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<li class="toctree-l1 current"><a class="current reference internal" href="#">Installation</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="#install-cuda-toolkit-and-cudnn">(0) Install CUDA toolkit and cuDNN</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#install-pytorch-and-torchaudio">(1) Install PyTorch and torchaudio</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#install-k2">(2) Install k2</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#install-lhotse">(3) Install lhotse</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#download-icefall">(4) Download icefall</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#installation-example">Installation example</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="#create-a-virtual-environment">(1) Create a virtual environment</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#activate-your-virtual-environment">(2) Activate your virtual environment</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#id1">(3) Install k2</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#id2">(4) Install lhotse</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#id3">(5) Download icefall</a></li>
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</ul>
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</li>
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<li class="toctree-l2"><a class="reference internal" href="#test-your-installation">Test Your Installation</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="#data-preparation">Data preparation</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#training">Training</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#decoding">Decoding</a></li>
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<li class="toctree-l2"><a class="reference internal" href="#youtube-video">YouTube Video</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../faqs.html">Frequently Asked Questions (FAQs)</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../model-export/index.html">Model export</a></li>
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<a href="https://github.com/k2-fsa/icefall/blob/master/docs/source/installation/index.rst" class="fa fa-github"> Edit on GitHub</a>
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<section id="installation">
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<span id="install-icefall"></span><h1>Installation<a class="headerlink" href="#installation" title="Permalink to this heading"></a></h1>
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<p><code class="docutils literal notranslate"><span class="pre">icefall</span></code> depends on <a class="reference external" href="https://github.com/k2-fsa/k2">k2</a> and
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<a class="reference external" href="https://github.com/lhotse-speech/lhotse">lhotse</a>.</p>
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<p>We recommend that you use the following steps to install the dependencies.</p>
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<ul class="simple">
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<li><ol class="arabic simple" start="0">
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<li><p>Install CUDA toolkit and cuDNN</p></li>
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</ol>
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</li>
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<li><ol class="arabic simple">
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<li><p>Install PyTorch and torchaudio</p></li>
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</ol>
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</li>
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<li><ol class="arabic simple" start="2">
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<li><p>Install k2</p></li>
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</ol>
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</li>
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<li><ol class="arabic simple" start="3">
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<li><p>Install lhotse</p></li>
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</ol>
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</li>
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</ul>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>99% users who have issues about the installation are using conda.</p>
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</div>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>99% users who have issues about the installation are using conda.</p>
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</div>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>99% users who have issues about the installation are using conda.</p>
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</div>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>We suggest that you use <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span></code> to install PyTorch.</p>
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<p>You can use the following command to create a virutal environment in Python:</p>
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<blockquote>
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<div><div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python3<span class="w"> </span>-m<span class="w"> </span>venv<span class="w"> </span>./my_env
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<span class="nb">source</span><span class="w"> </span>./my_env/bin/activate
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</pre></div>
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</div>
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</div></blockquote>
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</div>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>Installation order matters.</p>
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</div>
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<section id="install-cuda-toolkit-and-cudnn">
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<h2>(0) Install CUDA toolkit and cuDNN<a class="headerlink" href="#install-cuda-toolkit-and-cudnn" title="Permalink to this heading"></a></h2>
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<p>Please refer to
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<a class="reference external" href="https://k2-fsa.github.io/k2/installation/cuda-cudnn.html">https://k2-fsa.github.io/k2/installation/cuda-cudnn.html</a>
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to install CUDA and cuDNN.</p>
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</section>
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<section id="install-pytorch-and-torchaudio">
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<h2>(1) Install PyTorch and torchaudio<a class="headerlink" href="#install-pytorch-and-torchaudio" title="Permalink to this heading"></a></h2>
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<p>Please refer <a class="reference external" href="https://pytorch.org/">https://pytorch.org/</a> to install PyTorch
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and torchaudio.</p>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>You can also go to <a class="reference external" href="https://download.pytorch.org/whl/torch_stable.html">https://download.pytorch.org/whl/torch_stable.html</a>
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to download pre-compiled wheels and install them.</p>
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</div>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>Please install torch and torchaudio at the same time.</p>
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</div>
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</section>
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<section id="install-k2">
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<h2>(2) Install k2<a class="headerlink" href="#install-k2" title="Permalink to this heading"></a></h2>
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<p>Please refer to <a class="reference external" href="https://k2-fsa.github.io/k2/installation/index.html">https://k2-fsa.github.io/k2/installation/index.html</a>
