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Properties
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Basic
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<code class="doc-symbol doc-symbol-toc doc-symbol-attribute"></code>&nbsp;shape
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<code class="doc-symbol doc-symbol-toc doc-symbol-attribute"></code>&nbsp;dtype
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<code class="doc-symbol doc-symbol-toc doc-symbol-attribute"></code>&nbsp;device
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<code class="doc-symbol doc-symbol-toc doc-symbol-attribute"></code>&nbsp;ndim
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;numel
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;element_size
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;nbytes
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;is_floating_point
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;size
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Data Access
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;data
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;item
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;schedule_with_vars
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;schedule
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<code class="doc-symbol doc-symbol-toc doc-symbol-method"></code>&nbsp;realize
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<article class="md-content__inner md-typeset">
<a href="https://github.com/tinygrad/tinygrad/edit/master/docs/tensor/properties.md" title="Edit this page" class="md-content__button md-icon" rel="edit">
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<h1>Properties</h1>
<h2 id="basic">Basic<a class="headerlink" href="#basic" title="Permanent link">¤</a></h2>
<div class="doc doc-object doc-attribute">
<h3 id="tinygrad.Tensor.shape" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-attribute"></code> <span class="doc doc-object-name doc-attribute-name">shape</span>
<span class="doc doc-labels">
<small class="doc doc-label doc-label-property"><code>property</code></small>
</span>
<a href="#tinygrad.Tensor.shape" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="n">shape</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><span title="tinygrad.uop.ops.sint">sint</span></span><span class="p">,</span> <span class="o">...</span><span class="p">]</span>
</code></pre></div>
<div class="doc doc-contents first">
</div>
</div>
<div class="doc doc-object doc-attribute">
<h3 id="tinygrad.Tensor.dtype" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-attribute"></code> <span class="doc doc-object-name doc-attribute-name">dtype</span>
<span class="doc doc-labels">
<small class="doc doc-label doc-label-property"><code>property</code></small>
</span>
<a href="#tinygrad.Tensor.dtype" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="n">dtype</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;DType&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-dataclass&quot;&gt;&lt;code&gt;dataclass&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.dtype.DType&lt;/code&gt;)" href="../../dtypes/#tinygrad.dtype.DType">DType</a></span>
</code></pre></div>
<div class="doc doc-contents first">
</div>
</div>
<div class="doc doc-object doc-attribute">
<h3 id="tinygrad.Tensor.device" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-attribute"></code> <span class="doc doc-object-name doc-attribute-name">device</span>
<span class="doc doc-labels">
<small class="doc doc-label doc-label-property"><code>property</code></small>
</span>
<a href="#tinygrad.Tensor.device" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="n">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="o">...</span><span class="p">]</span>
</code></pre></div>
<div class="doc doc-contents first">
</div>
</div>
<div class="doc doc-object doc-attribute">
<h3 id="tinygrad.Tensor.ndim" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-attribute"></code> <span class="doc doc-object-name doc-attribute-name">ndim</span>
<span class="doc doc-labels">
<small class="doc doc-label doc-label-property"><code>property</code></small>
</span>
<a href="#tinygrad.Tensor.ndim" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="n">ndim</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/functions.html#int">int</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the number of dimensions in the tensor.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">ndim</span><span class="p">)</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">2</span>
</code></pre></div>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.numel" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">numel</span>
<a href="#tinygrad.Tensor.numel" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">numel</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><span title="tinygrad.mixin.movement.sint">sint</span></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the total number of elements in the tensor.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([[[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]],</span> <span class="p">[[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">]]])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">numel</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">8</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/mixin/movement.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">40</span>
<span class="normal">41</span>
<span class="normal">42</span>
<span class="normal">43</span>
<span class="normal">44</span>
<span class="normal">45</span>
<span class="normal">46</span>
<span class="normal">47</span>
<span class="normal">48</span>
<span class="normal">49</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">numel</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">sint</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the total number of elements in the tensor.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])</span>
<span class="sd"> print(t.numel())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">prod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.element_size" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">element_size</span>
<a href="#tinygrad.Tensor.element_size" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">element_size</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the size in bytes of an individual element in the tensor.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">5</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="o">.</span><span class="n">int16</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">element_size</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">2</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">3701</span>
<span class="normal">3702</span>
<span class="normal">3703</span>
<span class="normal">3704</span>
<span class="normal">3705</span>
<span class="normal">3706</span>
<span class="normal">3707</span>
<span class="normal">3708</span>
<span class="normal">3709</span>
<span class="normal">3710</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">element_size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the size in bytes of an individual element in the tensor.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([5], dtype=dtypes.int16)</span>
<span class="sd"> print(t.element_size())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">itemsize</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.nbytes" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">nbytes</span>
<a href="#tinygrad.Tensor.nbytes" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">nbytes</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the total number of bytes of all elements in the tensor.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">nbytes</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">8</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">3712</span>
<span class="normal">3713</span>
<span class="normal">3714</span>
<span class="normal">3715</span>
<span class="normal">3716</span>
<span class="normal">3717</span>
<span class="normal">3718</span>
<span class="normal">3719</span>
<span class="normal">3720</span>
