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  <div class="section" id="multiheadattention">
<h1>MultiheadAttention<a class="headerlink" href="#multiheadattention" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="torch.nn.MultiheadAttention">
<em class="property">class </em><code class="sig-prename descclassname">torch.nn.</code><code class="sig-name descname">MultiheadAttention</code><span class="sig-paren">(</span><em class="sig-param">embed_dim</em>, <em class="sig-param">num_heads</em>, <em class="sig-param">dropout=0.0</em>, <em class="sig-param">bias=True</em>, <em class="sig-param">add_bias_kv=False</em>, <em class="sig-param">add_zero_attn=False</em>, <em class="sig-param">kdim=None</em>, <em class="sig-param">vdim=None</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/modules/activation.html#MultiheadAttention"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.MultiheadAttention" title="Permalink to this definition">¶</a></dt>
<dd><p>Allows the model to jointly attend to information
from different representation subspaces.
See reference: Attention Is All You Need</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><mtext>MultiHead</mtext><mo stretchy="false">(</mo><mi>Q</mi><mo separator="true">,</mo><mi>K</mi><mo separator="true">,</mo><mi>V</mi><mo stretchy="false">)</mo><mo>=</mo><mtext>Concat</mtext><mo stretchy="false">(</mo><mi>h</mi><mi>e</mi><mi>a</mi><msub><mi>d</mi><mn>1</mn></msub><mo separator="true">,</mo><mo>…</mo><mo separator="true">,</mo><mi>h</mi><mi>e</mi><mi>a</mi><msub><mi>d</mi><mi>h</mi></msub><mo stretchy="false">)</mo><msup><mi>W</mi><mi>O</mi></msup><mtext>where</mtext><mi>h</mi><mi>e</mi><mi>a</mi><msub><mi>d</mi><mi>i</mi></msub><mo>=</mo><mtext>Attention</mtext><mo stretchy="false">(</mo><mi>Q</mi><msubsup><mi>W</mi><mi>i</mi><mi>Q</mi></msubsup><mo separator="true">,</mo><mi>K</mi><msubsup><mi>W</mi><mi>i</mi><mi>K</mi></msubsup><mo separator="true">,</mo><mi>V</mi><msubsup><mi>W</mi><mi>i</mi><mi>V</mi></msubsup><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\text{MultiHead}(Q, K, V) = \text{Concat}(head_1,\dots,head_h)W^O
\text{where} head_i = \text{Attention}(QW_i^Q, KW_i^K, VW_i^V)

</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="mord text"><span class="mord">MultiHead</span></span><span class="mopen">(</span><span class="mord mathnormal">Q</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.22222em;">V</span><span class="mclose">)</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:1.1413309999999999em;vertical-align:-0.25em;"></span><span class="mord text"><span class="mord">Concat</span></span><span class="mopen">(</span><span class="mord mathnormal">h</span><span class="mord mathnormal">e</span><span class="mord mathnormal">a</span><span class="mord"><span class="mord mathnormal">d</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.30110799999999993em;"><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">1</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="minner">…</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal">h</span><span class="mord mathnormal">e</span><span class="mord mathnormal">a</span><span class="mord"><span class="mord mathnormal">d</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><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 mathnormal mtight">h</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 class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="msupsub"><span class="vlist-t"><span class="vlist-r"><span class="vlist" style="height:0.8913309999999999em;"><span style="top:-3.113em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.02778em;">O</span></span></span></span></span></span></span></span><span class="mord text"><span class="mord">where</span></span><span class="mord mathnormal">h</span><span class="mord mathnormal">e</span><span class="mord mathnormal">a</span><span class="mord"><span class="mord mathnormal">d</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 mathnormal mtight">i</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:1.236103em;vertical-align:-0.276864em;"></span><span class="mord text"><span class="mord">Attention</span></span><span class="mopen">(</span><span class="mord mathnormal">Q</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.9592389999999998em;"><span style="top:-2.4231360000000004em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span><span style="top:-3.180908em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">Q</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.276864em;"><span></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.8913309999999999em;"><span style="top:-2.4530000000000003em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span><span style="top:-3.113em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.07153em;">K</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.247em;"><span></span></span></span></span></span></span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.22222em;">V</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.8913309999999999em;"><span style="top:-2.4530000000000003em;margin-left:-0.13889em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight">i</span></span></span><span style="top:-3.113em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.22222em;">V</span></span></span></span><span class="vlist-s">​</span></span><span class="vlist-r"><span class="vlist" style="height:0.247em;"><span></span></span></span></span></span></span><span class="mclose">)</span></span></span></span></span>

