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<h1><code class="doc-symbol doc-symbol-nav doc-symbol-module"></code> Utils</h1>
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<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">image_to_tensor</span>
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<a href="#refiners.fluxion.utils.image_to_tensor" class="headerlink" title="Permanent link">¶</a></h2>
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">image_to_tensor</span><span class="p">(</span>
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</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">image</span><span class="p">:</span> <span class="n"><span title="PIL.Image.Image">Image</span></span><span class="p">,</span>
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</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.device" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.device">device</a></span> <span class="o">|</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="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a> <span class="n">dtype</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.dtype" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.dtype">dtype</a></span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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</span><span id="__span-0-5"><a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a><span class="p">)</span> <span class="o">-></span> <span class="n"><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span>
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</span></code></pre></div>
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<div class="doc doc-contents ">
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<p>Convert a PIL Image to a Tensor.</p>
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<p><span class="doc-section-title">Parameters:</span></p>
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<table>
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<thead>
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<tr>
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<th>Name</th>
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<th>Type</th>
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<th>Description</th>
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<th>Default</th>
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</thead>
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<td>
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<code>image</code>
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</td>
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<td>
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<code><span title="PIL.Image.Image">Image</span></code>
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</td>
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<td>
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<div class="doc-md-description">
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<p>The image to convert.</p>
|
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</td>
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<td>
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<em>required</em>
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</td>
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<tr class="doc-section-item">
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<td>
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<code>device</code>
|
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</td>
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<td>
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<code><a class="autorefs autorefs-external" title="torch.device" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.device">device</a> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a> | None</code>
|
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</td>
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<td>
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<div class="doc-md-description">
|
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<p>The device to use for the tensor.</p>
|
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</div>
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</td>
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<td>
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<code>None</code>
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</td>
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</tr>
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<tr class="doc-section-item">
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<td>
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<code>dtype</code>
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</td>
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<td>
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<code><a class="autorefs autorefs-external" title="torch.dtype" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.dtype">dtype</a> | None</code>
|
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</td>
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<td>
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<div class="doc-md-description">
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<p>The dtype to use for the tensor.</p>
|
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</div>
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</td>
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<td>
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<code>None</code>
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</td>
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</tr>
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</tbody>
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</table>
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<p><span class="doc-section-title">Returns:</span></p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
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<tbody>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></code>
|
|
</td>
|
|
<td>
|
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<div class="doc-md-description">
|
|
<p>The converted tensor.</p>
|
|
</div>
|
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</td>
|
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</tr>
|
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</tbody>
|
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</table>
|
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|
|
|
<details class="note" open>
|
|
<summary>Note</summary>
|
|
<p>If the image is in mode <code>RGB</code> the tensor will have shape <code>[3, H, W]</code>,
|
|
otherwise <code>[1, H, W]</code> for mode <code>L</code> (grayscale) or <code>[4, H, W]</code> for mode <code>RGBA</code>.</p>
|
|
<p>Values are normalized to the range <code>[0, 1]</code>.</p>
|
|
</details>
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-122">122</a></span>
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<span class="normal"><a href="#__codelineno-0-123">123</a></span>
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<span class="normal"><a href="#__codelineno-0-124">124</a></span>
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<span class="normal"><a href="#__codelineno-0-126">126</a></span>
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<span class="normal"><a href="#__codelineno-0-127">127</a></span>
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<span class="normal"><a href="#__codelineno-0-129">129</a></span>
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<span class="normal"><a href="#__codelineno-0-130">130</a></span>
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<span class="normal"><a href="#__codelineno-0-131">131</a></span>
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<span class="normal"><a href="#__codelineno-0-132">132</a></span>
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<span class="normal"><a href="#__codelineno-0-133">133</a></span>
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<span class="normal"><a href="#__codelineno-0-134">134</a></span>
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<span class="normal"><a href="#__codelineno-0-135">135</a></span>
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<span class="normal"><a href="#__codelineno-0-136">136</a></span>
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<span class="normal"><a href="#__codelineno-0-137">137</a></span>
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<span class="normal"><a href="#__codelineno-0-138">138</a></span>
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<span class="normal"><a href="#__codelineno-0-139">139</a></span>
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<span class="normal"><a href="#__codelineno-0-140">140</a></span>
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<span class="normal"><a href="#__codelineno-0-141">141</a></span>