<span class="normal">3721</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">nbytes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the total number of bytes of all elements in the tensor.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([8, 9], dtype=dtypes.float)</span>
<span class="sd"> print(t.nbytes())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">element_size</span><span class="p">()</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.is_floating_point" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">is_floating_point</span>
<a href="#tinygrad.Tensor.is_floating_point" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">is_floating_point</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;bool&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.bool&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.bool">bool</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns <code class="language-python highlight"><span class="kc">True</span></code> if the tensor contains floating point types, i.e. is one of <code class="language-python highlight"><span class="n">dtypes</span><span class="o">.</span><span class="n">float64</span></code>, <code class="language-python highlight"><span class="n">dtypes</span><span class="o">.</span><span class="n">float32</span></code>,
<code class="language-python highlight"><span class="n">dtypes</span><span class="o">.</span><span class="n">float16</span></code>, <code class="language-python highlight"><span class="n">dtypes</span><span class="o">.</span><span class="n">bfloat16</span></code>.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">is_floating_point</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="kc">True</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">3723</span>
<span class="normal">3724</span>
<span class="normal">3725</span>
<span class="normal">3726</span>
<span class="normal">3727</span>
<span class="normal">3728</span>
<span class="normal">3729</span>
<span class="normal">3730</span>
<span class="normal">3731</span>
<span class="normal">3732</span>
<span class="normal">3733</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">is_floating_point</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns `True` if the tensor contains floating point types, i.e. is one of `dtypes.float64`, `dtypes.float32`,</span>
<span class="sd"> `dtypes.float16`, `dtypes.bfloat16`.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([8, 9], dtype=dtypes.float32)</span>
<span class="sd"> print(t.is_floating_point())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">is_float</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.size" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">size</span>
<a href="#tinygrad.Tensor.size" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">size</span><span class="p">(</span><span class="n">dim</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><span title="tinygrad.uop.ops.sint">sint</span></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><span title="tinygrad.uop.ops.sint">sint</span></span><span class="p">,</span> <span class="o">...</span><span class="p">]</span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the size of the tensor. If <code class="language-python highlight"><span class="n">dim</span></code> is specified, return the length along dimension <code class="language-python highlight"><span class="n">dim</span></code>. Otherwise return the shape of the tensor.</p>
<p><div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">]])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">size</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">3</span>
</code></pre></div></p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">3735</span>
<span class="normal">3736</span>
<span class="normal">3737</span>
<span class="normal">3738</span>
<span class="normal">3739</span>
<span class="normal">3740</span>
<span class="normal">3741</span>
<span class="normal">3742</span>
<span class="normal">3743</span>
<span class="normal">3744</span>
<span class="normal">3745</span>
<span class="normal">3746</span>
<span class="normal">3747</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">size</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dim</span><span class="p">:</span><span class="nb">int</span><span class="o">|</span><span class="kc">None</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">sint</span><span class="o">|</span><span class="nb">tuple</span><span class="p">[</span><span class="n">sint</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the size of the tensor. If `dim` is specified, return the length along dimension `dim`. Otherwise return the shape of the tensor.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([[4, 5, 6], [7, 8, 9]])</span>
<span class="sd"> print(t.size())</span>
<span class="sd"> ```</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> print(t.size(dim=1))</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="k">if</span> <span class="n">dim</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">dim</span><span class="p">]</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div><h2 id="data-access">Data Access<a class="headerlink" href="#data-access" title="Permanent link">¤</a></h2>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.data" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">data</span>
<a href="#tinygrad.Tensor.data" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#memoryview">memoryview</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the data of this tensor as a memoryview.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">frombuffer</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">data</span><span class="p">(),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">))</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="p">[</span><span class="mi">1</span> <span class="mi">2</span> <span class="mi">3</span> <span class="mi">4</span><span class="p">]</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">304</span>
<span class="normal">305</span>
<span class="normal">306</span>
<span class="normal">307</span>
<span class="normal">308</span>
<span class="normal">309</span>
<span class="normal">310</span>
<span class="normal">311</span>
<span class="normal">312</span>
<span class="normal">313</span>
<span class="normal">314</span>
<span class="normal">315</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">data</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">memoryview</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the data of this tensor as a memoryview.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([1, 2, 3, 4])</span>
<span class="sd"> print(np.frombuffer(t.data(), dtype=np.int32))</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="mi">0</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">:</span> <span class="k">return</span> <span class="nb">memoryview</span><span class="p">(</span><span class="nb">bytearray</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">base</span><span class="o">.</span><span class="n">fmt</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">all_int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="sa">f</span><span class="s2">&quot;no data if shape is symbolic, </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="si">=}</span><span class="s2">&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_buffer</span><span class="p">()</span><span class="o">.</span><span class="n">as_typed_buffer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.item" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">item</span>
<a href="#tinygrad.Tensor.item" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">item</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-attribute&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-attribute-name&quot;&gt;ConstType&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-module-attribute&quot;&gt;&lt;code&gt;module-attribute&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.dtype.ConstType&lt;/code&gt;)" href="../../dtypes/#tinygrad.dtype.ConstType">ConstType</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the value of this tensor as a standard Python number.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="mi">42</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">42</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">317</span>
<span class="normal">318</span>
