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<div class="section" id="jasper">
<h1>Jasper<a class="headerlink" href="#jasper" title="Permalink to this headline">¶</a></h1>
<div class="section" id="id1">
<h2>Jasper<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
<span class="target" id="module-kospeech.models.jasper.model"></span><dl class="py class">
<dt id="kospeech.models.jasper.model.Jasper">
<em class="property">class </em><code class="sig-prename descclassname">kospeech.models.jasper.model.</code><code class="sig-name descname">Jasper</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">num_classes</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">version</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)">str</a></span> <span class="o">=</span> <span class="default_value">'10x5'</span></em>, <em class="sig-param"><span class="n">device</span><span class="p">:</span> <span class="n">torch.device</span> <span class="o">=</span> <span class="default_value">'cuda'</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/kospeech/models/jasper/model.html#Jasper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#kospeech.models.jasper.model.Jasper" title="Permalink to this definition">¶</a></dt>
<dd><p>Jasper: An End-to-End Convolutional Neural Acoustic Model
Jasper (Just Another Speech Recognizer), an ASR model comprised of 54 layers proposed by NVIDIA.
Jasper achieved sub 3 percent word error rate (WER) on the LibriSpeech dataset.
More details: <a class="reference external" href="https://arxiv.org/pdf/1904.03288.pdf">https://arxiv.org/pdf/1904.03288.pdf</a></p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>num_classes</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 classification</p></li>
<li><p><strong>version</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – version of jasper. Marked as BxR: B - number of blocks, R - number of sub-blocks</p></li>
<li><p><strong>device</strong> (<em>torch.device</em>) – device - ‘cuda’ or ‘cpu’</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Inputs: inputs, input_lengths, residual</dt><dd><ul class="simple">
<li><p><strong>inputs</strong>: tensor contains input sequence vector</p></li>
<li><p><strong>input_lengths</strong>: tensor contains sequence lengths</p></li>
</ul>
</dd>
<dt>Returns: output, output_lengths</dt><dd><ul class="simple">
<li><p><strong>output</strong>: tensor contains output sequence vector</p></li>
<li><p><strong>output</strong>: tensor contains output sequence lengths</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt id="kospeech.models.jasper.model.Jasper.forward">
<code class="sig-name descname">forward</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">inputs</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://pytorch.org/docs/master/tensors.html#torch.Tensor" title="(in PyTorch vmaster (1.8.0a0+4b6fea9 ))">torch.Tensor</a></span></em>, <em class="sig-param"><span class="n">input_lengths</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://pytorch.org/docs/master/tensors.html#torch.Tensor" title="(in PyTorch vmaster (1.8.0a0+4b6fea9 ))">torch.Tensor</a></span></em><span class="sig-paren">)</span> → Tuple<span class="p">[</span><a class="reference external" href="https://pytorch.org/docs/master/tensors.html#torch.Tensor" title="(in PyTorch vmaster (1.8.0a0+4b6fea9 ))">torch.Tensor</a><span class="p">, </span><a class="reference external" href="https://pytorch.org/docs/master/tensors.html#torch.Tensor" title="(in PyTorch vmaster (1.8.0a0+4b6fea9 ))">torch.Tensor</a><span class="p">]</span><a class="reference internal" href="_modules/kospeech/models/jasper/model.html#Jasper.forward"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#kospeech.models.jasper.model.Jasper.forward" title="Permalink to this definition">¶</a></dt>
<dd><p>Forward propagate a <cite>inputs</cite> for ctc training.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>inputs</strong> (<em>torch.FloatTensor</em>) – A input sequence passed to encoder. Typically for inputs this will be a padded
<cite>FloatTensor</cite> of size <code class="docutils literal notranslate"><span class="pre">(batch,</span> <span class="pre">seq_length,</span> <span class="pre">dimension)</span></code>.</p></li>
<li><p><strong>input_lengths</strong> (<em>torch.LongTensor</em>) – The length of input tensor. <code class="docutils literal notranslate"><span class="pre">(batch)</span></code></p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><ul class="simple">
<li><p>predicted_log_prob (torch.FloatTensor)s: Log probability of model predictions.</p></li>
<li><p>output_lengths (torch.LongTensor): The length of output tensor <code class="docutils literal notranslate"><span class="pre">(batch)</span></code></p></li>
</ul>
</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>(Tensor, Tensor)</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-kospeech.models.jasper.sublayers">
<span id="sublayers"></span><h2>Sublayers<a class="headerlink" href="#module-kospeech.models.jasper.sublayers" title="Permalink to this headline">¶</a></h2>
<dl class="py class">
<dt id="kospeech.models.jasper.sublayers.JasperBlock">