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to install <code class="docutils literal notranslate"><span class="pre">k2</span></code>.</p>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p>Please don’t change your installed PyTorch after you have installed k2.</p>
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</div>
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<div class="admonition note">
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<p class="admonition-title">Note</p>
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<p>We suggest that you install k2 from source by following
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<a class="reference external" href="https://k2-fsa.github.io/k2/installation/from_source.html">https://k2-fsa.github.io/k2/installation/from_source.html</a>
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or
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<a class="reference external" href="https://k2-fsa.github.io/k2/installation/for_developers.html">https://k2-fsa.github.io/k2/installation/for_developers.html</a>.</p>
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</div>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>Please always install the latest version of k2.</p>
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</div>
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</section>
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<section id="install-lhotse">
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<h2>(3) Install lhotse<a class="headerlink" href="#install-lhotse" title="Permalink to this heading"></a></h2>
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<p>Please refer to <a class="reference external" href="https://lhotse.readthedocs.io/en/latest/getting-started.html#installation">https://lhotse.readthedocs.io/en/latest/getting-started.html#installation</a>
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to install <code class="docutils literal notranslate"><span class="pre">lhotse</span></code>.</p>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>We strongly recommend you to use:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">git</span><span class="o">+</span><span class="n">https</span><span class="p">:</span><span class="o">//</span><span class="n">github</span><span class="o">.</span><span class="n">com</span><span class="o">/</span><span class="n">lhotse</span><span class="o">-</span><span class="n">speech</span><span class="o">/</span><span class="n">lhotse</span>
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</pre></div>
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</div>
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<p>to install the latest version of lhotse.</p>
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</div>
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</section>
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<section id="download-icefall">
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<h2>(4) Download icefall<a class="headerlink" href="#download-icefall" title="Permalink to this heading"></a></h2>
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<p><code class="docutils literal notranslate"><span class="pre">icefall</span></code> is a collection of Python scripts; what you need is to download it
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and set the environment variable <code class="docutils literal notranslate"><span class="pre">PYTHONPATH</span></code> to point to it.</p>
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<p>Assume you want to place <code class="docutils literal notranslate"><span class="pre">icefall</span></code> in the folder <code class="docutils literal notranslate"><span class="pre">/tmp</span></code>. The
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following commands show you how to setup <code class="docutils literal notranslate"><span class="pre">icefall</span></code>:</p>
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">cd</span><span class="w"> </span>/tmp
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git<span class="w"> </span>clone<span class="w"> </span>https://github.com/k2-fsa/icefall
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<span class="nb">cd</span><span class="w"> </span>icefall
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pip<span class="w"> </span>install<span class="w"> </span>-r<span class="w"> </span>requirements.txt
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<span class="nb">export</span><span class="w"> </span><span class="nv">PYTHONPATH</span><span class="o">=</span>/tmp/icefall:<span class="nv">$PYTHONPATH</span>
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</pre></div>
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</div>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>You can put several versions of <code class="docutils literal notranslate"><span class="pre">icefall</span></code> in the same virtual environment.
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To switch among different versions of <code class="docutils literal notranslate"><span class="pre">icefall</span></code>, just set <code class="docutils literal notranslate"><span class="pre">PYTHONPATH</span></code>
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to point to the version you want.</p>
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</div>
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</section>
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<section id="installation-example">
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<h2>Installation example<a class="headerlink" href="#installation-example" title="Permalink to this heading"></a></h2>
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<p>The following shows an example about setting up the environment.</p>
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<section id="create-a-virtual-environment">
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<h3>(1) Create a virtual environment<a class="headerlink" href="#create-a-virtual-environment" title="Permalink to this heading"></a></h3>
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span>virtualenv<span class="w"> </span>-p<span class="w"> </span>python3.8<span class="w"> </span>test-icefall
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created<span class="w"> </span>virtual<span class="w"> </span>environment<span class="w"> </span>CPython3.8.6.final.0-64<span class="w"> </span><span class="k">in</span><span class="w"> </span>1540ms
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<span class="w"> </span>creator<span class="w"> </span>CPython3Posix<span class="o">(</span><span class="nv">dest</span><span class="o">=</span>/ceph-fj/fangjun/test-icefall,<span class="w"> </span><span class="nv">clear</span><span class="o">=</span>False,<span class="w"> </span><span class="nv">no_vcs_ignore</span><span class="o">=</span>False,<span class="w"> </span><span class="nv">global</span><span class="o">=</span>False<span class="o">)</span>
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<span class="w"> </span>seeder<span class="w"> </span>FromAppData<span class="o">(</span><span class="nv">download</span><span class="o">=</span>False,<span class="w"> </span><span class="nv">pip</span><span class="o">=</span>bundle,<span class="w"> </span><span class="nv">setuptools</span><span class="o">=</span>bundle,<span class="w"> </span><span class="nv">wheel</span><span class="o">=</span>bundle,<span class="w"> </span><span class="nv">via</span><span class="o">=</span>copy,<span class="w"> </span><span class="nv">app_data_dir</span><span class="o">=</span>/root/fangjun/.local/share/v
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irtualenv<span class="o">)</span>
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<span class="w"> </span>added<span class="w"> </span>seed<span class="w"> </span>packages:<span class="w"> </span><span class="nv">pip</span><span class="o">==</span><span class="m">21</span>.1.3,<span class="w"> </span><span class="nv">setuptools</span><span class="o">==</span><span class="m">57</span>.4.0,<span class="w"> </span><span class="nv">wheel</span><span class="o">==</span><span class="m">0</span>.36.2
