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<div class="section" id="convtranspose1d">
<h1>ConvTranspose1d<a class="headerlink" href="#convtranspose1d" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="torch.nn.ConvTranspose1d">
<em class="property">class </em><code class="sig-prename descclassname">torch.nn.</code><code class="sig-name descname">ConvTranspose1d</code><span class="sig-paren">(</span><em class="sig-param">in_channels: int, out_channels: int, kernel_size: Union[T, Tuple[T]], stride: Union[T, Tuple[T]] = 1, padding: Union[T, Tuple[T]] = 0, output_padding: Union[T, Tuple[T]] = 0, groups: int = 1, bias: bool = True, dilation: Union[T, Tuple[T]] = 1, padding_mode: str = 'zeros'</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/modules/conv.html#ConvTranspose1d"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.ConvTranspose1d" title="Permalink to this definition">¶</a></dt>
<dd><p>Applies a 1D transposed convolution operator over an input image
composed of several input planes.</p>
<p>This module can be seen as the gradient of Conv1d with respect to its input.
It is also known as a fractionally-strided convolution or
a deconvolution (although it is not an actual deconvolution operation).</p>
<p>This module supports <a class="reference internal" href="../notes/cuda.html#tf32-on-ampere"><span class="std std-ref">TensorFloat32</span></a>.</p>
<ul>
<li><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">stride</span></code> controls the stride for the cross-correlation.</p></li>
<li><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">padding</span></code> controls the amount of implicit zero-paddings on both
sides for <code class="docutils literal notranslate"><span class="pre">dilation</span> <span class="pre">*</span> <span class="pre">(kernel_size</span> <span class="pre">-</span> <span class="pre">1)</span> <span class="pre">-</span> <span class="pre">padding</span></code> number of points. See note
below for details.</p></li>
<li><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_padding</span></code> controls the additional size added to one side
of the output shape. See note below for details.</p></li>
<li><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">dilation</span></code> controls the spacing between the kernel points; also known as the à trous algorithm.
It is harder to describe, but this <a class="reference external" href="https://github.com/vdumoulin/conv_arithmetic/blob/master/README.md">link</a> has a nice visualization of what <code class="xref py py-attr docutils literal notranslate"><span class="pre">dilation</span></code> does.</p></li>
<li><p><code class="xref py py-attr docutils literal notranslate"><span class="pre">groups</span></code> controls the connections between inputs and outputs.
<code class="xref py py-attr docutils literal notranslate"><span class="pre">in_channels</span></code> and <code class="xref py py-attr docutils literal notranslate"><span class="pre">out_channels</span></code> must both be divisible by
<code class="xref py py-attr docutils literal notranslate"><span class="pre">groups</span></code>. For example,</p>
<blockquote>
<div><ul class="simple">
<li><p>At groups=1, all inputs are convolved to all outputs.</p></li>
<li><p>At groups=2, the operation becomes equivalent to having two conv
layers side by side, each seeing half the input channels,
and producing half the output channels, and both subsequently
concatenated.</p></li>
<li><p>At groups= <code class="xref py py-attr docutils literal notranslate"><span class="pre">in_channels</span></code>, each input channel is convolved with
its own set of filters (of size
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo fence="true">⌊</mo><mfrac><mrow><mi>o</mi><mi>u</mi><mi>t</mi><mi mathvariant="normal">_</mi><mi>c</mi><mi>h</mi><mi>a</mi><mi>n</mi><mi>n</mi><mi>e</mi><mi>l</mi><mi>s</mi></mrow><mrow><mi>i</mi><mi>n</mi><mi mathvariant="normal">_</mi><mi>c</mi><mi>h</mi><mi>a</mi><mi>n</mi><mi>n</mi><mi>e</mi><mi>l</mi><mi>s</mi></mrow></mfrac><mo fence="true">⌋</mo></mrow><annotation encoding="application/x-tex">\left\lfloor\frac{out\_channels}{in\_channels}\right\rfloor</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.80002em;vertical-align:-0.65002em;"></span><span class="minner"><span class="mopen delimcenter" style="top:0em;"><span