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<span class="normal"><a href="#__codelineno-0-142">142</a></span>
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<span class="normal"><a href="#__codelineno-0-150">150</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-122"><a id="__codelineno-0-122" name="__codelineno-0-122"></a><span class="k">def</span> <span class="nf">image_to_tensor</span><span class="p">(</span><span class="n">image</span><span class="p">:</span> <span class="n">Image</span><span class="o">.</span><span class="n">Image</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="n">Device</span> <span class="o">|</span> <span class="nb">str</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">dtype</span><span class="p">:</span> <span class="n">DType</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">-></span> <span class="n">Tensor</span><span class="p">:</span>
|
|
</span><span id="__span-0-123"><a id="__codelineno-0-123" name="__codelineno-0-123"></a><span class="w"> </span><span class="sd">"""Convert a PIL Image to a Tensor.</span>
|
|
</span><span id="__span-0-124"><a id="__codelineno-0-124" name="__codelineno-0-124"></a>
|
|
</span><span id="__span-0-125"><a id="__codelineno-0-125" name="__codelineno-0-125"></a><span class="sd"> Args:</span>
|
|
</span><span id="__span-0-126"><a id="__codelineno-0-126" name="__codelineno-0-126"></a><span class="sd"> image: The image to convert.</span>
|
|
</span><span id="__span-0-127"><a id="__codelineno-0-127" name="__codelineno-0-127"></a><span class="sd"> device: The device to use for the tensor.</span>
|
|
</span><span id="__span-0-128"><a id="__codelineno-0-128" name="__codelineno-0-128"></a><span class="sd"> dtype: The dtype to use for the tensor.</span>
|
|
</span><span id="__span-0-129"><a id="__codelineno-0-129" name="__codelineno-0-129"></a>
|
|
</span><span id="__span-0-130"><a id="__codelineno-0-130" name="__codelineno-0-130"></a><span class="sd"> Returns:</span>
|
|
</span><span id="__span-0-131"><a id="__codelineno-0-131" name="__codelineno-0-131"></a><span class="sd"> The converted tensor.</span>
|
|
</span><span id="__span-0-132"><a id="__codelineno-0-132" name="__codelineno-0-132"></a>
|
|
</span><span id="__span-0-133"><a id="__codelineno-0-133" name="__codelineno-0-133"></a><span class="sd"> Note:</span>
|
|
</span><span id="__span-0-134"><a id="__codelineno-0-134" name="__codelineno-0-134"></a><span class="sd"> If the image is in mode `RGB` the tensor will have shape `[3, H, W]`,</span>
|
|
</span><span id="__span-0-135"><a id="__codelineno-0-135" name="__codelineno-0-135"></a><span class="sd"> otherwise `[1, H, W]` for mode `L` (grayscale) or `[4, H, W]` for mode `RGBA`.</span>
|
|
</span><span id="__span-0-136"><a id="__codelineno-0-136" name="__codelineno-0-136"></a>
|
|
</span><span id="__span-0-137"><a id="__codelineno-0-137" name="__codelineno-0-137"></a><span class="sd"> Values are normalized to the range `[0, 1]`.</span>
|
|
</span><span id="__span-0-138"><a id="__codelineno-0-138" name="__codelineno-0-138"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-139"><a id="__codelineno-0-139" name="__codelineno-0-139"></a> <span class="n">image_tensor</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">array</span><span class="p">(</span><span class="n">image</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">float32</span><span class="p">)</span> <span class="o">/</span> <span class="mf">255.0</span><span class="p">,</span> <span class="n">device</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="n">dtype</span><span class="p">)</span>
|
|
</span><span id="__span-0-140"><a id="__codelineno-0-140" name="__codelineno-0-140"></a>
|
|
</span><span id="__span-0-141"><a id="__codelineno-0-141" name="__codelineno-0-141"></a> <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">image</span><span class="o">.</span><span class="n">mode</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="c1"># type: ignore</span>
|
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</span><span id="__span-0-142"><a id="__codelineno-0-142" name="__codelineno-0-142"></a> <span class="k">match</span> <span class="n">image</span><span class="o">.</span><span class="n">mode</span><span class="p">:</span>
|
|
</span><span id="__span-0-143"><a id="__codelineno-0-143" name="__codelineno-0-143"></a> <span class="k">case</span> <span class="s2">"L"</span><span class="p">:</span>
|
|
</span><span id="__span-0-144"><a id="__codelineno-0-144" name="__codelineno-0-144"></a> <span class="n">image_tensor</span> <span class="o">=</span> <span class="n">image_tensor</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
|
</span><span id="__span-0-145"><a id="__codelineno-0-145" name="__codelineno-0-145"></a> <span class="k">case</span> <span class="s2">"RGBA"</span> <span class="o">|</span> <span class="s2">"RGB"</span><span class="p">:</span>
|
|
</span><span id="__span-0-146"><a id="__codelineno-0-146" name="__codelineno-0-146"></a> <span class="n">image_tensor</span> <span class="o">=</span> <span class="n">image_tensor</span><span class="o">.</span><span class="n">permute</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
|
</span><span id="__span-0-147"><a id="__codelineno-0-147" name="__codelineno-0-147"></a> <span class="k">case</span><span class="w"> </span><span class="k">_</span><span class="p">:</span>
|
|
</span><span id="__span-0-148"><a id="__codelineno-0-148" name="__codelineno-0-148"></a> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Unsupported image mode: </span><span class="si">{</span><span class="n">image</span><span class="o">.</span><span class="n">mode</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
|
|
</span><span id="__span-0-149"><a id="__codelineno-0-149" name="__codelineno-0-149"></a>
|
|
</span><span id="__span-0-150"><a id="__codelineno-0-150" name="__codelineno-0-150"></a> <span class="k">return</span> <span class="n">image_tensor</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
|
</span></code></pre></div></td></tr></table></div>
|
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</details>
|
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</div>
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</div>
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|
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<div class="doc doc-object doc-function">
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<h2 id="refiners.fluxion.utils.load_from_safetensors" class="doc doc-heading">
|
|
<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">load_from_safetensors</span>
|
|
|
|
|
|
<a href="#refiners.fluxion.utils.load_from_safetensors" class="headerlink" title="Permanent link">¶</a></h2>
|
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">load_from_safetensors</span><span class="p">(</span>
|
|
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">path</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="pathlib.Path" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path">Path</a></span> <span class="o">|</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">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.device" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.device">device</a></span> <span class="o">|</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="s2">"cpu"</span>
|
|
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="p">)</span> <span class="o">-></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-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span><span class="p">]</span>
|
|
</span></code></pre></div>
|
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|
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<div class="doc doc-contents ">
|
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|
|
<p>Load tensors from a SafeTensor file from disk.</p>
|
|
|
|
|
|
<p><span class="doc-section-title">Parameters:</span></p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Name</th>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
<th>Default</th>
|
|
</tr>
|
|
</thead>
|
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<tbody>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code>path</code>
|
|
</td>
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" title="pathlib.Path" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path">Path</a> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></code>
|
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</td>
|
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<td>
|
|
<div class="doc-md-description">
|
|
<p>The path to the file.</p>
|
|
</div>
|
|
</td>
|
|
<td>
|
|
<em>required</em>
|
|
</td>
|
|
</tr>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code>device</code>
|
|
</td>
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" title="torch.device" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.device">device</a> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></code>
|
|
</td>
|
|
<td>
|
|
<div class="doc-md-description">
|
|
<p>The device to use for the tensors.</p>
|
|
</div>
|
|
