addition-rnn-webworker/index.html

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<body>
  <div class='tfjs-example-container centered-container'>
    <section class='title-area'>
      <h1>TensorFlow.js: Addition RNN in web worker</h1>
      <p class='subtitle'>Train a model in web worker</p>
    </section>
    <section>
      <p class='section-head'>Description</p>
      <p>
        This example trains a <a href="https://en.wikipedia.org/wiki/Recurrent_neural_network">Recurrent Neural Network</a>
        in <a href="https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers">web worker</a>
        to do addition without explicitly defining the addition operator. Instead
        we feed it examples of sums and let it learn from that.
      </p>
      <p>
        In this way, we can do long-running computation without actually blocking the UI rendering thread.
      </p>
      <p>
        Given a <span class='in-type'>string</span> like
        <span class='in-example'>3 + 4</span>, it will learn to output
        a <span class='out-type'>number</span>
        like <span class=out-example>7</span>.
      </p>
      <p>
        This example generates its own training data programatically.
      </p>
    </section>

    <div>
      <section>
        <p class='section-head'>Instructions</p>
        <p>
          Click the "Train Model" to start the model training button. You can edit the
          parameters used to train the model as well.
        </p>
      </section>

      <div class="controls with-rows">
        <div class="settings">
          <div class="setting">
            <span class="setting-label">Digits:</span>
            <input id="digits" value="2"></input>
          </div>
          <div class="setting">
            <span class="setting-label">Training Size:</span>
            <input id="trainingSize" value="5000"></input>
          </div>
          <div class="setting">
            <span class="setting-label">RNN Type:</span>
            <select id="rnnType">
              <option value="SimpleRNN">SimpleRNN</option>
              <option value="GRU">GRU</option>
              <option value="LSTM">LSTM</option>
            </select>
          </div>
          <div class="setting">
            <span class="setting-label">RNN Layers:</span>
            <input id="rnnLayers" value="1"></input>
          </div>
          <div class="setting">
            <span class="setting-label">RNN Hidden Layer Size:</span>
            <input id="rnnLayerSize" value="128"></input>
          </div>
          <div class="setting">
            <span class="setting-label">Batch Size:</span>
            <input id="batchSize" value="128"></input>
          </div>
          <div class="setting">
            <span class="setting-label">Train Iterations:</span>
            <input id="trainIterations" value="100"></input>
          </div>
          <div class="setting">
            <span class="setting-label"># of test examples:</span>
            <input id="numTestExamples" value="20"></input>
          </div>
        </div>

        <div>
          <span>
            <button class="btn-primary" id="trainModel">Train Model</button>
          </span>
        </div>
      </div>


      <section>
        <p class='section-head'>Training Progress</p>
        <p id="trainStatus"></p>
        <div class='with-cols'>
          <div id="lossChart"></div>
          <div id="accuracyChart"></div>
        </div>
      </section>

      <section>
        <p class='section-head'>Test Examples</p>
        <p id="testExamples"></p>
      </section>


    </div>
  </div>

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