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<span class="w"> </span>activators<span class="w"> </span>BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator
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</pre></div>
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</div>
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</section>
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<section id="activate-your-virtual-environment">
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<h3>(2) Activate your virtual environment<a class="headerlink" href="#activate-your-virtual-environment" title="Permalink to this heading"></a></h3>
|
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nb">source</span><span class="w"> </span>test-icefall/bin/activate
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</pre></div>
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</div>
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</section>
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<section id="id1">
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<h3>(3) Install k2<a class="headerlink" href="#id1" title="Permalink to this heading"></a></h3>
|
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span><span class="nv">k2</span><span class="o">==</span><span class="m">1</span>.4.dev20210822+cpu.torch1.9.0<span class="w"> </span>-f<span class="w"> </span>https://k2-fsa.org/nightly/index.html
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Looking<span class="w"> </span><span class="k">in</span><span class="w"> </span>links:<span class="w"> </span>https://k2-fsa.org/nightly/index.html
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Collecting<span class="w"> </span><span class="nv">k2</span><span class="o">==</span><span class="m">1</span>.4.dev20210822+cpu.torch1.9.0
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<span class="w"> </span>Downloading<span class="w"> </span>https://k2-fsa.org/nightly/whl/k2-1.4.dev20210822%2Bcpu.torch1.9.0-cp38-cp38-linux_x86_64.whl<span class="w"> </span><span class="o">(</span><span class="m">1</span>.6<span class="w"> </span>MB<span class="o">)</span>
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<span class="w"> </span><span class="p">|</span>________________________________<span class="p">|</span><span class="w"> </span><span class="m">1</span>.6<span class="w"> </span>MB<span class="w"> </span><span class="m">185</span><span class="w"> </span>kB/s
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Collecting<span class="w"> </span>graphviz
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<span class="w"> </span>Downloading<span class="w"> </span>graphviz-0.17-py3-none-any.whl<span class="w"> </span><span class="o">(</span><span class="m">18</span><span class="w"> </span>kB<span class="o">)</span>
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Collecting<span class="w"> </span><span class="nv">torch</span><span class="o">==</span><span class="m">1</span>.9.0
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<span class="w"> </span>Using<span class="w"> </span>cached<span class="w"> </span>torch-1.9.0-cp38-cp38-manylinux1_x86_64.whl<span class="w"> </span><span class="o">(</span><span class="m">831</span>.4<span class="w"> </span>MB<span class="o">)</span>
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Collecting<span class="w"> </span>typing-extensions
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<span class="w"> </span>Using<span class="w"> </span>cached<span class="w"> </span>typing_extensions-3.10.0.0-py3-none-any.whl<span class="w"> </span><span class="o">(</span><span class="m">26</span><span class="w"> </span>kB<span class="o">)</span>
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Installing<span class="w"> </span>collected<span class="w"> </span>packages:<span class="w"> </span>typing-extensions,<span class="w"> </span>torch,<span class="w"> </span>graphviz,<span class="w"> </span>k2
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||
Successfully<span class="w"> </span>installed<span class="w"> </span>graphviz-0.17<span class="w"> </span>k2-1.4.dev20210822+cpu.torch1.9.0<span class="w"> </span>torch-1.9.0<span class="w"> </span>typing-extensions-3.10.0.0
|
||
</pre></div>
|
||
</div>
|
||
<div class="admonition warning">
|
||
<p class="admonition-title">Warning</p>
|
||
<p>We choose to install a CPU version of k2 for testing. You would probably want to install
|
||
a CUDA version of k2.</p>
|
||
</div>
|
||
</section>
|
||
<section id="id2">
|
||
<h3>(4) Install lhotse<a class="headerlink" href="#id2" title="Permalink to this heading"></a></h3>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ pip install git+https://github.com/lhotse-speech/lhotse
|
||
|
||
Collecting git+https://github.com/lhotse-speech/lhotse
|
||
Cloning https://github.com/lhotse-speech/lhotse to /tmp/pip-req-build-7b1b76ge
|
||
Running command git clone -q https://github.com/lhotse-speech/lhotse /tmp/pip-req-build-7b1b76ge
|
||
Collecting audioread>=2.1.9
|
||
Using cached audioread-2.1.9-py3-none-any.whl
|
||
Collecting SoundFile>=0.10
|
||
Using cached SoundFile-0.10.3.post1-py2.py3-none-any.whl (21 kB)
|
||
Collecting click>=7.1.1
|
||
Using cached click-8.0.1-py3-none-any.whl (97 kB)
|
||
Collecting cytoolz>=0.10.1
|
||
Using cached cytoolz-0.11.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB)
|
||
Collecting dataclasses
|
||
Using cached dataclasses-0.6-py3-none-any.whl (14 kB)
|
||
Collecting h5py>=2.10.0
|
||
Downloading h5py-3.4.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (4.5 MB)
|
||
|________________________________| 4.5 MB 684 kB/s
|
||
Collecting intervaltree>=3.1.0
|
||
Using cached intervaltree-3.1.0-py2.py3-none-any.whl
|
||
Collecting lilcom>=1.1.0
|
||
Using cached lilcom-1.1.1-cp38-cp38-linux_x86_64.whl
|
||
Collecting numpy>=1.18.1
|
||
Using cached numpy-1.21.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (15.8 MB)
|
||
Collecting packaging
|
||
Using cached packaging-21.0-py3-none-any.whl (40 kB)
|
||
Collecting pyyaml>=5.3.1
|
||
Using cached PyYAML-5.4.1-cp38-cp38-manylinux1_x86_64.whl (662 kB)
|
||
Collecting tqdm
|
||
Downloading tqdm-4.62.1-py2.py3-none-any.whl (76 kB)
|
||
|________________________________| 76 kB 2.7 MB/s
|
||
Collecting torchaudio==0.9.0
|
||
Downloading torchaudio-0.9.0-cp38-cp38-manylinux1_x86_64.whl (1.9 MB)
|
||
|________________________________| 1.9 MB 73.1 MB/s
|
||
Requirement already satisfied: torch==1.9.0 in ./test-icefall/lib/python3.8/site-packages (from torchaudio==0.9.0->lhotse===0.8.0.dev
|
||
-2a1410b-clean) (1.9.0)
|
||
Requirement already satisfied: typing-extensions in ./test-icefall/lib/python3.8/site-packages (from torch==1.9.0->torchaudio==0.9.0-
|
||
>lhotse===0.8.0.dev-2a1410b-clean) (3.10.0.0)
|
||
Collecting toolz>=0.8.0
|
||
Using cached toolz-0.11.1-py3-none-any.whl (55 kB)
|
||
Collecting sortedcontainers<3.0,>=2.0
|
||
Using cached sortedcontainers-2.4.0-py2.py3-none-any.whl (29 kB)
|
||
Collecting cffi>=1.0
|
||
Using cached cffi-1.14.6-cp38-cp38-manylinux1_x86_64.whl (411 kB)
|
||
Collecting pycparser
|
||
Using cached pycparser-2.20-py2.py3-none-any.whl (112 kB)
|
||
Collecting pyparsing>=2.0.2
|
||
Using cached pyparsing-2.4.7-py2.py3-none-any.whl (67 kB)
|
||
Building wheels for collected packages: lhotse
|
||
Building wheel for lhotse (setup.py) ... done
|
||
Created wheel for lhotse: filename=lhotse-0.8.0.dev_2a1410b_clean-py3-none-any.whl size=342242 sha256=f683444afa4dc0881133206b4646a
|
||
9d0f774224cc84000f55d0a67f6e4a37997
|
||
Stored in directory: /tmp/pip-ephem-wheel-cache-ftu0qysz/wheels/7f/7a/8e/a0bf241336e2e3cb573e1e21e5600952d49f5162454f2e612f
|
||
WARNING: Built wheel for lhotse is invalid: Metadata 1.2 mandates PEP 440 version, but '0.8.0.dev-2a1410b-clean' is not
|
||
Failed to build lhotse
|
||
Installing collected packages: pycparser, toolz, sortedcontainers, pyparsing, numpy, cffi, tqdm, torchaudio, SoundFile, pyyaml, packa
|
||
ging, lilcom, intervaltree, h5py, dataclasses, cytoolz, click, audioread, lhotse
|
||
Running setup.py install for lhotse ... done
|
||
DEPRECATION: lhotse was installed using the legacy 'setup.py install' method, because a wheel could not be built for it. A possible
|
||
replacement is to fix the wheel build issue reported above. You can find discussion regarding this at https://github.com/pypa/pip/is
|
||
sues/8368.