<span class="normal">319</span>
<span class="normal">320</span>
<span class="normal">321</span>
<span class="normal">322</span>
<span class="normal">323</span>
<span class="normal">324</span>
<span class="normal">325</span>
<span class="normal">326</span>
<span class="normal">327</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">item</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ConstType</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the value of this tensor as a standard Python number.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor(42)</span>
<span class="sd"> print(t.item())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">==</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;must have one element for item&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">()[(</span><span class="mi">0</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)]</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.tolist" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">tolist</span>
<a href="#tinygrad.Tensor.tolist" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">tolist</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-external" title="&lt;code&gt;typing.Sequence&lt;/code&gt;" href="https://docs.python.org/3/library/typing.html#typing.Sequence">Sequence</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-attribute&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-attribute-name&quot;&gt;ConstType&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-module-attribute&quot;&gt;&lt;code&gt;module-attribute&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.dtype.ConstType&lt;/code&gt;)" href="../../dtypes/#tinygrad.dtype.ConstType">ConstType</a></span><span class="p">]</span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-attribute&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-attribute-name&quot;&gt;ConstType&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-module-attribute&quot;&gt;&lt;code&gt;module-attribute&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.dtype.ConstType&lt;/code&gt;)" href="../../dtypes/#tinygrad.dtype.ConstType">ConstType</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the value of this tensor as a nested list.
Returns single value for const tensor.</p>
<p><div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="mi">5</span>
</code></pre></div></p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">331</span>
<span class="normal">332</span>
<span class="normal">333</span>
<span class="normal">334</span>
<span class="normal">335</span>
<span class="normal">336</span>
<span class="normal">337</span>
<span class="normal">338</span>
<span class="normal">339</span>
<span class="normal">340</span>
<span class="normal">341</span>
<span class="normal">342</span>
<span class="normal">343</span>
<span class="normal">344</span>
<span class="normal">345</span>
<span class="normal">346</span>
<span class="normal">347</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">tolist</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">ConstType</span><span class="p">]</span><span class="o">|</span><span class="n">ConstType</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the value of this tensor as a nested list.</span>
<span class="sd"> Returns single value for const tensor.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([1, 2, 3, 4])</span>
<span class="sd"> print(t.tolist())</span>
<span class="sd"> ```</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor(5)</span>
<span class="sd"> print(t.tolist())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># TODO: remove half once minimum python supports it</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">in</span> <span class="p">(</span><span class="n">dtypes</span><span class="o">.</span><span class="n">half</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">bfloat16</span><span class="p">,</span> <span class="o">*</span><span class="n">dtypes</span><span class="o">.</span><span class="n">fp8s</span><span class="p">):</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="n">dtypes</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.numpy" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">numpy</span>
<a href="#tinygrad.Tensor.numpy" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">numpy</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="s1">&#39;numpy.ndarray&#39;</span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns the value of this tensor as a <code class="language-python highlight"><span class="n">numpy</span><span class="o">.</span><span class="n">ndarray</span></code>.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">repr</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">numpy</span><span class="p">()))</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">int32</span><span class="p">)</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">349</span>
<span class="normal">350</span>
<span class="normal">351</span>
<span class="normal">352</span>
<span class="normal">353</span>
<span class="normal">354</span>
<span class="normal">355</span>
<span class="normal">356</span>
<span class="normal">357</span>
<span class="normal">358</span>
<span class="normal">359</span>
<span class="normal">360</span>
<span class="normal">361</span>
<span class="normal">362</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">numpy</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s1">&#39;numpy.ndarray&#39;</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the value of this tensor as a `numpy.ndarray`.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([1, 2, 3, 4])</span>
<span class="sd"> print(repr(t.numpy()))</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">assert</span> <span class="n">all_int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">),</span> <span class="sa">f</span><span class="s2">&quot;no data if shape is symbolic, </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="si">=}</span><span class="s2">&quot;</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">base</span> <span class="ow">in</span> <span class="p">{</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">bfloat16</span><span class="p">,</span> <span class="o">*</span><span class="n">dtypes</span><span class="o">.</span><span class="n">fp8s</span> <span class="p">}:</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">float</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
<span class="k">if</span> <span class="mi">0</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">:</span> <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">_to_np_dtype</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">base</span><span class="p">))</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_buffer</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div><h2 id="tinygrad-ops">tinygrad ops<a class="headerlink" href="#tinygrad-ops" title="Permanent link">¤</a></h2>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.schedule_with_vars" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">schedule_with_vars</span>
<a href="#tinygrad.Tensor.schedule_with_vars" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">schedule_with_vars</span><span class="p">(</span>
<span class="o">*</span><span class="n">lst</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#list">list</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;ExecItem&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-dataclass&quot;&gt;&lt;code&gt;dataclass&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.engine.schedule.ExecItem&lt;/code&gt;)" href="../../developer/developer/#tinygrad.engine.schedule.ExecItem">ExecItem</a></span><span class="p">],</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#dict">dict</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span><span class="p">]]</span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Creates the schedule needed to realize these Tensor(s), with Variables.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>A Tensor can only be scheduled once.</p>
</div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">240</span>
<span class="normal">241</span>
<span class="normal">242</span>
<span class="normal">243</span>
<span class="normal">244</span>
<span class="normal">245</span>
<span class="normal">246</span>
