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<div class="section" id="module-torch.overrides">
<span id="torch-overrides"></span><h1>torch.overrides<a class="headerlink" href="#module-torch.overrides" title="Permalink to this heading">¶</a></h1>
<p>This module exposes various helper functions for the <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>
protocol. See <a class="reference internal" href="notes/extending.html#extending-torch-python"><span class="std std-ref">Extending torch Python API</span></a> for more details on the
<code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code> protocol.</p>
<div class="section" id="functions">
<h2>Functions<a class="headerlink" href="#functions" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.get_ignored_functions">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">get_ignored_functions</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#get_ignored_functions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.get_ignored_functions" title="Permalink to this definition">¶</a></dt>
<dd><p>Return public functions that cannot be overridden by <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A tuple of functions that are publicly available in the torch API but cannot
be overridden with <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>. Mostly this is because none of the
arguments of these functions are tensors or tensor-likes.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>Set[Callable]</p>
</dd>
</dl>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="o">.</span><span class="n">as_subclass</span> <span class="ow">in</span> <span class="n">torch</span><span class="o">.</span><span class="n">overrides</span><span class="o">.</span><span class="n">get_ignored_functions</span><span class="p">()</span>
<span class="go">True</span>
<span class="gp">>>> </span><span class="n">torch</span><span class="o">.</span><span class="n">add</span> <span class="ow">in</span> <span class="n">torch</span><span class="o">.</span><span class="n">overrides</span><span class="o">.</span><span class="n">get_ignored_functions</span><span class="p">()</span>
<span class="go">False</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.get_overridable_functions">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">get_overridable_functions</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#get_overridable_functions"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.get_overridable_functions" title="Permalink to this definition">¶</a></dt>
<dd><p>List functions that are overridable via __torch_function__</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A dictionary that maps namespaces that contain overridable functions
to functions in that namespace that can be overridden.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>Dict[Any, List[Callable]]</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.resolve_name">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">resolve_name</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">f</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#resolve_name"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.resolve_name" title="Permalink to this definition">¶</a></dt>
<dd><p>Get a human readable string name for a function passed to
__torch_function__</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>f</strong> (<em>Callable</em>) – Function to resolve the name of.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Name of the function; if eval’ed it should give back the input
function.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.get_testing_overrides">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">get_testing_overrides</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#get_testing_overrides"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.get_testing_overrides" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a dict containing dummy overrides for all overridable functions</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>A dictionary that maps overridable functions in the PyTorch API to
lambda functions that have the same signature as the real function
and unconditionally return -1. These lambda functions are useful
for testing API coverage for a type that defines <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>Dict[Callable, Callable]</p>
</dd>
</dl>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">inspect</span>
<span class="gp">>>> </span><span class="n">my_add</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">overrides</span><span class="o">.</span><span class="n">get_testing_overrides</span><span class="p">()[</span><span class="n">torch</span><span class="o">.</span><span class="n">add</span><span class="p">]</span>
<span class="gp">>>> </span><span class="n">inspect</span><span class="o">.</span><span class="n">signature</span><span class="p">(</span><span class="n">my_add</span><span class="p">)</span>
<span class="go"><Signature (input, other, out=None)></span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.handle_torch_function">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">handle_torch_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">public_api</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">relevant_args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#handle_torch_function"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.handle_torch_function" title="Permalink to this definition">¶</a></dt>
<dd><p>Implement a function with checks for <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code> overrides.</p>
<p>See torch::autograd::handle_torch_function for the equivalent of this
function in the C++ implementation.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>public_api</strong> (<em>function</em>) – Function exposed by the public torch API originally called like
<code class="docutils literal notranslate"><span class="pre">public_api(*args,</span> <span class="pre">**kwargs)</span></code> on which arguments are now being
checked.</p></li>
<li><p><strong>relevant_args</strong> (<em>iterable</em>) – Iterable of arguments to check for __torch_function__ methods.</p></li>
<li><p><strong>args</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.12)"><em>tuple</em></a>) – Arbitrary positional arguments originally passed into <code class="docutils literal notranslate"><span class="pre">public_api</span></code>.</p></li>
<li><p><strong>kwargs</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.12)"><em>tuple</em></a>) – Arbitrary keyword arguments originally passed into <code class="docutils literal notranslate"><span class="pre">public_api</span></code>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Result from calling <code class="docutils literal notranslate"><span class="pre">implementation</span></code> or an <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>
method, as appropriate.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.12)">object</a></p>
</dd>
</dl>
<p>:raises TypeError : if no implementation is found.:</p>
<p class="rubric">Example</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">a</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">if</span> <span class="n">has_torch_function_unary</span><span class="p">(</span><span class="n">a</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">handle_torch_function</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="p">(</span><span class="n">a</span><span class="p">,),</span> <span class="n">a</span><span class="p">)</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="mi">0</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.has_torch_function">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">has_torch_function</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#torch.overrides.has_torch_function" title="Permalink to this definition">¶</a></dt>
<dd><p>Check for __torch_function__ implementations in the elements of an iterable
or if a __torch_function__ mode is enabled. Considers exact <code class="docutils literal notranslate"><span class="pre">Tensor</span></code> s
and <code class="docutils literal notranslate"><span class="pre">Parameter</span></code> s non-dispatchable. Use this to guard a call to
<a class="reference internal" href="#torch.overrides.handle_torch_function" title="torch.overrides.handle_torch_function"><code class="xref py py-func docutils literal notranslate"><span class="pre">handle_torch_function()</span></code></a>; don’t use it to test if something
is Tensor-like, use <a class="reference internal" href="#torch.overrides.is_tensor_like" title="torch.overrides.is_tensor_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">is_tensor_like()</span></code></a> instead.