|
||
Successfully installed SoundFile-0.10.3.post1 audioread-2.1.9 cffi-1.14.6 click-8.0.1 cytoolz-0.11.0 dataclasses-0.6 h5py-3.4.0 inter
|
||
valtree-3.1.0 lhotse-0.8.0.dev-2a1410b-clean lilcom-1.1.1 numpy-1.21.2 packaging-21.0 pycparser-2.20 pyparsing-2.4.7 pyyaml-5.4.1 sor
|
||
tedcontainers-2.4.0 toolz-0.11.1 torchaudio-0.9.0 tqdm-4.62.1
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="id3">
|
||
<h3>(5) Download icefall<a class="headerlink" href="#id3" title="Permalink to this heading"></a></h3>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ cd /tmp
|
||
$ git clone https://github.com/k2-fsa/icefall
|
||
|
||
Cloning into 'icefall'...
|
||
remote: Enumerating objects: 500, done.
|
||
remote: Counting objects: 100% (500/500), done.
|
||
remote: Compressing objects: 100% (308/308), done.
|
||
remote: Total 500 (delta 263), reused 307 (delta 102), pack-reused 0
|
||
Receiving objects: 100% (500/500), 172.49 KiB | 385.00 KiB/s, done.
|
||
Resolving deltas: 100% (263/263), done.
|
||
|
||
$ cd icefall
|
||
$ pip install -r requirements.txt
|
||
|
||
Collecting kaldilm
|
||
Downloading kaldilm-1.8.tar.gz (48 kB)
|
||
|________________________________| 48 kB 574 kB/s
|
||
Collecting kaldialign
|
||
Using cached kaldialign-0.2-cp38-cp38-linux_x86_64.whl
|
||
Collecting sentencepiece>=0.1.96
|
||
Using cached sentencepiece-0.1.96-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)
|
||
Collecting tensorboard
|
||
Using cached tensorboard-2.6.0-py3-none-any.whl (5.6 MB)
|
||
Requirement already satisfied: setuptools>=41.0.0 in /ceph-fj/fangjun/test-icefall/lib/python3.8/site-packages (from tensorboard->-r
|
||
requirements.txt (line 4)) (57.4.0)
|
||
Collecting absl-py>=0.4
|
||
Using cached absl_py-0.13.0-py3-none-any.whl (132 kB)
|
||
Collecting google-auth-oauthlib<0.5,>=0.4.1
|
||
Using cached google_auth_oauthlib-0.4.5-py2.py3-none-any.whl (18 kB)
|
||
Collecting grpcio>=1.24.3
|
||
Using cached grpcio-1.39.0-cp38-cp38-manylinux2014_x86_64.whl (4.3 MB)
|
||
Requirement already satisfied: wheel>=0.26 in /ceph-fj/fangjun/test-icefall/lib/python3.8/site-packages (from tensorboard->-r require
|
||
ments.txt (line 4)) (0.36.2)
|
||
Requirement already satisfied: numpy>=1.12.0 in /ceph-fj/fangjun/test-icefall/lib/python3.8/site-packages (from tensorboard->-r requi
|
||
rements.txt (line 4)) (1.21.2)
|
||
Collecting protobuf>=3.6.0
|
||
Using cached protobuf-3.17.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.0 MB)
|
||
Collecting werkzeug>=0.11.15
|
||
Using cached Werkzeug-2.0.1-py3-none-any.whl (288 kB)
|
||
Collecting tensorboard-data-server<0.7.0,>=0.6.0
|
||
Using cached tensorboard_data_server-0.6.1-py3-none-manylinux2010_x86_64.whl (4.9 MB)
|
||
Collecting google-auth<2,>=1.6.3
|
||
Downloading google_auth-1.35.0-py2.py3-none-any.whl (152 kB)
|
||
|________________________________| 152 kB 1.4 MB/s
|
||
Collecting requests<3,>=2.21.0
|
||
Using cached requests-2.26.0-py2.py3-none-any.whl (62 kB)
|
||
Collecting tensorboard-plugin-wit>=1.6.0
|
||
Using cached tensorboard_plugin_wit-1.8.0-py3-none-any.whl (781 kB)
|
||
Collecting markdown>=2.6.8
|
||
Using cached Markdown-3.3.4-py3-none-any.whl (97 kB)
|
||
Collecting six
|
||
Using cached six-1.16.0-py2.py3-none-any.whl (11 kB)
|
||
Collecting cachetools<5.0,>=2.0.0
|
||
Using cached cachetools-4.2.2-py3-none-any.whl (11 kB)
|
||
Collecting rsa<5,>=3.1.4
|
||
Using cached rsa-4.7.2-py3-none-any.whl (34 kB)
|
||
Collecting pyasn1-modules>=0.2.1
|
||
Using cached pyasn1_modules-0.2.8-py2.py3-none-any.whl (155 kB)
|
||
Collecting requests-oauthlib>=0.7.0
|
||
Using cached requests_oauthlib-1.3.0-py2.py3-none-any.whl (23 kB)
|
||
Collecting pyasn1<0.5.0,>=0.4.6
|
||
Using cached pyasn1-0.4.8-py2.py3-none-any.whl (77 kB)
|
||
Collecting urllib3<1.27,>=1.21.1
|
||
Using cached urllib3-1.26.6-py2.py3-none-any.whl (138 kB)
|
||
Collecting certifi>=2017.4.17
|
||
Using cached certifi-2021.5.30-py2.py3-none-any.whl (145 kB)