<span class="normal">247</span>
<span class="normal">248</span>
<span class="normal">249</span>
<span class="normal">250</span>
<span class="normal">251</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">schedule_with_vars</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">lst</span><span class="p">:</span><span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">ExecItem</span><span class="p">],</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]]:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates the schedule needed to realize these Tensor(s), with Variables.</span>
<span class="sd"> NOTE: A Tensor can only be scheduled once.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">big_sink</span> <span class="o">=</span> <span class="n">UOp</span><span class="o">.</span><span class="n">sink</span><span class="p">(</span><span class="o">*</span><span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">uop</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="bp">self</span><span class="p">,)</span><span class="o">+</span><span class="n">lst</span><span class="p">])</span>
<span class="c1"># this is where the schedule cache should go</span>
<span class="n">becomes_map</span><span class="p">,</span> <span class="n">schedule</span><span class="p">,</span> <span class="n">var_vals</span> <span class="o">=</span> <span class="n">complete_create_schedule_with_vars</span><span class="p">(</span><span class="n">big_sink</span><span class="p">)</span>
<span class="n">_apply_map_to_tensors</span><span class="p">(</span><span class="n">becomes_map</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Apply Schedule Map&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">schedule</span><span class="p">,</span> <span class="n">var_vals</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.schedule" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">schedule</span>
<a href="#tinygrad.Tensor.schedule" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">schedule</span><span class="p">(</span><span class="o">*</span><span class="n">lst</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#list">list</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;ExecItem&lt;/span&gt;
&lt;span class=&quot;doc doc-labels&quot;&gt;
&lt;small class=&quot;doc doc-label doc-label-dataclass&quot;&gt;&lt;code&gt;dataclass&lt;/code&gt;&lt;/small&gt;
&lt;/span&gt; (&lt;code&gt;tinygrad.engine.schedule.ExecItem&lt;/code&gt;)" href="../../developer/developer/#tinygrad.engine.schedule.ExecItem">ExecItem</a></span><span class="p">]</span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Creates the schedule needed to realize these Tensor(s).</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">253</span>
<span class="normal">254</span>
<span class="normal">255</span>
<span class="normal">256</span>
<span class="normal">257</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">schedule</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">lst</span><span class="p">:</span><span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">ExecItem</span><span class="p">]:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;Creates the schedule needed to realize these Tensor(s).&quot;&quot;&quot;</span>
<span class="n">schedule</span><span class="p">,</span> <span class="n">var_vals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">schedule_with_vars</span><span class="p">(</span><span class="o">*</span><span class="n">lst</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">var_vals</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span>
<span class="k">return</span> <span class="n">schedule</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.realize" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">realize</span>
<a href="#tinygrad.Tensor.realize" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">realize</span><span class="p">(</span><span class="o">*</span><span class="n">lst</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">,</span> <span class="n">do_update_stats</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Triggers the computation needed to create these Tensor(s).</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">259</span>
<span class="normal">260</span>
<span class="normal">261</span>
<span class="normal">262</span>
<span class="normal">263</span>
<span class="normal">264</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="nd">@disable_gc</span><span class="p">()</span>
<span class="k">def</span><span class="w"> </span><span class="nf">realize</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">lst</span><span class="p">:</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">do_update_stats</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;Triggers the computation needed to create these Tensor(s).&quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">to_realize</span><span class="o">:=</span><span class="p">[</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="p">(</span><span class="bp">self</span><span class="p">,)</span><span class="o">+</span><span class="n">lst</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">x</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">is_contiguous</span><span class="p">()]):</span>
<span class="n">run_schedule</span><span class="p">(</span><span class="o">*</span><span class="n">Tensor</span><span class="o">.</span><span class="n">schedule_with_vars</span><span class="p">(</span><span class="o">*</span><span class="n">to_realize</span><span class="p">),</span> <span class="n">do_update_stats</span><span class="o">=</span><span class="n">do_update_stats</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.replace" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">replace</span>
<a href="#tinygrad.Tensor.replace" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">replace</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">,</span> <span class="n">allow_shape_mismatch</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Replaces the data of this tensor with the data of another tensor. Only the shape of the tensors must match.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">266</span>
<span class="normal">267</span>
<span class="normal">268</span>
<span class="normal">269</span>
<span class="normal">270</span>
<span class="normal">271</span>
<span class="normal">272</span>
<span class="normal">273</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">replace</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">allow_shape_mismatch</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Replaces the data of this tensor with the data of another tensor. Only the shape of the tensors must match.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># used for replacing a Tensor with a new version of it (potentially with a different device and dtype)</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span> <span class="ow">or</span> <span class="n">allow_shape_mismatch</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;replace shape mismatch </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">uop</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">uop</span>
<span class="k">return</span> <span class="bp">self</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.assign" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">assign</span>
<a href="#tinygrad.Tensor.assign" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">assign</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">275</span>
<span class="normal">276</span>
<span class="normal">277</span>
<span class="normal">278</span>
<span class="normal">279</span>
<span class="normal">280</span>
<span class="normal">281</span>
<span class="normal">282</span>
<span class="normal">283</span>
<span class="normal">284</span>
<span class="normal">285</span>
<span class="normal">286</span>
<span class="normal">287</span>
<span class="normal">288</span>
<span class="normal">289</span>
<span class="normal">290</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">assign</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="c1"># TODO: this is a hack for writing to DISK. remove with working assign</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">&quot;DISK&quot;</span><span class="p">):</span>