class="delimsizing size2">⌊</span></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.013108em;"><span style="top:-2.6550000000000002em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mord mathnormal mtight">n</span><span class="mord mtight" style="margin-right:0.02778em;">_</span><span class="mord mathnormal mtight">c</span><span class="mord mathnormal mtight">h</span><span class="mord mathnormal mtight">a</span><span class="mord mathnormal mtight">n</span><span class="mord mathnormal mtight">n</span><span class="mord mathnormal mtight">e</span><span class="mord mathnormal mtight" style="margin-right:0.01968em;">l</span><span class="mord mathnormal mtight">s</span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.527em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">t</span><span class="mord mtight" style="margin-right:0.02778em;">_</span><span class="mord mathnormal mtight">c</span><span class="mord mathnormal mtight">h</span><span class="mord mathnormal mtight">a</span><span class="mord mathnormal mtight">n</span><span class="mord mathnormal mtight">n</span><span class="mord mathnormal mtight">e</span><span class="mord mathnormal mtight" style="margin-right:0.01968em;">l</span><span class="mord mathnormal mtight">s</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.5619999999999999em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mclose delimcenter" style="top:0em;"><span class="delimsizing size2">⌋</span></span></span></span></span></span>
</span>).</p></li>
</ul>
</div></blockquote>
</li>
</ul>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Depending of the size of your kernel, several (of the last)
columns of the input might be lost, because it is a valid <a class="reference external" href="https://en.wikipedia.org/wiki/Cross-correlation">cross-correlation</a>,
and not a full <a class="reference external" href="https://en.wikipedia.org/wiki/Cross-correlation">cross-correlation</a>.
It is up to the user to add proper padding.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The <code class="xref py py-attr docutils literal notranslate"><span class="pre">padding</span></code> argument effectively adds <code class="docutils literal notranslate"><span class="pre">dilation</span> <span class="pre">*</span> <span class="pre">(kernel_size</span> <span class="pre">-</span> <span class="pre">1)</span> <span class="pre">-</span> <span class="pre">padding</span></code>
amount of zero padding to both sizes of the input. This is set so that
when a <a class="reference internal" href="torch.nn.Conv1d.html#torch.nn.Conv1d" title="torch.nn.Conv1d"><code class="xref py py-class docutils literal notranslate"><span class="pre">Conv1d</span></code></a> and a <a class="reference internal" href="#torch.nn.ConvTranspose1d" title="torch.nn.ConvTranspose1d"><code class="xref py py-class docutils literal notranslate"><span class="pre">ConvTranspose1d</span></code></a>
are initialized with same parameters, they are inverses of each other in
regard to the input and output shapes. However, when <code class="docutils literal notranslate"><span class="pre">stride</span> <span class="pre">></span> <span class="pre">1</span></code>,
<a class="reference internal" href="torch.nn.Conv1d.html#torch.nn.Conv1d" title="torch.nn.Conv1d"><code class="xref py py-class docutils literal notranslate"><span class="pre">Conv1d</span></code></a> maps multiple input shapes to the same output
shape. <code class="xref py py-attr docutils literal notranslate"><span class="pre">output_padding</span></code> is provided to resolve this ambiguity by
effectively increasing the calculated output shape on one side. Note
that <code class="xref py py-attr docutils literal notranslate"><span class="pre">output_padding</span></code> is only used to find output shape, but does
not actually add zero-padding to output.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>In some circumstances when using the CUDA backend with CuDNN, this operator
may select a nondeterministic algorithm to increase performance. If this is
undesirable, you can try to make the operation deterministic (potentially at
a performance cost) by setting <code class="docutils literal notranslate"><span class="pre">torch.backends.cudnn.deterministic</span> <span class="pre">=</span>
<span class="pre">True</span></code>.