|
||
Collecting charset-normalizer~=2.0.0
|
||
Using cached charset_normalizer-2.0.4-py3-none-any.whl (36 kB)
|
||
Collecting idna<4,>=2.5
|
||
Using cached idna-3.2-py3-none-any.whl (59 kB)
|
||
Collecting oauthlib>=3.0.0
|
||
Using cached oauthlib-3.1.1-py2.py3-none-any.whl (146 kB)
|
||
Building wheels for collected packages: kaldilm
|
||
Building wheel for kaldilm (setup.py) ... done
|
||
Created wheel for kaldilm: filename=kaldilm-1.8-cp38-cp38-linux_x86_64.whl size=897233 sha256=eccb906cafcd45bf9a7e1a1718e4534254bfb
|
||
f4c0d0cbc66eee6c88d68a63862
|
||
Stored in directory: /root/fangjun/.cache/pip/wheels/85/7d/63/f2dd586369b8797cb36d213bf3a84a789eeb92db93d2e723c9
|
||
Successfully built kaldilm
|
||
Installing collected packages: urllib3, pyasn1, idna, charset-normalizer, certifi, six, rsa, requests, pyasn1-modules, oauthlib, cach
|
||
etools, requests-oauthlib, google-auth, werkzeug, tensorboard-plugin-wit, tensorboard-data-server, protobuf, markdown, grpcio, google
|
||
-auth-oauthlib, absl-py, tensorboard, sentencepiece, kaldilm, kaldialign
|
||
Successfully installed absl-py-0.13.0 cachetools-4.2.2 certifi-2021.5.30 charset-normalizer-2.0.4 google-auth-1.35.0 google-auth-oaut
|
||
hlib-0.4.5 grpcio-1.39.0 idna-3.2 kaldialign-0.2 kaldilm-1.8 markdown-3.3.4 oauthlib-3.1.1 protobuf-3.17.3 pyasn1-0.4.8 pyasn1-module
|
||
s-0.2.8 requests-2.26.0 requests-oauthlib-1.3.0 rsa-4.7.2 sentencepiece-0.1.96 six-1.16.0 tensorboard-2.6.0 tensorboard-data-server-0
|
||
.6.1 tensorboard-plugin-wit-1.8.0 urllib3-1.26.6 werkzeug-2.0.1
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
</section>
|
||
<section id="test-your-installation">
|
||
<h2>Test Your Installation<a class="headerlink" href="#test-your-installation" title="Permalink to this heading"></a></h2>
|
||
<p>To test that your installation is successful, let us run
|
||
the <a class="reference external" href="https://github.com/k2-fsa/icefall/tree/master/egs/yesno/ASR">yesno recipe</a>
|
||
on CPU.</p>
|
||
<section id="data-preparation">
|
||
<h3>Data preparation<a class="headerlink" href="#data-preparation" title="Permalink to this heading"></a></h3>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nb">export</span><span class="w"> </span><span class="nv">PYTHONPATH</span><span class="o">=</span>/tmp/icefall:<span class="nv">$PYTHONPATH</span>
|
||
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>/tmp/icefall
|
||
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>egs/yesno/ASR
|
||
$<span class="w"> </span>./prepare.sh
|
||
</pre></div>
|
||
</div>
|
||
<p>The log of running <code class="docutils literal notranslate"><span class="pre">./prepare.sh</span></code> is:</p>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>2023-05-12 17:55:21 (prepare.sh:27:main) dl_dir: /tmp/icefall/egs/yesno/ASR/download
|
||
2023-05-12 17:55:21 (prepare.sh:30:main) Stage 0: Download data
|
||
/tmp/icefall/egs/yesno/ASR/download/waves_yesno.tar.gz: 100%|_______________________________________________________________| 4.70M/4.70M [06:54<00:00, 11.4kB/s]
|
||
2023-05-12 18:02:19 (prepare.sh:39:main) Stage 1: Prepare yesno manifest
|
||
2023-05-12 18:02:21 (prepare.sh:45:main) Stage 2: Compute fbank for yesno
|
||
2023-05-12 18:02:23,199 INFO [compute_fbank_yesno.py:65] Processing train
|
||
Extracting and storing features: 100%|_______________________________________________________________| 90/90 [00:00<00:00, 212.60it/s]
|
||
2023-05-12 18:02:23,640 INFO [compute_fbank_yesno.py:65] Processing test
|
||
Extracting and storing features: 100%|_______________________________________________________________| 30/30 [00:00<00:00, 304.53it/s]
|
||
2023-05-12 18:02:24 (prepare.sh:51:main) Stage 3: Prepare lang
|
||
2023-05-12 18:02:26 (prepare.sh:66:main) Stage 4: Prepare G
|
||
/project/kaldilm/csrc/arpa_file_parser.cc:void kaldilm::ArpaFileParser::Read(std::istream&):79
|
||
[I] Reading \data\ section.