</td>
|
|
<td>
|
|
<code>'cpu'</code>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
|
|
|
|
<p><span class="doc-section-title">Returns:</span></p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#dict">dict</a>[<a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a>, <a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a>]</code>
|
|
</td>
|
|
<td>
|
|
<div class="doc-md-description">
|
|
<p>The loaded tensors.</p>
|
|
</div>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-211">211</a></span>
|
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<span class="normal"><a href="#__codelineno-0-212">212</a></span>
|
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<span class="normal"><a href="#__codelineno-0-213">213</a></span>
|
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<span class="normal"><a href="#__codelineno-0-214">214</a></span>
|
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<span class="normal"><a href="#__codelineno-0-215">215</a></span>
|
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<span class="normal"><a href="#__codelineno-0-216">216</a></span>
|
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<span class="normal"><a href="#__codelineno-0-217">217</a></span>
|
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<span class="normal"><a href="#__codelineno-0-218">218</a></span>
|
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<span class="normal"><a href="#__codelineno-0-219">219</a></span>
|
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<span class="normal"><a href="#__codelineno-0-220">220</a></span>
|
|
<span class="normal"><a href="#__codelineno-0-221">221</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-211"><a id="__codelineno-0-211" name="__codelineno-0-211"></a><span class="k">def</span> <span class="nf">load_from_safetensors</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">Path</span> <span class="o">|</span> <span class="nb">str</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="n">Device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"cpu"</span><span class="p">)</span> <span class="o">-></span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]:</span>
|
|
</span><span id="__span-0-212"><a id="__codelineno-0-212" name="__codelineno-0-212"></a><span class="w"> </span><span class="sd">"""Load tensors from a SafeTensor file from disk.</span>
|
|
</span><span id="__span-0-213"><a id="__codelineno-0-213" name="__codelineno-0-213"></a>
|
|
</span><span id="__span-0-214"><a id="__codelineno-0-214" name="__codelineno-0-214"></a><span class="sd"> Args:</span>
|
|
</span><span id="__span-0-215"><a id="__codelineno-0-215" name="__codelineno-0-215"></a><span class="sd"> path: The path to the file.</span>
|
|
</span><span id="__span-0-216"><a id="__codelineno-0-216" name="__codelineno-0-216"></a><span class="sd"> device: The device to use for the tensors.</span>
|
|
</span><span id="__span-0-217"><a id="__codelineno-0-217" name="__codelineno-0-217"></a>
|
|
</span><span id="__span-0-218"><a id="__codelineno-0-218" name="__codelineno-0-218"></a><span class="sd"> Returns:</span>
|
|
</span><span id="__span-0-219"><a id="__codelineno-0-219" name="__codelineno-0-219"></a><span class="sd"> The loaded tensors.</span>
|
|
</span><span id="__span-0-220"><a id="__codelineno-0-220" name="__codelineno-0-220"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-221"><a id="__codelineno-0-221" name="__codelineno-0-221"></a> <span class="k">return</span> <span class="n">_load_file</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">device</span><span class="p">))</span>
|
|
</span></code></pre></div></td></tr></table></div>
|
|
</details>
|
|
</div>
|
|
|
|
</div>
|
|
|
|
<div class="doc doc-object doc-function">
|
|
|
|
|
|
<h2 id="refiners.fluxion.utils.load_tensors" class="doc doc-heading">
|
|
<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">load_tensors</span>
|
|
|
|
|
|
<a href="#refiners.fluxion.utils.load_tensors" class="headerlink" title="Permanent link">¶</a></h2>
|
|
<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">load_tensors</span><span class="p">(</span>
|
|
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">path</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="pathlib.Path" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path">Path</a></span> <span class="o">|</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">device</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.device" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.device">device</a></span> <span class="o">|</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="s2">"cpu"</span>
|
|
</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="p">)</span> <span class="o">-></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-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span><span class="p">]</span>
|
|
</span></code></pre></div>
|
|
|
|
<div class="doc doc-contents ">
|
|
|
|
<p>Load tensors from a file saved with <code>torch.save</code> from disk.</p>
|
|
|
|
|
|
<details class="note" open>
|
|
<summary>Note</summary>
|
|
<p>This function uses the <code>weights_only</code> mode of <code>torch.load</code> for additional safety.</p>
|
|
</details>
|
|
|
|
<details class="warning" open>
|
|
<summary>Warning</summary>
|
|
<p>Still, <strong>only load data you trust</strong> and favor using
|
|
<a class="autorefs autorefs-internal" href="#refiners.fluxion.utils.load_from_safetensors"><code>load_from_safetensors</code></a> instead.</p>
|
|
</details>
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-188">188</a></span>
|
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<span class="normal"><a href="#__codelineno-0-189">189</a></span>
|
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<span class="normal"><a href="#__codelineno-0-190">190</a></span>
|
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<span class="normal"><a href="#__codelineno-0-191">191</a></span>
|
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<span class="normal"><a href="#__codelineno-0-192">192</a></span>
|
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<span class="normal"><a href="#__codelineno-0-193">193</a></span>
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<span class="normal"><a href="#__codelineno-0-194">194</a></span>
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<span class="normal"><a href="#__codelineno-0-195">195</a></span>
|
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<span class="normal"><a href="#__codelineno-0-196">196</a></span>
|
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<span class="normal"><a href="#__codelineno-0-197">197</a></span>
|
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<span class="normal"><a href="#__codelineno-0-198">198</a></span>
|
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<span class="normal"><a href="#__codelineno-0-199">199</a></span>
|
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<span class="normal"><a href="#__codelineno-0-200">200</a></span>
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<span class="normal"><a href="#__codelineno-0-201">201</a></span>
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<span class="normal"><a href="#__codelineno-0-202">202</a></span>
|
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<span class="normal"><a href="#__codelineno-0-203">203</a></span>
|
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<span class="normal"><a href="#__codelineno-0-204">204</a></span>
|
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<span class="normal"><a href="#__codelineno-0-205">205</a></span>
|
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<span class="normal"><a href="#__codelineno-0-206">206</a></span>
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<span class="normal"><a href="#__codelineno-0-207">207</a></span>
|
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<span class="normal"><a href="#__codelineno-0-208">208</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-188"><a id="__codelineno-0-188" name="__codelineno-0-188"></a><span class="k">def</span> <span class="nf">load_tensors</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">Path</span> <span class="o">|</span> <span class="nb">str</span><span class="p">,</span> <span class="o">/</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="n">Device</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"cpu"</span><span class="p">)</span> <span class="o">-></span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">]:</span>
|
|
</span><span id="__span-0-189"><a id="__codelineno-0-189" name="__codelineno-0-189"></a><span class="w"> </span><span class="sd">"""Load tensors from a file saved with `torch.save` from disk.</span>
|
|
</span><span id="__span-0-190"><a id="__codelineno-0-190" name="__codelineno-0-190"></a>
|
|
</span><span id="__span-0-191"><a id="__codelineno-0-191" name="__codelineno-0-191"></a><span class="sd"> Note:</span>
|
|
</span><span id="__span-0-192"><a id="__codelineno-0-192" name="__codelineno-0-192"></a><span class="sd"> This function uses the `weights_only` mode of `torch.load` for additional safety.</span>