</div><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>embed_dim</strong> – total dimension of the model.</p></li>
<li><p><strong>num_heads</strong> – parallel attention heads.</p></li>
<li><p><strong>dropout</strong> – a Dropout layer on attn_output_weights. Default: 0.0.</p></li>
<li><p><strong>bias</strong> – add bias as module parameter. Default: True.</p></li>
<li><p><strong>add_bias_kv</strong> – add bias to the key and value sequences at dim=0.</p></li>
<li><p><strong>add_zero_attn</strong> – add a new batch of zeros to the key and
value sequences at dim=1.</p></li>
<li><p><strong>kdim</strong> – total number of features in key. Default: None.</p></li>
<li><p><strong>vdim</strong> – total number of features in value. Default: None.</p></li>
<li><p><strong>Note</strong> – if kdim and vdim are None, they will be set to embed_dim such that</p></li>
<li><p><strong>key, and value have the same number of features.</strong> (<em>query</em><em>,</em>) – </p></li>
</ul>
</dd>
</dl>
<p>Examples:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">multihead_attn</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">MultiheadAttention</span><span class="p">(</span><span class="n">embed_dim</span><span class="p">,</span> <span class="n">num_heads</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">attn_output</span><span class="p">,</span> <span class="n">attn_output_weights</span> <span class="o">=</span> <span class="n">multihead_attn</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
</pre></div>
</div>
<dl class="method">
<dt id="torch.nn.MultiheadAttention.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param">query</em>, <em class="sig-param">key</em>, <em class="sig-param">value</em>, <em class="sig-param">key_padding_mask=None</em>, <em class="sig-param">need_weights=True</em>, <em class="sig-param">attn_mask=None</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torch/nn/modules/activation.html#MultiheadAttention.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torch.nn.MultiheadAttention.forward" title="Permalink to this definition">¶</a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>key, value</strong> (<em>query</em><em>,</em>) – map a query and a set of key-value pairs to an output.
See “Attention Is All You Need” for more details.</p></li>
<li><p><strong>key_padding_mask</strong> – if provided, specified padding elements in the key will
be ignored by the attention. When given a binary mask and a value is True,
the corresponding value on the attention layer will be ignored. When given
a byte mask and a value is non-zero, the corresponding value on the attention
layer will be ignored</p></li>
<li><p><strong>need_weights</strong> – output attn_output_weights.</p></li>
<li><p><strong>attn_mask</strong> – 2D or 3D mask that prevents attention to certain positions. A 2D mask will be broadcasted for all
the batches while a 3D mask allows to specify a different mask for the entries of each batch.</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Shape:</dt><dd><ul class="simple">
<li><p>Inputs:</p></li>
<li><p>query: <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>L</mi><mo separator="true">,</mo><mi>N</mi><mo separator="true">,</mo><mi>E</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(L, N, E)</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">L</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></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 mathnormal" style="margin-right:0.05764em;">E</span><span class="mclose">)</span></span></span></span>

</span> where L is the target sequence length, N is the batch size, E is
the embedding dimension.</p></li>
<li><p>key: <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>S</mi><mo separator="true">,</mo><mi>N</mi><mo separator="true">,</mo><mi>E</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(S, N, E)</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:0.05764em;">S</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></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 mathnormal" style="margin-right:0.05764em;">E</span><span class="mclose">)</span></span></span></span>

</span>, where S is the source sequence length, N is the batch size, E is
the embedding dimension.</p></li>
<li><p>value: <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>S</mi><mo separator="true">,</mo><mi>N</mi><mo separator="true">,</mo><mi>E</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(S, N, E)</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:0.05764em;">S</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></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 mathnormal" style="margin-right:0.05764em;">E</span><span class="mclose">)</span></span></span></span>

</span> where S is the source sequence length, N is the batch size, E is
the embedding dimension.</p></li>
<li><p>key_padding_mask: <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><mi>S</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(N, S)</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 mathnormal" style="margin-right:0.05764em;">S</span><span class="mclose">)</span></span></span></span>

</span> where N is the batch size, S is the source sequence length.
If a ByteTensor is provided, the non-zero positions will be ignored while the position
with the zero positions will be unchanged. If a BoolTensor is provided, the positions with the
value of <code class="docutils literal notranslate"><span class="pre">True</span></code> will be ignored while the position with the value of <code class="docutils literal notranslate"><span class="pre">False</span></code> will be unchanged.</p></li>
<li><p>attn_mask: 2D mask <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>L</mi><mo separator="true">,</mo><mi>S</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(L, S)</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">L</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="mclose">)</span></span></span></span>

</span> where L is the target sequence length, S is the source sequence length.
3D mask <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>∗</mo><mi>n</mi><mi>u</mi><msub><mi>m</mi><mi>h</mi></msub><mi>e</mi><mi>a</mi><mi>d</mi><mi>s</mi><mo separator="true">,</mo><mi>L</mi><mo separator="true">,</mo><mi>S</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(N*num_heads, L, S)</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="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 mathnormal">n</span><span class="mord mathnormal">u</span><span class="mord"><span class="mord mathnormal">m</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><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 mathnormal mtight">h</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="mord mathnormal">e</span><span class="mord mathnormal">a</span><span class="mord mathnormal">d</span><span class="mord mathnormal">s</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal">L</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="mclose">)</span></span></span></span>

</span> where N is the batch size, L is the target sequence length,
S is the source sequence length. attn_mask ensure that position i is allowed to attend the unmasked
positions. If a ByteTensor is provided, the non-zero positions are not allowed to attend
while the zero positions will be unchanged. If a BoolTensor is provided, positions with <code class="docutils literal notranslate"><span class="pre">True</span></code>
is not allowed to attend while <code class="docutils literal notranslate"><span class="pre">False</span></code> values will be unchanged. If a FloatTensor
is provided, it will be added to the attention weight.</p></li>
<li><p>Outputs:</p></li>
<li><p>attn_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>L</mi><mo separator="true">,</mo><mi>N</mi><mo separator="true">,</mo><mi>E</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(L, N, E)</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">L</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></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 mathnormal" style="margin-right:0.05764em;">E</span><span class="mclose">)</span></span></span></span>

</span> where L is the target sequence length, N is the batch size,
E is the embedding dimension.</p></li>
<li><p>attn_output_weights: <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><mi>L</mi><mo separator="true">,</mo><mi>S</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(N, L, S)</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 mathnormal">L</span><span class="mpunct">,</span><span class="mspace" style="margin-right:0.16666666666666666em;"></span><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="mclose">)</span></span></span></span>

</span> where N is the batch size,
L is the target sequence length, S is the source sequence length.</p></li>
</ul>
</dd>
</dl>
</dd></dl>

</dd></dl>

</div>


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