|
||
/project/kaldilm/csrc/arpa_file_parser.cc:void kaldilm::ArpaFileParser::Read(std::istream&):140
|
||
[I] Reading \1-grams: section.
|
||
2023-05-12 18:02:26 (prepare.sh:92:main) Stage 5: Compile HLG
|
||
2023-05-12 18:02:28,581 INFO [compile_hlg.py:124] Processing data/lang_phone
|
||
2023-05-12 18:02:28,582 INFO [lexicon.py:171] Converting L.pt to Linv.pt
|
||
2023-05-12 18:02:28,609 INFO [compile_hlg.py:48] Building ctc_topo. max_token_id: 3
|
||
2023-05-12 18:02:28,610 INFO [compile_hlg.py:52] Loading G.fst.txt
|
||
2023-05-12 18:02:28,611 INFO [compile_hlg.py:62] Intersecting L and G
|
||
2023-05-12 18:02:28,613 INFO [compile_hlg.py:64] LG shape: (4, None)
|
||
2023-05-12 18:02:28,613 INFO [compile_hlg.py:66] Connecting LG
|
||
2023-05-12 18:02:28,614 INFO [compile_hlg.py:68] LG shape after k2.connect: (4, None)
|
||
2023-05-12 18:02:28,614 INFO [compile_hlg.py:70] <class 'torch.Tensor'>
|
||
2023-05-12 18:02:28,614 INFO [compile_hlg.py:71] Determinizing LG
|
||
2023-05-12 18:02:28,615 INFO [compile_hlg.py:74] <class '_k2.ragged.RaggedTensor'>
|
||
2023-05-12 18:02:28,615 INFO [compile_hlg.py:76] Connecting LG after k2.determinize
|
||
2023-05-12 18:02:28,615 INFO [compile_hlg.py:79] Removing disambiguation symbols on LG
|
||
2023-05-12 18:02:28,616 INFO [compile_hlg.py:91] LG shape after k2.remove_epsilon: (6, None)
|
||
2023-05-12 18:02:28,617 INFO [compile_hlg.py:96] Arc sorting LG
|
||
2023-05-12 18:02:28,617 INFO [compile_hlg.py:99] Composing H and LG
|
||
2023-05-12 18:02:28,619 INFO [compile_hlg.py:106] Connecting LG
|
||
2023-05-12 18:02:28,619 INFO [compile_hlg.py:109] Arc sorting LG
|
||
2023-05-12 18:02:28,619 INFO [compile_hlg.py:111] HLG.shape: (8, None)
|
||
2023-05-12 18:02:28,619 INFO [compile_hlg.py:127] Saving HLG.pt to data/lang_phone
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="training">
|
||
<h3>Training<a class="headerlink" href="#training" title="Permalink to this heading"></a></h3>
|
||
<p>Now let us run the training part:</p>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ export CUDA_VISIBLE_DEVICES=""
|
||
$ ./tdnn/train.py
|
||
</pre></div>
|
||
</div>
|
||
<div class="admonition caution">
|
||
<p class="admonition-title">Caution</p>
|
||
<p>We use <code class="docutils literal notranslate"><span class="pre">export</span> <span class="pre">CUDA_VISIBLE_DEVICES=""</span></code> so that <code class="docutils literal notranslate"><span class="pre">icefall</span></code> uses CPU
|
||
even if there are GPUs available.</p>
|
||
</div>
|
||
<div class="admonition hint">
|
||
<p class="admonition-title">Hint</p>
|
||
<p>In case you get a <code class="docutils literal notranslate"><span class="pre">Segmentation</span> <span class="pre">fault</span> <span class="pre">(core</span> <span class="pre">dump)</span></code> error, please use:</p>
|
||
<blockquote>
|
||
<div><div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="nb">export</span><span class="w"> </span><span class="nv">PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION</span><span class="o">=</span>python
|
||
</pre></div>
|
||
</div>
|
||
</div></blockquote>
|
||
<p>See more at <cite><https://github.com/k2-fsa/icefall/issues/674></cite> if you are
|
||
interested.</p>
|
||
</div>
|
||
<p>The training log is given below:</p>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> 2023-05-12 18:04:59,759 INFO [train.py:481] Training started
|
||
2023-05-12 18:04:59,759 INFO [train.py:482] {'exp_dir': PosixPath('tdnn/exp'), 'lang_dir': PosixPath('data/lang_phone'), 'lr': 0.01, 'feature_dim': 23, 'weight_decay': 1e-06, 'start_epoch': 0,
|
||
'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 10, 'reset_interval': 20, 'valid_interval': 10, 'beam_size': 10,
|
||
'reduction': 'sum', 'use_double_scores': True, 'world_size': 1, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 15, 'seed': 42, 'feature_dir': PosixPath('data/fbank'), 'max_duration': 30.0,
|
||
'bucketing_sampler': False, 'num_buckets': 10, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': False, 'return_cuts': True, 'num_workers': 2,
|
||
'env_info': {'k2-version': '1.24.3', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '3b7f09fa35e72589914f67089c0da9f196a92ca4', 'k2-git-date': 'Mon May 8 22:58:45 2023',
|
||
'lhotse-version': '1.15.0.dev+git.6fcfced.clean', 'torch-version': '2.0.0+cu118', 'torch-cuda-available': False, 'torch-cuda-version': '11.8', 'python-version': '3.1', 'icefall-git-branch': 'master',
|
||
'icefall-git-sha1': '30bde4b-clean', 'icefall-git-date': 'Thu May 11 17:37:47 2023', 'icefall-path': '/tmp/icefall',
|
||
'k2-path': 'tmp/lib/python3.10/site-packages/k2-1.24.3.dev20230512+cuda11.8.torch2.0.0-py3.10-linux-x86_64.egg/k2/__init__.py',
|
||
'lhotse-path': 'tmp/lib/python3.10/site-packages/lhotse/__init__.py', 'hostname': 'host', 'IP address': '0.0.0.0'}}
|
||
2023-05-12 18:04:59,761 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt
|
||
2023-05-12 18:04:59,764 INFO [train.py:495] device: cpu
|
||
2023-05-12 18:04:59,791 INFO [asr_datamodule.py:146] About to get train cuts
|
||
2023-05-12 18:04:59,791 INFO [asr_datamodule.py:244] About to get train cuts
|
||
2023-05-12 18:04:59,852 INFO [asr_datamodule.py:149] About to create train dataset
|
||
2023-05-12 18:04:59,852 INFO [asr_datamodule.py:199] Using SingleCutSampler.