|
|
</span><span id="__span-0-193"><a id="__codelineno-0-193" name="__codelineno-0-193"></a>
|
|
</span><span id="__span-0-194"><a id="__codelineno-0-194" name="__codelineno-0-194"></a><span class="sd"> Warning:</span>
|
|
</span><span id="__span-0-195"><a id="__codelineno-0-195" name="__codelineno-0-195"></a><span class="sd"> Still, **only load data you trust** and favor using</span>
|
|
</span><span id="__span-0-196"><a id="__codelineno-0-196" name="__codelineno-0-196"></a><span class="sd"> [`load_from_safetensors`][refiners.fluxion.utils.load_from_safetensors] instead.</span>
|
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</span><span id="__span-0-197"><a id="__codelineno-0-197" name="__codelineno-0-197"></a><span class="sd"> """</span>
|
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</span><span id="__span-0-198"><a id="__codelineno-0-198" name="__codelineno-0-198"></a> <span class="c1"># see https://github.com/pytorch/pytorch/issues/97207#issuecomment-1494781560</span>
|
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</span><span id="__span-0-199"><a id="__codelineno-0-199" name="__codelineno-0-199"></a> <span class="k">with</span> <span class="n">warnings</span><span class="o">.</span><span class="n">catch_warnings</span><span class="p">():</span>
|
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</span><span id="__span-0-200"><a id="__codelineno-0-200" name="__codelineno-0-200"></a> <span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">category</span><span class="o">=</span><span class="ne">UserWarning</span><span class="p">,</span> <span class="n">message</span><span class="o">=</span><span class="s2">"TypedStorage is deprecated"</span><span class="p">)</span>
|
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</span><span id="__span-0-201"><a id="__codelineno-0-201" name="__codelineno-0-201"></a> <span class="n">tensors</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">map_location</span><span class="o">=</span><span class="n">device</span><span class="p">,</span> <span class="n">weights_only</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># type: ignore</span>
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</span><span id="__span-0-202"><a id="__codelineno-0-202" name="__codelineno-0-202"></a>
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</span><span id="__span-0-203"><a id="__codelineno-0-203" name="__codelineno-0-203"></a> <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tensors</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">all</span><span class="p">(</span>
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</span><span id="__span-0-204"><a id="__codelineno-0-204" name="__codelineno-0-204"></a> <span class="nb">isinstance</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">Tensor</span><span class="p">)</span>
|
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</span><span id="__span-0-205"><a id="__codelineno-0-205" name="__codelineno-0-205"></a> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">tensors</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="c1"># type: ignore</span>
|
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</span><span id="__span-0-206"><a id="__codelineno-0-206" name="__codelineno-0-206"></a> <span class="p">),</span> <span class="s2">"Invalid tensor file, expected a dict[str, Tensor]"</span>
|
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</span><span id="__span-0-207"><a id="__codelineno-0-207" name="__codelineno-0-207"></a>
|
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</span><span id="__span-0-208"><a id="__codelineno-0-208" name="__codelineno-0-208"></a> <span class="k">return</span> <span class="n">cast</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="n">Tensor</span><span class="p">],</span> <span class="n">tensors</span><span class="p">)</span>
|
|
</span></code></pre></div></td></tr></table></div>
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</details>
|
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</div>
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</div>
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<div class="doc doc-object doc-function">
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<h2 id="refiners.fluxion.utils.save_to_safetensors" class="doc doc-heading">
|
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<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">save_to_safetensors</span>
|
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<a href="#refiners.fluxion.utils.save_to_safetensors" class="headerlink" title="Permanent link">¶</a></h2>
|
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">save_to_safetensors</span><span class="p">(</span>
|
|
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a> <span class="n">path</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="pathlib.Path" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path">Path</a></span> <span class="o">|</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><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="n">tensors</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-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span><span class="p">],</span>
|
|
</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a> <span class="n">metadata</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-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
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</span><span id="__span-0-5"><a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span>
|
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</span></code></pre></div>
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<div class="doc doc-contents ">
|
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<p>Save tensors to a SafeTensor file on disk.</p>
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<p><span class="doc-section-title">Parameters:</span></p>
|
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<table>
|
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<thead>
|
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<tr>
|
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<th>Name</th>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
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<th>Default</th>
|
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</tr>
|
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</thead>
|
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<tbody>
|
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<tr class="doc-section-item">
|
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<td>
|
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<code>path</code>
|
|
</td>
|
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<td>
|
|
<code><a class="autorefs autorefs-external" title="pathlib.Path" href="https://docs.python.org/3/library/pathlib.html#pathlib.Path">Path</a> | <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></code>
|
|
</td>
|
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<td>
|
|
<div class="doc-md-description">
|
|
<p>The path to the file.</p>
|
|
</div>
|
|
</td>
|
|
<td>
|
|
<em>required</em>
|
|
</td>
|
|
</tr>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code>tensors</code>
|
|
</td>
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#dict">dict</a>[<a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a>, <a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a>]</code>
|
|
</td>
|
|
<td>
|
|
<div class="doc-md-description">
|
|
<p>The tensors to save.</p>
|
|
</div>
|
|
</td>
|
|
<td>
|
|
<em>required</em>
|
|
</td>
|
|
</tr>
|
|
<tr class="doc-section-item">
|
|
<td>
|
|
<code>metadata</code>
|
|
</td>
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#dict">dict</a>[<a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a>, <a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a>] | None</code>
|
|
</td>
|
|
<td>
|
|
<div class="doc-md-description">
|
|
<p>The metadata to save.</p>
|
|
</div>
|
|
</td>
|
|
<td>
|
|
<code>None</code>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-224">224</a></span>
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<span class="normal"><a href="#__codelineno-0-225">225</a></span>
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<span class="normal"><a href="#__codelineno-0-226">226</a></span>
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<span class="normal"><a href="#__codelineno-0-227">227</a></span>
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<span class="normal"><a href="#__codelineno-0-228">228</a></span>
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<span class="normal"><a href="#__codelineno-0-229">229</a></span>
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<span class="normal"><a href="#__codelineno-0-231">231</a></span>