<span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="vm">__class__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">Tensor</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="s2">&quot;CPU&quot;</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_buffer</span><span class="p">()</span><span class="o">.</span><span class="n">copyin</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">_data</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span>
<span class="k">if</span> <span class="n">x</span><span class="o">.</span><span class="vm">__class__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">Tensor</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">uop</span> <span class="ow">is</span> <span class="n">x</span><span class="o">.</span><span class="n">uop</span><span class="p">:</span> <span class="k">return</span> <span class="bp">self</span> <span class="c1"># a self assign is a NOOP</span>
<span class="c1"># NOTE: we allow cross device assign</span>
<span class="c1"># broadcast x</span>
<span class="k">if</span> <span class="n">least_upper_dtype</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span> <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">_broadcast_to</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;assign shape mismatch </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="n">x</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;assign device mismatch </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="n">x</span><span class="o">.</span><span class="n">device</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;assign dtype mismatch </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="k">assert</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">axis</span> <span class="o">==</span> <span class="n">x</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">axis</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;multi assign axis mismatch </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">axis</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="n">x</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">axis</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_apply_uop</span><span class="p">(</span><span class="n">UOp</span><span class="o">.</span><span class="n">assign</span><span class="p">,</span> <span class="n">x</span><span class="p">))</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.detach" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">detach</span>
<a href="#tinygrad.Tensor.detach" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">detach</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns a new tensor with the same data as this tensor, but detached from the autograd graph.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">292</span>
<span class="normal">293</span>
<span class="normal">294</span>
<span class="normal">295</span>
<span class="normal">296</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">detach</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns a new tensor with the same data as this tensor, but detached from the autograd graph.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">Tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">detach</span><span class="p">(),</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.clone" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">clone</span>
<a href="#tinygrad.Tensor.clone" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">clone</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Creates a clone of this tensor allocating a separate buffer for the data.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">364</span>
<span class="normal">365</span>
<span class="normal">366</span>
<span class="normal">367</span>
<span class="normal">368</span>
<span class="normal">369</span>
<span class="normal">370</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">clone</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates a clone of this tensor allocating a separate buffer for the data.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">ret</span> <span class="o">=</span> <span class="n">Tensor</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">ret</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">clone</span><span class="p">()</span>
<span class="k">return</span> <span class="n">ret</span><span class="o">.</span><span class="n">assign</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.to" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">to</span>
<a href="#tinygrad.Tensor.to" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">to</span><span class="p">(</span><span class="n">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="o">...</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="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Moves the tensor to the given device.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">372</span>
<span class="normal">373</span>
<span class="normal">374</span>
<span class="normal">375</span>
<span class="normal">376</span>
<span class="normal">377</span>
<span class="normal">378</span>
<span class="normal">379</span>
<span class="normal">380</span>
<span class="normal">381</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">to</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span><span class="nb">str</span><span class="o">|</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="o">...</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="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Moves the tensor to the given device.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">device</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">canonicalize_device</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">device</span><span class="p">)</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="p">(</span><span class="nb">tuple</span><span class="p">,</span> <span class="nb">list</span><span class="p">))</span> <span class="k">else</span> <span class="n">canonicalize_device</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">if</span> <span class="n">device</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">:</span> <span class="k">return</span> <span class="bp">self</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">shard</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="n">ret</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="n">ret</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.to_" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">to_</span>
<a href="#tinygrad.Tensor.to_" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">to_</span><span class="p">(</span><span class="n">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span> <span class="o">|</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="o">...</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="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Moves the tensor to the given device in place.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">383</span>
<span class="normal">384</span>
<span class="normal">385</span>
<span class="normal">386</span>
<span class="normal">387</span>
<span class="normal">388</span>
<span class="normal">389</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">to_</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span><span class="nb">str</span><span class="o">|</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="o">...</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="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Moves the tensor to the given device in place.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">real</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">real</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="n">real</span><span class="o">.</span><span class="n">grad</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="n">real</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.shard" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">shard</span>
<a href="#tinygrad.Tensor.shard" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">shard</span><span class="p">(</span>