|
||
2023-05-12 18:04:59,852 INFO [asr_datamodule.py:205] About to create train dataloader
|
||
2023-05-12 18:04:59,853 INFO [asr_datamodule.py:218] About to get test cuts
|
||
2023-05-12 18:04:59,853 INFO [asr_datamodule.py:252] About to get test cuts
|
||
2023-05-12 18:04:59,986 INFO [train.py:422] Epoch 0, batch 0, loss[loss=1.065, over 2436.00 frames. ], tot_loss[loss=1.065, over 2436.00 frames. ], batch size: 4
|
||
2023-05-12 18:05:00,352 INFO [train.py:422] Epoch 0, batch 10, loss[loss=0.4561, over 2828.00 frames. ], tot_loss[loss=0.7076, over 22192.90 frames. ], batch size: 4
|
||
2023-05-12 18:05:00,691 INFO [train.py:444] Epoch 0, validation loss=0.9002, over 18067.00 frames.
|
||
2023-05-12 18:05:00,996 INFO [train.py:422] Epoch 0, batch 20, loss[loss=0.2555, over 2695.00 frames. ], tot_loss[loss=0.484, over 34971.47 frames. ], batch size: 5
|
||
2023-05-12 18:05:01,217 INFO [train.py:444] Epoch 0, validation loss=0.4688, over 18067.00 frames.
|
||
2023-05-12 18:05:01,251 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-0.pt
|
||
2023-05-12 18:05:01,389 INFO [train.py:422] Epoch 1, batch 0, loss[loss=0.2532, over 2436.00 frames. ], tot_loss[loss=0.2532, over 2436.00 frames. ], batch size: 4
|
||
2023-05-12 18:05:01,637 INFO [train.py:422] Epoch 1, batch 10, loss[loss=0.1139, over 2828.00 frames. ], tot_loss[loss=0.1592, over 22192.90 frames. ], batch size: 4
|
||
2023-05-12 18:05:01,859 INFO [train.py:444] Epoch 1, validation loss=0.1629, over 18067.00 frames.
|
||
2023-05-12 18:05:02,094 INFO [train.py:422] Epoch 1, batch 20, loss[loss=0.0767, over 2695.00 frames. ], tot_loss[loss=0.118, over 34971.47 frames. ], batch size: 5
|
||
2023-05-12 18:05:02,350 INFO [train.py:444] Epoch 1, validation loss=0.06778, over 18067.00 frames.
|
||
2023-05-12 18:05:02,395 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-1.pt
|
||
|
||
... ...
|
||
|
||
2023-05-12 18:05:14,789 INFO [train.py:422] Epoch 13, batch 0, loss[loss=0.01056, over 2436.00 frames. ], tot_loss[loss=0.01056, over 2436.00 frames. ], batch size: 4
|
||
2023-05-12 18:05:15,016 INFO [train.py:422] Epoch 13, batch 10, loss[loss=0.009022, over 2828.00 frames. ], tot_loss[loss=0.009985, over 22192.90 frames. ], batch size: 4
|
||
2023-05-12 18:05:15,271 INFO [train.py:444] Epoch 13, validation loss=0.01088, over 18067.00 frames.
|
||
2023-05-12 18:05:15,497 INFO [train.py:422] Epoch 13, batch 20, loss[loss=0.01174, over 2695.00 frames. ], tot_loss[loss=0.01077, over 34971.47 frames. ], batch size: 5
|
||
2023-05-12 18:05:15,747 INFO [train.py:444] Epoch 13, validation loss=0.01087, over 18067.00 frames.
|
||
2023-05-12 18:05:15,783 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-13.pt
|
||
2023-05-12 18:05:15,921 INFO [train.py:422] Epoch 14, batch 0, loss[loss=0.01045, over 2436.00 frames. ], tot_loss[loss=0.01045, over 2436.00 frames. ], batch size: 4
|
||
2023-05-12 18:05:16,146 INFO [train.py:422] Epoch 14, batch 10, loss[loss=0.008957, over 2828.00 frames. ], tot_loss[loss=0.009903, over 22192.90 frames. ], batch size: 4
|
||
2023-05-12 18:05:16,374 INFO [train.py:444] Epoch 14, validation loss=0.01092, over 18067.00 frames.
|
||
2023-05-12 18:05:16,598 INFO [train.py:422] Epoch 14, batch 20, loss[loss=0.01169, over 2695.00 frames. ], tot_loss[loss=0.01065, over 34971.47 frames. ], batch size: 5
|
||
2023-05-12 18:05:16,824 INFO [train.py:444] Epoch 14, validation loss=0.01077, over 18067.00 frames.
|
||
2023-05-12 18:05:16,862 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-14.pt
|
||
2023-05-12 18:05:16,865 INFO [train.py:555] Done!