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<span class="normal"><a href="#__codelineno-0-232">232</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-224"><a id="__codelineno-0-224" name="__codelineno-0-224"></a><span class="k">def</span> <span class="nf">save_to_safetensors</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="n">Path</span> <span class="o">|</span> <span class="nb">str</span><span class="p">,</span> <span class="n">tensors</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="n">Tensor</span><span class="p">],</span> <span class="n">metadata</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">str</span><span class="p">]</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">-></span> <span class="kc">None</span><span class="p">:</span>
|
|
</span><span id="__span-0-225"><a id="__codelineno-0-225" name="__codelineno-0-225"></a><span class="w"> </span><span class="sd">"""Save tensors to a SafeTensor file on disk.</span>
|
|
</span><span id="__span-0-226"><a id="__codelineno-0-226" name="__codelineno-0-226"></a>
|
|
</span><span id="__span-0-227"><a id="__codelineno-0-227" name="__codelineno-0-227"></a><span class="sd"> Args:</span>
|
|
</span><span id="__span-0-228"><a id="__codelineno-0-228" name="__codelineno-0-228"></a><span class="sd"> path: The path to the file.</span>
|
|
</span><span id="__span-0-229"><a id="__codelineno-0-229" name="__codelineno-0-229"></a><span class="sd"> tensors: The tensors to save.</span>
|
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</span><span id="__span-0-230"><a id="__codelineno-0-230" name="__codelineno-0-230"></a><span class="sd"> metadata: The metadata to save.</span>
|
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</span><span id="__span-0-231"><a id="__codelineno-0-231" name="__codelineno-0-231"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-232"><a id="__codelineno-0-232" name="__codelineno-0-232"></a> <span class="n">_save_file</span><span class="p">(</span><span class="n">tensors</span><span class="p">,</span> <span class="n">path</span><span class="p">,</span> <span class="n">metadata</span><span class="p">)</span> <span class="c1"># type: ignore</span>
|
|
</span></code></pre></div></td></tr></table></div>
|
|
</details>
|
|
</div>
|
|
|
|
</div>
|
|
|
|
<div class="doc doc-object doc-function">
|
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|
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|
<h2 id="refiners.fluxion.utils.str_to_dtype" class="doc doc-heading">
|
|
<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">str_to_dtype</span>
|
|
|
|
|
|
<a href="#refiners.fluxion.utils.str_to_dtype" class="headerlink" title="Permanent link">¶</a></h2>
|
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">str_to_dtype</span><span class="p">(</span><span class="n">dtype</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="n"><a class="autorefs autorefs-external" title="torch.dtype" href="https://pytorch.org/docs/main/tensor_attributes.html#torch.dtype">dtype</a></span>
|
|
</span></code></pre></div>
|
|
|
|
<div class="doc doc-contents ">
|
|
|
|
<p>Converts a string dtype to a torch.dtype.</p>
|
|
<p>See also https://pytorch.org/docs/stable/tensor_attributes.html#torch-dtype</p>
|
|
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-275">275</a></span>
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<span class="normal"><a href="#__codelineno-0-276">276</a></span>
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<span class="normal"><a href="#__codelineno-0-279">279</a></span>
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<span class="normal"><a href="#__codelineno-0-303">303</a></span>
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<span class="normal"><a href="#__codelineno-0-306">306</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-275"><a id="__codelineno-0-275" name="__codelineno-0-275"></a><span class="k">def</span> <span class="nf">str_to_dtype</span><span class="p">(</span><span class="n">dtype</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-></span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
|
|
</span><span id="__span-0-276"><a id="__codelineno-0-276" name="__codelineno-0-276"></a><span class="w"> </span><span class="sd">"""Converts a string dtype to a torch.dtype.</span>
|
|
</span><span id="__span-0-277"><a id="__codelineno-0-277" name="__codelineno-0-277"></a>
|
|
</span><span id="__span-0-278"><a id="__codelineno-0-278" name="__codelineno-0-278"></a><span class="sd"> See also https://pytorch.org/docs/stable/tensor_attributes.html#torch-dtype</span>
|
|
</span><span id="__span-0-279"><a id="__codelineno-0-279" name="__codelineno-0-279"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-280"><a id="__codelineno-0-280" name="__codelineno-0-280"></a> <span class="k">match</span> <span class="n">dtype</span><span class="o">.</span><span class="n">lower</span><span class="p">():</span>
|
|
</span><span id="__span-0-281"><a id="__codelineno-0-281" name="__codelineno-0-281"></a> <span class="k">case</span> <span class="s2">"float32"</span> <span class="o">|</span> <span class="s2">"float"</span><span class="p">:</span>
|
|
</span><span id="__span-0-282"><a id="__codelineno-0-282" name="__codelineno-0-282"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">float32</span>
|
|
</span><span id="__span-0-283"><a id="__codelineno-0-283" name="__codelineno-0-283"></a> <span class="k">case</span> <span class="s2">"float64"</span> <span class="o">|</span> <span class="s2">"double"</span><span class="p">:</span>
|
|
</span><span id="__span-0-284"><a id="__codelineno-0-284" name="__codelineno-0-284"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">float64</span>
|
|
</span><span id="__span-0-285"><a id="__codelineno-0-285" name="__codelineno-0-285"></a> <span class="k">case</span> <span class="s2">"complex64"</span> <span class="o">|</span> <span class="s2">"cfloat"</span><span class="p">:</span>
|
|
</span><span id="__span-0-286"><a id="__codelineno-0-286" name="__codelineno-0-286"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">complex64</span>
|
|
</span><span id="__span-0-287"><a id="__codelineno-0-287" name="__codelineno-0-287"></a> <span class="k">case</span> <span class="s2">"complex128"</span> <span class="o">|</span> <span class="s2">"cdouble"</span><span class="p">:</span>
|
|
</span><span id="__span-0-288"><a id="__codelineno-0-288" name="__codelineno-0-288"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">complex128</span>
|
|
</span><span id="__span-0-289"><a id="__codelineno-0-289" name="__codelineno-0-289"></a> <span class="k">case</span> <span class="s2">"float16"</span> <span class="o">|</span> <span class="s2">"half"</span><span class="p">:</span>
|
|
</span><span id="__span-0-290"><a id="__codelineno-0-290" name="__codelineno-0-290"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">float16</span>
|
|
</span><span id="__span-0-291"><a id="__codelineno-0-291" name="__codelineno-0-291"></a> <span class="k">case</span> <span class="s2">"bfloat16"</span><span class="p">:</span>
|
|
</span><span id="__span-0-292"><a id="__codelineno-0-292" name="__codelineno-0-292"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">bfloat16</span>
|
|
</span><span id="__span-0-293"><a id="__codelineno-0-293" name="__codelineno-0-293"></a> <span class="k">case</span> <span class="s2">"uint8"</span><span class="p">:</span>
|
|
</span><span id="__span-0-294"><a id="__codelineno-0-294" name="__codelineno-0-294"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">uint8</span>
|
|
</span><span id="__span-0-295"><a id="__codelineno-0-295" name="__codelineno-0-295"></a> <span class="k">case</span> <span class="s2">"int8"</span><span class="p">:</span>
|
|
</span><span id="__span-0-296"><a id="__codelineno-0-296" name="__codelineno-0-296"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">int8</span>
|
|
</span><span id="__span-0-297"><a id="__codelineno-0-297" name="__codelineno-0-297"></a> <span class="k">case</span> <span class="s2">"int16"</span> <span class="o">|</span> <span class="s2">"short"</span><span class="p">:</span>
|
|
</span><span id="__span-0-298"><a id="__codelineno-0-298" name="__codelineno-0-298"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">int16</span>
|
|
</span><span id="__span-0-299"><a id="__codelineno-0-299" name="__codelineno-0-299"></a> <span class="k">case</span> <span class="s2">"int32"</span> <span class="o">|</span> <span class="s2">"int"</span><span class="p">:</span>
|
|
</span><span id="__span-0-300"><a id="__codelineno-0-300" name="__codelineno-0-300"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">int32</span>
|
|
</span><span id="__span-0-301"><a id="__codelineno-0-301" name="__codelineno-0-301"></a> <span class="k">case</span> <span class="s2">"int64"</span> <span class="o">|</span> <span class="s2">"long"</span><span class="p">:</span>
|
|
</span><span id="__span-0-302"><a id="__codelineno-0-302" name="__codelineno-0-302"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">int64</span>
|
|
</span><span id="__span-0-303"><a id="__codelineno-0-303" name="__codelineno-0-303"></a> <span class="k">case</span> <span class="s2">"bool"</span><span class="p">:</span>
|
|