<span class="n">devices</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">axis</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Shards the tensor across the given devices. Optionally specify which axis to shard on.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">shard</span><span class="p">((</span><span class="n">t</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">t</span><span class="o">.</span><span class="n">device</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">uop</span><span class="p">)</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">MULTI</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">SHRINK</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">COPY</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">RESHAPE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">BUFFER</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">float</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">UNIQUE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">void</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="mi">1432</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">()),</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">DEVICE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">void</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="s1">&#39;CPU&#39;</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">()),)),</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">VCONST</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">vec</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="n">arg</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">src</span><span class="o">=</span><span class="p">()),)),</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">DEVICE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">void</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;CPU&#39;</span><span class="p">,</span> <span class="s1">&#39;CPU&#39;</span><span class="p">),</span> <span class="n">src</span><span class="o">=</span><span class="p">()),)),</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">VECTORIZE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">vec</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">CONST</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">()),</span>
<span class="n">x10</span><span class="o">:=</span><span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">MUL</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">DEFINE_VAR</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;_device_num&#39;</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">src</span><span class="o">=</span><span class="p">()),</span>
<span class="n">x12</span><span class="o">:=</span><span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">CONST</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">()),)),)),</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">VECTORIZE</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">vec</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">x12</span><span class="p">,</span>
<span class="n">UOp</span><span class="p">(</span><span class="n">Ops</span><span class="o">.</span><span class="n">ADD</span><span class="p">,</span> <span class="n">dtypes</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="p">(</span>
<span class="n">x10</span><span class="p">,</span>
<span class="n">x12</span><span class="p">,)),)),)),))</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">391</span>
<span class="normal">392</span>
<span class="normal">393</span>
<span class="normal">394</span>
<span class="normal">395</span>
<span class="normal">396</span>
<span class="normal">397</span>
<span class="normal">398</span>
<span class="normal">399</span>
<span class="normal">400</span>
<span class="normal">401</span>
<span class="normal">402</span>
<span class="normal">403</span>
<span class="normal">404</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">shard</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">devices</span><span class="p">:</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">axis</span><span class="p">:</span><span class="nb">int</span><span class="o">|</span><span class="kc">None</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Shards the tensor across the given devices. Optionally specify which axis to shard on.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor.empty(2, 4)</span>
<span class="sd"> print(t.shard((t.device, t.device), axis=1).uop)</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span> <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;can&#39;t shard a MultiLazyBuffer&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">devices</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">devices</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">devices</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">canonicalize_device</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">devices</span><span class="p">)</span>
<span class="n">mlb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">shard</span><span class="p">(</span><span class="n">devices</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_resolve_dim</span><span class="p">(</span><span class="n">axis</span><span class="p">))</span> <span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">copy_to_device</span><span class="p">(</span><span class="n">devices</span><span class="p">)</span>
<span class="k">return</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">mlb</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">devices</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.shard_" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">shard_</span>
<a href="#tinygrad.Tensor.shard_" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">shard_</span><span class="p">(</span>
<span class="n">devices</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#tuple">tuple</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">axis</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-method&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-function-name&quot;&gt;int&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor.int&lt;/code&gt;)" href="../elementwise/#tinygrad.Tensor.int">int</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Shards the tensor across the given devices in place.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">406</span>
<span class="normal">407</span>
<span class="normal">408</span>
<span class="normal">409</span>
<span class="normal">410</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">shard_</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">devices</span><span class="p">:</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">axis</span><span class="p">:</span><span class="nb">int</span><span class="o">|</span><span class="kc">None</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Shards the tensor across the given devices in place.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shard</span><span class="p">(</span><span class="n">devices</span><span class="p">,</span> <span class="n">axis</span><span class="p">))</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.contiguous" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">contiguous</span>
<a href="#tinygrad.Tensor.contiguous" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">contiguous</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="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Returns a contiguous tensor.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">2736</span>
<span class="normal">2737</span>
<span class="normal">2738</span>
<span class="normal">2739</span>
<span class="normal">2740</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">contiguous</span><span class="p">(</span><span class="bp">self</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="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns a contiguous tensor.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_uop</span><span class="p">(</span><span class="n">UOp</span><span class="o">.</span><span class="n">contiguous</span><span class="p">,</span> <span class="n">extra_args</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>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.contiguous_backward" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">contiguous_backward</span>
<a href="#tinygrad.Tensor.contiguous_backward" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">contiguous_backward</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Inserts a contiguous operation in the backward pass.</p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">2742</span>