Please see the notes on <a class="reference internal" href="../notes/randomness.html"><span class="doc">Reproducibility</span></a> for background.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>in_channels</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a>) – Number of channels in the input image</p></li>
<li><p><strong>out_channels</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a>) – Number of channels produced by the convolution</p></li>
<li><p><strong>kernel_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a>) – Size of the convolving kernel</p></li>
<li><p><strong>stride</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em>, </em><em>optional</em>) – Stride of the convolution. Default: 1</p></li>
<li><p><strong>padding</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em>, </em><em>optional</em>) – <code class="docutils literal notranslate"><span class="pre">dilation</span> <span class="pre">*</span> <span class="pre">(kernel_size</span> <span class="pre">-</span> <span class="pre">1)</span> <span class="pre">-</span> <span class="pre">padding</span></code> zero-padding
will be added to both sides of the input. Default: 0</p></li>
<li><p><strong>output_padding</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em>, </em><em>optional</em>) – Additional size added to one side
of the output shape. Default: 0</p></li>
<li><p><strong>groups</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em>, </em><em>optional</em>) – Number of blocked connections from input channels to output channels. Default: 1</p></li>
<li><p><strong>bias</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)"><em>bool</em></a><em>, </em><em>optional</em>) – If <code class="docutils literal notranslate"><span class="pre">True</span></code>, adds a learnable bias to the output. Default: <code class="docutils literal notranslate"><span class="pre">True</span></code></p></li>
<li><p><strong>dilation</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.9)"><em>tuple</em></a><em>, </em><em>optional</em>) – Spacing between kernel elements. Default: 1</p></li>
</ul>
</dd>
</dl>
<dl>
<dt>Shape:</dt><dd><ul>
<li><p>Input: <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="false">(</mo><mi>N</mi><mo separator="true">,</mo><msub><mi>C</mi><mrow><mi>i</mi><mi>n</mi></mrow></msub><mo separator="true">,</mo><msub><mi>L</mi><mrow><mi>i</mi><mi>n</mi></mrow></msub><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(N, C_{in}, L_{in})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.10903em;">N</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.07153em;">C</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-left:-0.07153em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mord mathnormal mtight">n</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mord mathnormal">L</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mord mathnormal mtight">n</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mclose">)</span></span></span></span>
</span></p></li>
<li><p>Output: <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="false">(</mo><mi>N</mi><mo separator="true">,</mo><msub><mi>C</mi><mrow><mi>o</mi><mi>u</mi><mi>t</mi></mrow></msub><mo separator="true">,</mo><msub><mi>L</mi><mrow><mi>o</mi><mi>u</mi><mi>t</mi></mrow></msub><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(N, C_{out}, L_{out})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">(</span><span class="mord mathnormal" style="margin-right:0.10903em;">N</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.07153em;">C</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:-0.07153em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mord mathnormal">L</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mclose">)</span></span></span></span>
</span> where</p>
<div class="math">
<span class="katex-display"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML" display="block"><semantics><mrow><msub><mi>L</mi><mrow><mi>o</mi><mi>u</mi><mi>t</mi></mrow></msub><mo>=</mo><mo stretchy="false">(</mo><msub><mi>L</mi><mrow><mi>i</mi><mi>n</mi></mrow></msub><mo>−</mo><mn>1</mn><mo stretchy="false">)</mo><mo>×</mo><mtext>stride</mtext><mo>−</mo><mn>2</mn><mo>×</mo><mtext>padding</mtext><mo>+</mo><mtext>dilation</mtext><mo>×</mo><mo stretchy="false">(</mo><mtext>kernel_size</mtext><mo>−</mo><mn>1</mn><mo stretchy="false">)</mo><mo>+</mo><mtext>output_padding</mtext><mo>+</mo><mn>1</mn></mrow><annotation encoding="application/x-tex">L_{out} = (L_{in} - 1) \times \text{stride} - 2 \times \text{padding} + \text{dilation}
\times (\text{kernel\_size} - 1) + \text{output\_padding} + 1
</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.83333em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal">L</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.2805559999999999em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">t</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mopen">(</span><span class="mord"><span class="mord mathnormal">L</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.31166399999999994em;"><span style="top:-2.5500000000000003em;margin-left:0em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight">i</span><span class="mord mathnormal mtight">n</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord">1</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.77777em;vertical-align:-0.08333em;"></span><span class="mord text"><span class="mord">stride</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.72777em;vertical-align:-0.08333em;"></span><span class="mord">2</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.8888799999999999em;vertical-align:-0.19444em;"></span><span class="mord text"><span class="mord">padding</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.77777em;vertical-align:-0.08333em;"></span><span class="mord text"><span class="mord">dilation</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">×</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1.06em;vertical-align:-0.31em;"></span><span class="mopen">(</span><span class="mord text"><span class="mord">kernel_size</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord">1</span><span class="mclose">)</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:1.00444em;vertical-align:-0.31em;"></span><span class="mord text"><span class="mord">output_padding</span></span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span></span><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">1</span></span></span></span></span>