</span><span id="__span-0-304"><a id="__codelineno-0-304" name="__codelineno-0-304"></a> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">bool</span>
|
|
</span><span id="__span-0-305"><a id="__codelineno-0-305" name="__codelineno-0-305"></a> <span class="k">case</span><span class="w"> </span><span class="k">_</span><span class="p">:</span>
|
|
</span><span id="__span-0-306"><a id="__codelineno-0-306" name="__codelineno-0-306"></a> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Unknown dtype: </span><span class="si">{</span><span class="n">dtype</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
|
|
</span></code></pre></div></td></tr></table></div>
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</details>
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</div>
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</div>
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<div class="doc doc-object doc-function">
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<h2 id="refiners.fluxion.utils.summarize_tensor" class="doc doc-heading">
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<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">summarize_tensor</span>
|
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<a href="#refiners.fluxion.utils.summarize_tensor" class="headerlink" title="Permanent link">¶</a></h2>
|
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">summarize_tensor</span><span class="p">(</span><span class="n">tensor</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span><span class="p">)</span> <span class="o">-></span> <span class="n"><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></span>
|
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</span></code></pre></div>
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<div class="doc doc-contents ">
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<p>Summarize a tensor.</p>
|
|
<p>This helper function prints the shape, dtype, device, min, max, mean, std, norm and grad of a tensor.</p>
|
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|
|
<p><span class="doc-section-title">Parameters:</span></p>
|
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<table>
|
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<thead>
|
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<tr>
|
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<th>Name</th>
|
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<th>Type</th>
|
|
<th>Description</th>
|
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<th>Default</th>
|
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</tr>
|
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</thead>
|
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<tbody>
|
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<tr class="doc-section-item">
|
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<td>
|
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<code>tensor</code>
|
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</td>
|
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<td>
|
|
<code><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></code>
|
|
</td>
|
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<td>
|
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<div class="doc-md-description">
|
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<p>The tensor to summarize.</p>
|
|
</div>
|
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</td>
|
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<td>
|
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<em>required</em>
|
|
</td>
|
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</tr>
|
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</tbody>
|
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</table>
|
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<p><span class="doc-section-title">Returns:</span></p>
|
|
<table>
|
|
<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
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<tbody>
|
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<tr class="doc-section-item">
|
|
<td>
|
|
<code><a class="autorefs autorefs-external" href="https://docs.python.org/3/library/stdtypes.html#str">str</a></code>
|
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</td>
|
|
<td>
|
|
<div class="doc-md-description">
|
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<p>The summary string.</p>
|
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</div>
|
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</td>
|
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</tr>
|
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</tbody>
|
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</table>
|
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|
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<details class="quote">
|
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<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
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<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-235">235</a></span>
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<span class="normal"><a href="#__codelineno-0-272">272</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-235"><a id="__codelineno-0-235" name="__codelineno-0-235"></a><span class="k">def</span> <span class="nf">summarize_tensor</span><span class="p">(</span><span class="n">tensor</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="o">/</span><span class="p">)</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
|
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</span><span id="__span-0-236"><a id="__codelineno-0-236" name="__codelineno-0-236"></a><span class="w"> </span><span class="sd">"""Summarize a tensor.</span>
|
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</span><span id="__span-0-237"><a id="__codelineno-0-237" name="__codelineno-0-237"></a>
|
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</span><span id="__span-0-238"><a id="__codelineno-0-238" name="__codelineno-0-238"></a><span class="sd"> This helper function prints the shape, dtype, device, min, max, mean, std, norm and grad of a tensor.</span>
|
|
</span><span id="__span-0-239"><a id="__codelineno-0-239" name="__codelineno-0-239"></a>
|
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</span><span id="__span-0-240"><a id="__codelineno-0-240" name="__codelineno-0-240"></a><span class="sd"> Args:</span>
|
|
</span><span id="__span-0-241"><a id="__codelineno-0-241" name="__codelineno-0-241"></a><span class="sd"> tensor: The tensor to summarize.</span>
|
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</span><span id="__span-0-242"><a id="__codelineno-0-242" name="__codelineno-0-242"></a>
|
|
</span><span id="__span-0-243"><a id="__codelineno-0-243" name="__codelineno-0-243"></a><span class="sd"> Returns:</span>
|
|
</span><span id="__span-0-244"><a id="__codelineno-0-244" name="__codelineno-0-244"></a><span class="sd"> The summary string.</span>
|
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</span><span id="__span-0-245"><a id="__codelineno-0-245" name="__codelineno-0-245"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-246"><a id="__codelineno-0-246" name="__codelineno-0-246"></a> <span class="n">info_list</span> <span class="o">=</span> <span class="p">[</span>
|
|
</span><span id="__span-0-247"><a id="__codelineno-0-247" name="__codelineno-0-247"></a> <span class="sa">f</span><span class="s2">"shape=(</span><span class="si">{</span><span class="s1">', '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span><span class="w"> </span><span class="n">tensor</span><span class="o">.</span><span class="n">shape</span><span class="p">))</span><span class="si">}</span><span class="s2">)"</span><span class="p">,</span>
|
|
</span><span id="__span-0-248"><a id="__codelineno-0-248" name="__codelineno-0-248"></a> <span class="sa">f</span><span class="s2">"dtype=</span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">object</span><span class="o">=</span><span class="n">tensor</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span><span class="o">.</span><span class="n">removeprefix</span><span class="p">(</span><span class="s1">'torch.'</span><span class="p">)</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-249"><a id="__codelineno-0-249" name="__codelineno-0-249"></a> <span class="sa">f</span><span class="s2">"device=</span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">device</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-250"><a id="__codelineno-0-250" name="__codelineno-0-250"></a> <span class="p">]</span>
|
|
</span><span id="__span-0-251"><a id="__codelineno-0-251" name="__codelineno-0-251"></a> <span class="k">if</span> <span class="n">tensor</span><span class="o">.</span><span class="n">is_complex</span><span class="p">():</span>
|
|
</span><span id="__span-0-252"><a id="__codelineno-0-252" name="__codelineno-0-252"></a> <span class="n">tensor_f</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">real</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