:param relevant_args: Iterable or arguments to check for __torch_function__ methods.
:type relevant_args: iterable</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>True if any of the elements of relevant_args have __torch_function__
implementations, False otherwise.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)">bool</a></p>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">torch.is_tensor_like</span></code></dt><dd><p>Checks if something is a Tensor-like, including an exact <code class="docutils literal notranslate"><span class="pre">Tensor</span></code>.</p>
</dd>
</dl>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.is_tensor_like">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">is_tensor_like</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inp</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#is_tensor_like"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.is_tensor_like" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns <code class="docutils literal notranslate"><span class="pre">True</span></code> if the passed-in input is a Tensor-like.</p>
<p>Currently, this occurs whenever there’s a <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>
attribute on the type of the input.</p>
<p class="rubric">Examples</p>
<p>A subclass of tensor is generally a Tensor-like.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">class</span> <span class="nc">SubTensor</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span> <span class="o">...</span>
<span class="gp">>>> </span><span class="n">is_tensor_like</span><span class="p">(</span><span class="n">SubTensor</span><span class="p">([</span><span class="mi">0</span><span class="p">]))</span>
<span class="go">True</span>
</pre></div>
</div>
<p>Built-in or user types aren’t usually Tensor-like.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">is_tensor_like</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span>
<span class="go">False</span>
<span class="gp">>>> </span><span class="n">is_tensor_like</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
<span class="go">False</span>
<span class="gp">>>> </span><span class="k">class</span> <span class="nc">NotATensor</span><span class="p">:</span> <span class="o">...</span>
<span class="gp">>>> </span><span class="n">is_tensor_like</span><span class="p">(</span><span class="n">NotATensor</span><span class="p">())</span>
<span class="go">False</span>
</pre></div>
</div>
<p>But, they can be made Tensor-like by implementing __torch_function__.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">class</span> <span class="nc">TensorLike</span><span class="p">:</span>
<span class="gp">... </span> <span class="nd">@classmethod</span>
<span class="gp">... </span> <span class="k">def</span> <span class="nf">__torch_function__</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="o">-</span><span class="mi">1</span>
<span class="gp">>>> </span><span class="n">is_tensor_like</span><span class="p">(</span><span class="n">TensorLike</span><span class="p">())</span>
<span class="go">True</span>
</pre></div>
</div>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.is_tensor_method_or_property">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">is_tensor_method_or_property</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#is_tensor_method_or_property"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.is_tensor_method_or_property" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if the function passed in is a handler for a
method or property belonging to <code class="docutils literal notranslate"><span class="pre">torch.Tensor</span></code>, as passed
into <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>For properties, their <code class="docutils literal notranslate"><span class="pre">__get__</span></code> method must be passed in.</p>
</div>
<p>This may be needed, in particular, for the following reasons:</p>
<ol class="arabic simple">
<li><p>Methods/properties sometimes don’t contain a <cite>__module__</cite> slot.</p></li>
<li><p>They require that the first passed-in argument is an instance
of <code class="docutils literal notranslate"><span class="pre">torch.Tensor</span></code>.</p></li>
</ol>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">is_tensor_method_or_property</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="o">.</span><span class="n">add</span><span class="p">)</span>
<span class="go">True</span>
<span class="gp">>>> </span><span class="n">is_tensor_method_or_property</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">add</span><span class="p">)</span>
<span class="go">False</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)">bool</a></p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="torch.overrides.wrap_torch_function">
<span class="sig-prename descclassname"><span class="pre">torch.overrides.</span></span><span class="sig-name descname"><span class="pre">wrap_torch_function</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dispatcher</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/torch/overrides.html#wrap_torch_function"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch.overrides.wrap_torch_function" title="Permalink to this definition">¶</a></dt>
<dd><p>Wraps a given function with <code class="docutils literal notranslate"><span class="pre">__torch_function__</span></code> -related functionality.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>dispatcher</strong> (<em>Callable</em>) – A callable that returns an iterable of Tensor-likes passed into the function.</p>
</dd>
</dl>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>This decorator may reduce the performance of your code. Generally, it’s enough to express
your code as a series of functions that, themselves, support __torch_function__. If you
find yourself in the rare situation where this is not the case, e.g. if you’re wrapping a
low-level library and you also need it to work for Tensor-likes, then this function is available.</p>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">def</span> <span class="nf">dispatcher</span><span class="p">(</span><span class="n">a</span><span class="p">):</span> <span class="c1"># Must have the same signature as func</span>
<span class="gp">... </span> <span class="k">return</span> <span class="p">(</span><span class="n">a</span><span class="p">,)</span>
<span class="gp">>>> </span><span class="nd">@torch</span><span class="o">.</span><span class="n">overrides</span><span class="o">.</span><span class="n">wrap_torch_function</span><span class="p">(</span><span class="n">dispatcher</span><span class="p">)</span>
<span class="gp">>>> </span><span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">a</span><span class="p">):</span> <span class="c1"># This will make func dispatchable by __torch_function__</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="mi">0</span>
</pre></div>
</div>
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