</div></li>
</ul>
</dd>
</dl>
<dl class="field-list simple">
<dt class="field-odd">Variables</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>~ConvTranspose1d.weight</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – the learnable weights of the module of shape
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="false">(</mo><mtext>in_channels</mtext><mo separator="true">,</mo><mfrac><mtext>out_channels</mtext><mtext>groups</mtext></mfrac><mo separator="true">,</mo></mrow><annotation encoding="application/x-tex">(\text{in\_channels}, \frac{\text{out\_channels}}{\text{groups}},</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.4942159999999998em;vertical-align:-0.481108em;"></span><span class="mopen">(</span><span class="mord text"><span class="mord">in_channels</span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.013108em;"><span style="top:-2.6550000000000002em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord text mtight"><span class="mord mtight">groups</span></span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.527em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord text mtight"><span class="mord mtight">out_channels</span></span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.481108em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span><span class="mpunct">,</span></span></span></span>
</span>
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mtext>kernel_size</mtext><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\text{kernel\_size})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.06em;vertical-align:-0.31em;"></span><span class="mord text"><span class="mord">kernel_size</span></span><span class="mclose">)</span></span></span></span>
</span>.
The values of these weights are sampled from
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="script">U</mi><mo stretchy="false">(</mo><mo>−</mo><msqrt><mi>k</mi></msqrt><mo separator="true">,</mo><msqrt><mi>k</mi></msqrt><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\mathcal{U}(-\sqrt{k}, \sqrt{k})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.18222em;vertical-align:-0.25em;"></span><span class="mord"><span class="mord mathcal" style="margin-right:0.09931em;">U</span></span><span class="mopen">(</span><span class="mord">−</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.93222em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal" style="margin-right:0.03148em;">k</span></span></span><span style="top:-2.89222em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg width='400em' height='1.08em' viewBox='0 0 400000 1080' preserveAspectRatio='xMinYMin slice'><path d='M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z'/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.10777999999999999em;"><span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.93222em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal" style="margin-right:0.03148em;">k</span></span></span><span style="top:-2.89222em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg width='400em' height='1.08em' viewBox='0 0 400000 1080' preserveAspectRatio='xMinYMin slice'><path d='M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z'/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.10777999999999999em;"><span></span></span></span></span></span><span class="mclose">)</span></span></span></span>
</span> where
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi><mo>=</mo><mfrac><mrow><mi>g</mi><mi>r</mi><mi>o</mi><mi>u</mi><mi>p</mi><mi>s</mi></mrow><mrow><msub><mi>C</mi><mtext>out</mtext></msub><mo>∗</mo><mtext>kernel_size</mtext></mrow></mfrac></mrow><annotation encoding="application/x-tex">k = \frac{groups}{C_\text{out} * \text{kernel\_size}}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.03148em;">k</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1.3094999999999999em;vertical-align:-0.5619999999999999em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.7475em;"><span style="top:-2.6550000000000002em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.07153em;">C</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.29634285714285713em;"><span style="top:-2.357em;margin-left:-0.07153em;margin-right:0.07142857142857144em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size3 size1 mtight"><span class="mord text mtight"><span class="mord mtight">out</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.143em;"><span></span></span></span></span></span></span><span class="mbin mtight">∗</span><span class="mord text mtight"><span class="mord mtight">kernel_size</span></span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.446108em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.03588em;">g</span><span class="mord mathnormal mtight" style="margin-right:0.02778em;">r</span><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">p</span><span class="mord mathnormal mtight">s</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.5619999999999999em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span>
</span></p></li>
<li><p><strong>~ConvTranspose1d.bias</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a>) – the learnable bias of the module of shape (out_channels).
