
<p>This action is your model code, or any related code you want to package. For example, if you are trying to package a ResNet from <code class="docutils literal notranslate"><span class="pre">torchvision</span></code>,
you will need to <code class="docutils literal notranslate"><span class="pre">intern</span></code> the module torchvision.models.resnet.</p>
<p>On package import, when your packaged code tries to import an <code class="docutils literal notranslate"><span class="pre">intern</span></code>-ed module, PackageImporter will look inside your package for that module.
If it can’t find that module, an error will be raised. This ensures that each <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> is isolated from the loading environment—even
if you have <code class="docutils literal notranslate"><span class="pre">my_interned_module</span></code> available in both your package and the loading environment, <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> will only use the version in your
package.</p>
<p><strong>Note</strong>: Only Python source modules can be <code class="docutils literal notranslate"><span class="pre">intern</span></code>-ed. Other kinds of modules, like C extension modules and bytecode modules, will raise an error if
you attempt to <code class="docutils literal notranslate"><span class="pre">intern</span></code> them. These kinds of modules need to be <code class="docutils literal notranslate"><span class="pre">mock</span></code>-ed or <code class="docutils literal notranslate"><span class="pre">extern</span></code>-ed.</p>
</section>
<section id="extern">
<h4><code class="docutils literal notranslate"><span class="pre">extern</span></code><a class="headerlink" href="#extern" title="Permalink to this heading">¶</a></h4>
<p>If a module is <code class="docutils literal notranslate"><span class="pre">extern</span></code>-ed, it will not be packaged. Instead, it will be added to a list of external dependencies for this package. You can find this
list on <code class="docutils literal notranslate"><span class="pre">package_exporter.extern_modules</span></code>.</p>
<p>On package import, when the packaged code tries to import an <code class="docutils literal notranslate"><span class="pre">extern</span></code>-ed module, <a class="reference internal" href="#torch.package.PackageImporter" title="torch.package.PackageImporter"><code class="xref py py-class docutils literal notranslate"><span class="pre">PackageImporter</span></code></a> will use the default Python importer to find
that module, as if you did <code class="docutils literal notranslate"><span class="pre">importlib.import_module("my_externed_module")</span></code>. If it can’t find that module, an error will be raised.</p>