|
|
</span><span id="__span-0-253"><a id="__codelineno-0-253" name="__codelineno-0-253"></a> <span class="k">else</span><span class="p">:</span>
|
|
</span><span id="__span-0-254"><a id="__codelineno-0-254" name="__codelineno-0-254"></a> <span class="k">if</span> <span class="n">tensor</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
|
</span><span id="__span-0-255"><a id="__codelineno-0-255" name="__codelineno-0-255"></a> <span class="n">info_list</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span>
|
|
</span><span id="__span-0-256"><a id="__codelineno-0-256" name="__codelineno-0-256"></a> <span class="p">[</span>
|
|
</span><span id="__span-0-257"><a id="__codelineno-0-257" name="__codelineno-0-257"></a> <span class="sa">f</span><span class="s2">"min=</span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="c1"># type: ignore</span>
|
|
</span><span id="__span-0-258"><a id="__codelineno-0-258" name="__codelineno-0-258"></a> <span class="sa">f</span><span class="s2">"max=</span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="c1"># type: ignore</span>
|
|
</span><span id="__span-0-259"><a id="__codelineno-0-259" name="__codelineno-0-259"></a> <span class="p">]</span>
|
|
</span><span id="__span-0-260"><a id="__codelineno-0-260" name="__codelineno-0-260"></a> <span class="p">)</span>
|
|
</span><span id="__span-0-261"><a id="__codelineno-0-261" name="__codelineno-0-261"></a> <span class="n">tensor_f</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
|
|
</span><span id="__span-0-262"><a id="__codelineno-0-262" name="__codelineno-0-262"></a>
|
|
</span><span id="__span-0-263"><a id="__codelineno-0-263" name="__codelineno-0-263"></a> <span class="n">info_list</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span>
|
|
</span><span id="__span-0-264"><a id="__codelineno-0-264" name="__codelineno-0-264"></a> <span class="p">[</span>
|
|
</span><span id="__span-0-265"><a id="__codelineno-0-265" name="__codelineno-0-265"></a> <span class="sa">f</span><span class="s2">"mean=</span><span class="si">{</span><span class="n">tensor_f</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-266"><a id="__codelineno-0-266" name="__codelineno-0-266"></a> <span class="sa">f</span><span class="s2">"std=</span><span class="si">{</span><span class="n">tensor_f</span><span class="o">.</span><span class="n">std</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-267"><a id="__codelineno-0-267" name="__codelineno-0-267"></a> <span class="sa">f</span><span class="s2">"norm=</span><span class="si">{</span><span class="n">norm</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">tensor_f</span><span class="p">)</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-268"><a id="__codelineno-0-268" name="__codelineno-0-268"></a> <span class="sa">f</span><span class="s2">"grad=</span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">requires_grad</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span>
|
|
</span><span id="__span-0-269"><a id="__codelineno-0-269" name="__codelineno-0-269"></a> <span class="p">]</span>
|
|
</span><span id="__span-0-270"><a id="__codelineno-0-270" name="__codelineno-0-270"></a> <span class="p">)</span>
|
|
</span><span id="__span-0-271"><a id="__codelineno-0-271" name="__codelineno-0-271"></a>
|
|
</span><span id="__span-0-272"><a id="__codelineno-0-272" name="__codelineno-0-272"></a> <span class="k">return</span> <span class="s2">"Tensor("</span> <span class="o">+</span> <span class="s2">", "</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">info_list</span><span class="p">)</span> <span class="o">+</span> <span class="s2">")"</span>
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</span></code></pre></div></td></tr></table></div>
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</details>
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</div>
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</div>
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<div class="doc doc-object doc-function">
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<h2 id="refiners.fluxion.utils.tensor_to_image" class="doc doc-heading">
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<code class="doc-symbol doc-symbol-heading doc-symbol-function"></code> <span class="doc doc-object-name doc-function-name">tensor_to_image</span>
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<a href="#refiners.fluxion.utils.tensor_to_image" class="headerlink" title="Permanent link">¶</a></h2>
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<div class="language-python doc-signature highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="nf">tensor_to_image</span><span class="p">(</span><span class="n">tensor</span><span class="p">:</span> <span class="n"><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></span><span class="p">)</span> <span class="o">-></span> <span class="n"><span title="PIL.Image.Image">Image</span></span>
|
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</span></code></pre></div>
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<div class="doc doc-contents ">
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<p>Convert a Tensor to a PIL Image.</p>
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<p><span class="doc-section-title">Parameters:</span></p>
|
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<table>
|
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<thead>
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<tr>
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<th>Name</th>
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<th>Type</th>
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<th>Description</th>
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<th>Default</th>
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</tr>
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</thead>
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<tbody>
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<tr class="doc-section-item">
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<td>
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<code>tensor</code>
|
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</td>
|
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<td>
|
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<code><a class="autorefs autorefs-external" title="torch.Tensor" href="https://pytorch.org/docs/main/tensors.html#torch.Tensor">Tensor</a></code>
|
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</td>
|
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<td>
|
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<div class="doc-md-description">
|
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<p>The tensor to convert.</p>
|
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</div>
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</td>
|
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<td>
|
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<em>required</em>
|
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</td>
|
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</tr>
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</tbody>
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</table>
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<p><span class="doc-section-title">Returns:</span></p>
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<table>
|
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<thead>
|
|
<tr>
|
|
<th>Type</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
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<tbody>
|
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<tr class="doc-section-item">
|
|
<td>
|
|
<code><span title="PIL.Image.Image">Image</span></code>
|
|
</td>
|
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<td>
|
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<div class="doc-md-description">
|
|
<p>The converted image.</p>
|
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</div>
|
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</td>
|
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</tr>
|
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</tbody>
|
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</table>
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<details class="note" open>
|
|
<summary>Note</summary>
|
|
<p>The tensor must have shape <code>[1, channels, height, width]</code> where the number of
|
|
channels is either 1 (grayscale) or 3 (RGB) or 4 (RGBA).</p>
|
|
<p>Expected values are in the range <code>[0, 1]</code> and are clamped to this range.</p>
|
|
</details>
|
|
<details class="quote">
|
|
<summary>Source code in <code>src/refiners/fluxion/utils.py</code></summary>
|
|
<div class="language-python highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"><a href="#__codelineno-0-157">157</a></span>
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<span class="normal"><a href="#__codelineno-0-158">158</a></span>