<span class="normal">2743</span>
<span class="normal">2744</span>
<span class="normal">2745</span>
<span class="normal">2746</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">contiguous_backward</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Inserts a contiguous operation in the backward pass.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_uop</span><span class="p">(</span><span class="n">UOp</span><span class="o">.</span><span class="n">contiguous_backward</span><span class="p">)</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div><h2 id="gradient">Gradient<a class="headerlink" href="#gradient" title="Permanent link">¤</a></h2>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.gradient" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">gradient</span>
<a href="#tinygrad.Tensor.gradient" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">gradient</span><span class="p">(</span>
<span class="o">*</span><span class="n">targets</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">,</span>
<span class="n">gradient</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">materialize_grads</span><span class="o">=</span><span class="kc">False</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#list">list</a></span><span class="p">[</span><span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span><span class="p">]</span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Computes the gradient of the targets with respect to self.</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="o">.</span><span class="n">eye</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([[</span><span class="mf">2.0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="o">-</span><span class="mf">2.0</span><span class="p">]])</span>
<span class="n">z</span> <span class="o">=</span> <span class="n">y</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
<span class="n">dx</span><span class="p">,</span> <span class="n">dy</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">gradient</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">dx</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span> <span class="c1"># dz/dx</span>
<span class="nb">print</span><span class="p">(</span><span class="n">dy</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span> <span class="c1"># dz/dy</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="p">[[</span><span class="mf">2.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">],</span> <span class="p">[</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">],</span> <span class="p">[</span><span class="o">-</span><span class="mf">2.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.0</span><span class="p">,</span> <span class="o">-</span><span class="mf">2.0</span><span class="p">]]</span>
<span class="p">[[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">]]</span>
</code></pre></div>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"> 986</span>
<span class="normal"> 987</span>
<span class="normal"> 988</span>
<span class="normal"> 989</span>
<span class="normal"> 990</span>
<span class="normal"> 991</span>
<span class="normal"> 992</span>
<span class="normal"> 993</span>
<span class="normal"> 994</span>
<span class="normal"> 995</span>
<span class="normal"> 996</span>
<span class="normal"> 997</span>
<span class="normal"> 998</span>
<span class="normal"> 999</span>
<span class="normal">1000</span>
<span class="normal">1001</span>
<span class="normal">1002</span>
<span class="normal">1003</span>
<span class="normal">1004</span>
<span class="normal">1005</span>
<span class="normal">1006</span>
<span class="normal">1007</span>
<span class="normal">1008</span>
<span class="normal">1009</span>
<span class="normal">1010</span>
<span class="normal">1011</span>
<span class="normal">1012</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">gradient</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">targets</span><span class="p">:</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">gradient</span><span class="p">:</span><span class="n">Tensor</span><span class="o">|</span><span class="kc">None</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">materialize_grads</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Computes the gradient of the targets with respect to self.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> x = Tensor.eye(3)</span>
<span class="sd"> y = Tensor([[2.0,0,-2.0]])</span>
<span class="sd"> z = y.matmul(x).sum()</span>
<span class="sd"> dx, dy = z.gradient(x, y)</span>
<span class="sd"> print(dx.tolist()) # dz/dx</span>
<span class="sd"> print(dy.tolist()) # dz/dy</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">assert</span> <span class="n">gradient</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="nb">tuple</span><span class="p">(),</span> <span class="s2">&quot;when no gradient is provided, backward must be called on a scalar tensor&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">is_floating_point</span><span class="p">()</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">is_floating_point</span><span class="p">()</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">targets</span><span class="p">)):</span> <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;only float Tensors have gradient&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">gradient</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">gradient</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">target_uops</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">uop</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">targets</span><span class="p">]</span>
<span class="n">grads</span> <span class="o">=</span> <span class="n">compute_gradient</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="p">,</span> <span class="n">gradient</span><span class="o">.</span><span class="n">uop</span><span class="p">,</span> <span class="nb">set</span><span class="p">(</span><span class="n">target_uops</span><span class="p">))</span>
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">target_uops</span><span class="p">:</span>
<span class="k">if</span> <span class="p">(</span><span class="n">y</span><span class="o">:=</span><span class="n">grads</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">x</span><span class="p">))</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">if</span> <span class="n">materialize_grads</span><span class="p">:</span> <span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">const_like</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span> <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">x</span><span class="si">}</span><span class="se">\n\n</span><span class="s2">not found in</span><span class="se">\n\n</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
<span class="c1"># create returned Tensors</span>
<span class="k">return</span> <span class="p">[</span><span class="n">Tensor</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">t</span><span class="o">.</span><span class="n">device</span><span class="p">)</span> <span class="k">for</span> <span class="n">t</span><span class="p">,</span><span class="n">u</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">ret</span><span class="p">)]</span>
</code></pre></div></td></tr></table></div>
</details>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="tinygrad.Tensor.backward" class="doc doc-heading">
<code class="doc-symbol doc-symbol-heading doc-symbol-method"></code> <span class="doc doc-object-name doc-function-name">backward</span>
<a href="#tinygrad.Tensor.backward" class="headerlink" title="Permanent link">¤</a></h3>
<div class="language-python doc-signature highlight"><pre><span></span><code><span class="nf">backward</span><span class="p">(</span><span class="n">gradient</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n"><a class="autorefs autorefs-internal" title="&lt;code class=&quot;doc-symbol doc-symbol-heading doc-symbol-class&quot;&gt;&lt;/code&gt; &lt;span class=&quot;doc doc-object-name doc-class-name&quot;&gt;Tensor&lt;/span&gt; (&lt;code&gt;tinygrad.tensor.Tensor&lt;/code&gt;)" href="../#tinygrad.Tensor">Tensor</a></span>
</code></pre></div>
<div class="doc doc-contents first">
<p>Propagates the gradient of a tensor backwards through the computation graph.