<em class="property">class </em><code class="sig-prename descclassname">kospeech.models.jasper.sublayers.</code><code class="sig-name descname">JasperBlock</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">num_sub_blocks</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">in_channels</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">out_channels</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">kernel_size</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">stride</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">dilation</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">bias</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)">bool</a></span> <span class="o">=</span> <span class="default_value">True</span></em>, <em class="sig-param"><span class="n">dropout_p</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)">float</a></span> <span class="o">=</span> <span class="default_value">0.2</span></em>, <em class="sig-param"><span class="n">activation</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)">str</a></span> <span class="o">=</span> <span class="default_value">'relu'</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/kospeech/models/jasper/sublayers.html#JasperBlock"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#kospeech.models.jasper.sublayers.JasperBlock" title="Permalink to this definition">¶</a></dt>
<dd><p>Jasper Block: The Jasper Block consists of R Jasper sub-block.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>num_sub_blocks</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 sub block</p></li>
<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 feature</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>) – 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>) – stride of the convolution. (default: 1)</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>) – spacing between kernel elements. (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>) – if True, adds a learnable bias to the output. (default: True)</p></li>
<li><p><strong>dropout_p</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – probability of dropout</p></li>
<li><p><strong>activation</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – activation function</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Inputs: inputs, input_lengths, residual</dt><dd><ul class="simple">
<li><p><strong>inputs</strong>: tensor contains input sequence vector</p></li>
<li><p><strong>input_lengths</strong>: tensor contains sequence lengths</p></li>
<li><p><strong>residual</strong>: tensor contains residual vector</p></li>
</ul>
</dd>
<dt>Returns: output, output_lengths</dt><dd><ul class="simple">
<li><p><strong>output</strong>: tensor contains output sequence vector</p></li>
<li><p><strong>output</strong>: tensor contains output sequence lengths</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt id="kospeech.models.jasper.sublayers.JasperSubBlock">
<em class="property">class </em><code class="sig-prename descclassname">kospeech.models.jasper.sublayers.</code><code class="sig-name descname">JasperSubBlock</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">in_channels</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">out_channels</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">kernel_size</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span></em>, <em class="sig-param"><span class="n">stride</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">dilation</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span> <span class="o">=</span> <span class="default_value">1</span></em>, <em class="sig-param"><span class="n">padding</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)">int</a></span> <span class="o">=</span> <span class="default_value">0</span></em>, <em class="sig-param"><span class="n">bias</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.9)">bool</a></span> <span class="o">=</span> <span class="default_value">False</span></em>, <em class="sig-param"><span class="n">dropout_p</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)">float</a></span> <span class="o">=</span> <span class="default_value">0.2</span></em>, <em class="sig-param"><span class="n">activation</span><span class="p">:</span> <span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)">str</a></span> <span class="o">=</span> <span class="default_value">'relu'</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/kospeech/models/jasper/sublayers.html#JasperSubBlock"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#kospeech.models.jasper.sublayers.JasperSubBlock" title="Permalink to this definition">¶</a></dt>
<dd><p>Jasper sub-block applies the following operations: a 1D-convolution, batch norm, ReLU, and dropout.</p>
<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 feature</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>) – 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>) – stride of the convolution. (default: 1)</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>) – spacing between kernel elements. (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>) – zero-padding added to both sides of the input. (default: 0)</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>) – if True, adds a learnable bias to the output. (default: False)</p></li>
<li><p><strong>dropout_p</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – probability of dropout</p></li>
<li><p><strong>activation</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – activation function</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Inputs: inputs, input_lengths, residual</dt><dd><ul class="simple">
<li><p><strong>inputs</strong>: tensor contains input sequence vector</p></li>
<li><p><strong>input_lengths</strong>: tensor contains sequence lengths</p></li>
<li><p><strong>residual</strong>: tensor contains residual vector</p></li>
</ul>
</dd>
<dt>Returns: output, output_lengths</dt><dd><ul class="simple">
<li><p><strong>output</strong>: tensor contains output sequence vector</p></li>
<li><p><strong>output</strong>: tensor contains output sequence lengths</p></li>
</ul>
</dd>
</dl>
</dd></dl>
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