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="decoding">
|
||
<h3>Decoding<a class="headerlink" href="#decoding" title="Permalink to this heading"></a></h3>
|
||
<p>Let us use the trained model to decode the test set:</p>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ ./tdnn/decode.py
|
||
</pre></div>
|
||
</div>
|
||
<p>The decoding log is:</p>
|
||
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>2023-05-12 18:08:30,482 INFO [decode.py:263] Decoding started
|
||
2023-05-12 18:08:30,483 INFO [decode.py:264] {'exp_dir': PosixPath('tdnn/exp'), 'lang_dir': PosixPath('data/lang_phone'), 'lm_dir': PosixPath('data/lm'), 'feature_dim': 23,
|
||
'search_beam': 20, 'output_beam': 8, 'min_active_states': 30, 'max_active_states': 10000, 'use_double_scores': True, 'epoch': 14, 'avg': 2, 'export': False, 'feature_dir': PosixPath('data/fbank'),
|
||
'max_duration': 30.0, 'bucketing_sampler': False, 'num_buckets': 10, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': False, 'return_cuts': True,
|
||
'num_workers': 2, 'env_info': {'k2-version': '1.24.3', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '3b7f09fa35e72589914f67089c0da9f196a92ca4', 'k2-git-date': 'Mon May 8 22:58:45 2023',
|
||
'lhotse-version': '1.15.0.dev+git.6fcfced.clean', 'torch-version': '2.0.0+cu118', 'torch-cuda-available': False, 'torch-cuda-version': '11.8', 'python-version': '3.1', 'icefall-git-branch': 'master',
|
||
'icefall-git-sha1': '30bde4b-clean', 'icefall-git-date': 'Thu May 11 17:37:47 2023', 'icefall-path': '/tmp/icefall',
|
||
'k2-path': '/tmp/lib/python3.10/site-packages/k2-1.24.3.dev20230512+cuda11.8.torch2.0.0-py3.10-linux-x86_64.egg/k2/__init__.py',
|
||
'lhotse-path': '/tmp/lib/python3.10/site-packages/lhotse/__init__.py', 'hostname': 'host', 'IP address': '0.0.0.0'}}
|
||
2023-05-12 18:08:30,483 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt
|
||
2023-05-12 18:08:30,487 INFO [decode.py:273] device: cpu
|
||
2023-05-12 18:08:30,513 INFO [decode.py:291] averaging ['tdnn/exp/epoch-13.pt', 'tdnn/exp/epoch-14.pt']
|
||
2023-05-12 18:08:30,521 INFO [asr_datamodule.py:218] About to get test cuts
|
||
2023-05-12 18:08:30,521 INFO [asr_datamodule.py:252] About to get test cuts
|
||
2023-05-12 18:08:30,675 INFO [decode.py:204] batch 0/?, cuts processed until now is 4
|
||
2023-05-12 18:08:30,923 INFO [decode.py:241] The transcripts are stored in tdnn/exp/recogs-test_set.txt
|
||
2023-05-12 18:08:30,924 INFO [utils.py:558] [test_set] %WER 0.42% [1 / 240, 0 ins, 1 del, 0 sub ]
|
||
2023-05-12 18:08:30,925 INFO [decode.py:249] Wrote detailed error stats to tdnn/exp/errs-test_set.txt
|
||
2023-05-12 18:08:30,925 INFO [decode.py:316] Done!
|
||
</pre></div>
|
||
</div>
|
||
<p><strong>Congratulations!</strong> You have successfully setup the environment and have run the first recipe in <code class="docutils literal notranslate"><span class="pre">icefall</span></code>.</p>
|
||
<p>Have fun with <code class="docutils literal notranslate"><span class="pre">icefall</span></code>!</p>
|
||
</section>
|
||
</section>
|
||
<section id="youtube-video">
|
||
<h2>YouTube Video<a class="headerlink" href="#youtube-video" title="Permalink to this heading"></a></h2>
|
||
<p>We provide the following YouTube video showing how to install <code class="docutils literal notranslate"><span class="pre">icefall</span></code>.
|
||
It also shows how to debug various problems that you may encounter while
|
||
using <code class="docutils literal notranslate"><span class="pre">icefall</span></code>.</p>
|
||
<div class="admonition note">
|
||
<p class="admonition-title">Note</p>
|
||
<p>To get the latest news of <a class="reference external" href="https://github.com/k2-fsa">next-gen Kaldi</a>, please subscribe
|
||
the following YouTube channel by <a class="reference external" href="https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw">Nadira Povey</a>:</p>
|
||
<blockquote>
|
||
<div><p><a class="reference external" href="https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw">https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw</a></p>
|
||
</div></blockquote>
|
||
</div>
|
||
<div class="video_wrapper" style="">
|
||
<iframe allowfullscreen="true" src="https://www.youtube.com/embed/LVmrBD0tLfE" style="border: 0; height: 345px; width: 560px">
|
||
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