If <code class="xref py py-attr docutils literal notranslate"><span class="pre">bias</span></code> is <code class="docutils literal notranslate"><span class="pre">True</span></code>, then the values of these weights are
sampled from <span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi mathvariant="script">U</mi><mo stretchy="false">(</mo><mo>−</mo><msqrt><mi>k</mi></msqrt><mo separator="true">,</mo><msqrt><mi>k</mi></msqrt><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\mathcal{U}(-\sqrt{k}, \sqrt{k})</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.18222em;vertical-align:-0.25em;"></span><span class="mord"><span class="mord mathcal" style="margin-right:0.09931em;">U</span></span><span class="mopen">(</span><span class="mord">−</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.93222em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal" style="margin-right:0.03148em;">k</span></span></span><span style="top:-2.89222em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg width='400em' height='1.08em' viewBox='0 0 400000 1080' preserveAspectRatio='xMinYMin slice'><path d='M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z'/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.10777999999999999em;"><span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.93222em;"><span class="svg-align" style="top:-3em;"><span class="pstrut" style="height:3em;"></span><span class="mord" style="padding-left:0.833em;"><span class="mord mathnormal" style="margin-right:0.03148em;">k</span></span></span><span style="top:-2.89222em;"><span class="pstrut" style="height:3em;"></span><span class="hide-tail" style="min-width:0.853em;height:1.08em;"><svg width='400em' height='1.08em' viewBox='0 0 400000 1080' preserveAspectRatio='xMinYMin slice'><path d='M95,702
c-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14
c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54
c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10
s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429
c69,-144,104.5,-217.7,106.5,-221
l0 -0
c5.3,-9.3,12,-14,20,-14
H400000v40H845.2724
s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7
c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47z
M834 80h400000v40h-400000z'/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.10777999999999999em;"><span></span></span></span></span></span><span class="mclose">)</span></span></span></span>
</span> where
<span class="math"><span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>k</mi><mo>=</mo><mfrac><mrow><mi>g</mi><mi>r</mi><mi>o</mi><mi>u</mi><mi>p</mi><mi>s</mi></mrow><mrow><msub><mi>C</mi><mtext>out</mtext></msub><mo>∗</mo><mtext>kernel_size</mtext></mrow></mfrac></mrow><annotation encoding="application/x-tex">k = \frac{groups}{C_\text{out} * \text{kernel\_size}}</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.69444em;vertical-align:0em;"></span><span class="mord mathnormal" style="margin-right:0.03148em;">k</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:1.3094999999999999em;vertical-align:-0.5619999999999999em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.7475em;"><span style="top:-2.6550000000000002em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.07153em;">C</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.29634285714285713em;"><span style="top:-2.357em;margin-left:-0.07153em;margin-right:0.07142857142857144em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size3 size1 mtight"><span class="mord text mtight"><span class="mord mtight">out</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.143em;"><span></span></span></span></span></span></span><span class="mbin mtight">∗</span><span class="mord text mtight"><span class="mord mtight">kernel_size</span></span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.446108em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mathnormal mtight" style="margin-right:0.03588em;">g</span><span class="mord mathnormal mtight" style="margin-right:0.02778em;">r</span><span class="mord mathnormal mtight">o</span><span class="mord mathnormal mtight">u</span><span class="mord mathnormal mtight">p</span><span class="mord mathnormal mtight">s</span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.5619999999999999em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span>
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