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<span class="normal"><a href="#__codelineno-0-159">159</a></span>
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<span class="normal"><a href="#__codelineno-0-160">160</a></span>
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<span class="normal"><a href="#__codelineno-0-161">161</a></span>
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<span class="normal"><a href="#__codelineno-0-162">162</a></span>
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<span class="normal"><a href="#__codelineno-0-163">163</a></span>
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<span class="normal"><a href="#__codelineno-0-164">164</a></span>
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<span class="normal"><a href="#__codelineno-0-165">165</a></span>
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<span class="normal"><a href="#__codelineno-0-166">166</a></span>
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<span class="normal"><a href="#__codelineno-0-167">167</a></span>
|
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<span class="normal"><a href="#__codelineno-0-168">168</a></span>
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<span class="normal"><a href="#__codelineno-0-169">169</a></span>
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<span class="normal"><a href="#__codelineno-0-170">170</a></span>
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<span class="normal"><a href="#__codelineno-0-171">171</a></span>
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<span class="normal"><a href="#__codelineno-0-172">172</a></span>
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<span class="normal"><a href="#__codelineno-0-173">173</a></span>
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<span class="normal"><a href="#__codelineno-0-174">174</a></span>
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<span class="normal"><a href="#__codelineno-0-175">175</a></span>
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<span class="normal"><a href="#__codelineno-0-176">176</a></span>
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<span class="normal"><a href="#__codelineno-0-177">177</a></span>
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<span class="normal"><a href="#__codelineno-0-178">178</a></span>
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<span class="normal"><a href="#__codelineno-0-179">179</a></span>
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<span class="normal"><a href="#__codelineno-0-180">180</a></span>
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<span class="normal"><a href="#__codelineno-0-181">181</a></span>
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<span class="normal"><a href="#__codelineno-0-182">182</a></span>
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<span class="normal"><a href="#__codelineno-0-183">183</a></span>
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<span class="normal"><a href="#__codelineno-0-184">184</a></span>
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<span class="normal"><a href="#__codelineno-0-185">185</a></span></pre></div></td><td class="code"><div><pre><span></span><code><span id="__span-0-157"><a id="__codelineno-0-157" name="__codelineno-0-157"></a><span class="k">def</span> <span class="nf">tensor_to_image</span><span class="p">(</span><span class="n">tensor</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">)</span> <span class="o">-></span> <span class="n">Image</span><span class="o">.</span><span class="n">Image</span><span class="p">:</span>
|
|
</span><span id="__span-0-158"><a id="__codelineno-0-158" name="__codelineno-0-158"></a><span class="w"> </span><span class="sd">"""Convert a Tensor to a PIL Image.</span>
|
|
</span><span id="__span-0-159"><a id="__codelineno-0-159" name="__codelineno-0-159"></a>
|
|
</span><span id="__span-0-160"><a id="__codelineno-0-160" name="__codelineno-0-160"></a><span class="sd"> Args:</span>
|
|
</span><span id="__span-0-161"><a id="__codelineno-0-161" name="__codelineno-0-161"></a><span class="sd"> tensor: The tensor to convert.</span>
|
|
</span><span id="__span-0-162"><a id="__codelineno-0-162" name="__codelineno-0-162"></a>
|
|
</span><span id="__span-0-163"><a id="__codelineno-0-163" name="__codelineno-0-163"></a><span class="sd"> Returns:</span>
|
|
</span><span id="__span-0-164"><a id="__codelineno-0-164" name="__codelineno-0-164"></a><span class="sd"> The converted image.</span>
|
|
</span><span id="__span-0-165"><a id="__codelineno-0-165" name="__codelineno-0-165"></a>
|
|
</span><span id="__span-0-166"><a id="__codelineno-0-166" name="__codelineno-0-166"></a><span class="sd"> Note:</span>
|
|
</span><span id="__span-0-167"><a id="__codelineno-0-167" name="__codelineno-0-167"></a><span class="sd"> The tensor must have shape `[1, channels, height, width]` where the number of</span>
|
|
</span><span id="__span-0-168"><a id="__codelineno-0-168" name="__codelineno-0-168"></a><span class="sd"> channels is either 1 (grayscale) or 3 (RGB) or 4 (RGBA).</span>
|
|
</span><span id="__span-0-169"><a id="__codelineno-0-169" name="__codelineno-0-169"></a>
|
|
</span><span id="__span-0-170"><a id="__codelineno-0-170" name="__codelineno-0-170"></a><span class="sd"> Expected values are in the range `[0, 1]` and are clamped to this range.</span>
|
|
</span><span id="__span-0-171"><a id="__codelineno-0-171" name="__codelineno-0-171"></a><span class="sd"> """</span>
|
|
</span><span id="__span-0-172"><a id="__codelineno-0-172" name="__codelineno-0-172"></a> <span class="k">assert</span> <span class="n">tensor</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">4</span> <span class="ow">and</span> <span class="n">tensor</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"Unsupported tensor shape: </span><span class="si">{</span><span class="n">tensor</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s2">"</span>
|
|
</span><span id="__span-0-173"><a id="__codelineno-0-173" name="__codelineno-0-173"></a> <span class="n">num_channels</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
|
</span><span id="__span-0-174"><a id="__codelineno-0-174" name="__codelineno-0-174"></a> <span class="n">tensor</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">clamp</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="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
|
</span><span id="__span-0-175"><a id="__codelineno-0-175" name="__codelineno-0-175"></a> <span class="n">tensor</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span> <span class="c1"># to avoid numpy error with bfloat16</span>
|
|
</span><span id="__span-0-176"><a id="__codelineno-0-176" name="__codelineno-0-176"></a>
|
|
</span><span id="__span-0-177"><a id="__codelineno-0-177" name="__codelineno-0-177"></a> <span class="k">match</span> <span class="n">num_channels</span><span class="p">:</span>
|
|
</span><span id="__span-0-178"><a id="__codelineno-0-178" name="__codelineno-0-178"></a> <span class="k">case</span> <span class="mi">1</span><span class="p">:</span>
|
|
</span><span id="__span-0-179"><a id="__codelineno-0-179" name="__codelineno-0-179"></a> <span class="n">tensor</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
|
</span><span id="__span-0-180"><a id="__codelineno-0-180" name="__codelineno-0-180"></a> <span class="k">case</span> <span class="mi">3</span> <span class="o">|</span> <span class="mi">4</span><span class="p">:</span>
|
|
</span><span id="__span-0-181"><a id="__codelineno-0-181" name="__codelineno-0-181"></a> <span class="n">tensor</span> <span class="o">=</span> <span class="n">tensor</span><span class="o">.</span><span class="n">permute</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">0</span><span class="p">)</span>
|
|
</span><span id="__span-0-182"><a id="__codelineno-0-182" name="__codelineno-0-182"></a> <span class="k">case</span><span class="w"> </span><span class="k">_</span><span class="p">:</span>
|
|
</span><span id="__span-0-183"><a id="__codelineno-0-183" name="__codelineno-0-183"></a> <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Unsupported number of channels: </span><span class="si">{</span><span class="n">num_channels</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
|
|
</span><span id="__span-0-184"><a id="__codelineno-0-184" name="__codelineno-0-184"></a>
|
|
</span><span id="__span-0-185"><a id="__codelineno-0-185" name="__codelineno-0-185"></a> <span class="k">return</span> <span class="n">Image</span><span class="o">.</span><span class="n">fromarray</span><span class="p">((</span><span class="n">tensor</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span> <span class="o">*</span> <span class="mi">255</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s2">"uint8"</span><span class="p">))</span> <span class="c1"># type: ignore[reportUnknownType]</span>
|
|
</span></code></pre></div></td></tr></table></div>
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</details>
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