If the 'gradient' argument is not provided, the tensor must be a scalar, and the gradient is implicitly set to 1.0.
<div class="language-python highlight"><pre><span></span><code><span class="n">t</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">([</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">,</span> <span class="mf">3.0</span><span class="p">,</span> <span class="mf">4.0</span><span class="p">],</span> <span class="n">requires_grad</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">t</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span>
</code></pre></div>
<div class="language-python highlight"><pre><span></span><code><span class="p">[</span><span class="mf">1.</span> <span class="mf">1.</span> <span class="mf">1.</span> <span class="mf">1.</span><span class="p">]</span>
</code></pre></div></p>
<details class="mkdocstrings-source">
<summary>Source code in <code>tinygrad/tensor.py</code></summary>
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">1014</span>
<span class="normal">1015</span>
<span class="normal">1016</span>
<span class="normal">1017</span>
<span class="normal">1018</span>
<span class="normal">1019</span>
<span class="normal">1020</span>
<span class="normal">1021</span>
<span class="normal">1022</span>
<span class="normal">1023</span>
<span class="normal">1024</span>
<span class="normal">1025</span>
<span class="normal">1026</span>
<span class="normal">1027</span>
<span class="normal">1028</span>
<span class="normal">1029</span>
<span class="normal">1030</span>
<span class="normal">1031</span>
<span class="normal">1032</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gradient</span><span class="p">:</span><span class="n">Tensor</span><span class="o">|</span><span class="kc">None</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tensor</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Propagates the gradient of a tensor backwards through the computation graph.</span>
<span class="sd"> If the &#39;gradient&#39; argument is not provided, the tensor must be a scalar, and the gradient is implicitly set to 1.0.</span>
<span class="sd"> ```python exec=&quot;true&quot; source=&quot;above&quot; session=&quot;tensor&quot; result=&quot;python&quot;</span>
<span class="sd"> t = Tensor([1.0, 2.0, 3.0, 4.0], requires_grad=True)</span>
<span class="sd"> t.sum().backward()</span>
<span class="sd"> print(t.grad.numpy())</span>
<span class="sd"> ```</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">all_uops</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">uop</span><span class="o">.</span><span class="n">toposort</span><span class="p">()</span>
<span class="n">tensors_need_grad</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">t</span> <span class="k">for</span> <span class="n">tref</span> <span class="ow">in</span> <span class="n">all_tensors</span> <span class="k">if</span> <span class="p">(</span><span class="n">t</span><span class="o">:=</span><span class="n">tref</span><span class="p">())</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> \
<span class="n">t</span><span class="o">.</span><span class="n">uop</span> <span class="ow">in</span> <span class="n">all_uops</span> <span class="ow">and</span> <span class="n">t</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">]</span>
<span class="c1"># clear contexts</span>
<span class="k">for</span> <span class="n">t</span><span class="p">,</span><span class="n">g</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">tensors_need_grad</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">gradient</span><span class="p">(</span><span class="o">*</span><span class="n">tensors_need_grad</span><span class="p">,</span> <span class="n">gradient</span><span class="o">=</span><span class="n">gradient</span><span class="p">,</span> <span class="n">materialize_grads</span><span class="o">=</span><span class="kc">True</span><span class="p">)):</span>
<span class="k">assert</span> <span class="n">g</span><span class="o">.</span><span class="n">shape</span> <span class="o">==</span> <span class="n">t</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;grad shape must match tensor shape, </span><span class="si">{</span><span class="n">g</span><span class="o">.</span><span class="n">shape</span><span class="si">!r}</span><span class="s2"> != </span><span class="si">{</span><span class="n">t</span><span class="o">.</span><span class="n">shape</span><span class="si">!r}</span><span class="s2">&quot;</span>
<span class="k">if</span> <span class="n">t</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">t</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="n">g</span>
<span class="k">else</span><span class="p">:</span> <span class="n">t</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">assign</span><span class="p">(</span><span class="n">t</span><span class="o">.</span><span class="n">grad</span> <span class="o">+</span> <span class="n">g</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span>
</code></pre></div></td></tr></table></div>
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