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Update UI of more examples (#184)
- lstm-text-gen - mnist-core - mnist-cnn-transfer-learning - mobilenet
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‎lstm-text-generation/index.html‎

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-->
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<!doctype html>
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<head>
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<link rel="stylesheet" href="https://code.getmdl.io/1.3.0/material.cyan-teal.min.css" />
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<link rel="stylesheet" href="../shared/tfjs-examples.css" />
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</head>
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<style>
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body {
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font-family: "Roboto", "Helvetica", "Arial", sans-serif;
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margin-top: 50px;
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margin-left: 50px;
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width: 80%;
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}
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.canvases {
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display: inline-block;
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}
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.monospace {
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font-family: monospace;
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}
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.input-title {
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display: inline-block;
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width: 20em;
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}
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.vertical-sections {
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border: 1px solid #AAA;
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padding: 6px;
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margin: 6px;
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}
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.horizontal-sections {
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display: inline-block;
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padding-right: 20px;
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vertical-align: top;
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}
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#app-status {
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color: blue;
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font-size: 150%;
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padding-bottom: 1em;
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width: 12em;
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}
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select {
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font-size: 14pt;
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}
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button {
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font-size: 14pt;
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margin: 3px;
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}
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input:disabled {
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background: #eeeeee;
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}
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textarea {
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width:98%;
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width: 98%;
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}
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</style>
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<body>
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<h1>TensorFlow.js Example:<br/>Train LSTM to Generate Text</h1>
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<div>
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<div id="app-status" class="vertical-sections">
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<span>Please select a text data source or enter your custom text in the text box below and click "load text data" first</span>
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<body class='tfjs-example-container'>
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<section class='title-area'>
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<h1>TensorFlow.js Text Generation:</h1>
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<p class='subtitle'>Train a LSTM (Long Short Term Memory) model to generate text</p>
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</section>
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<section>
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<p class='section-head'>Description</p>
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<p>
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This example allows you to train a model to generate text in the style of some existing source text.
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The model is designed to predict the <em>next character</em> in a text given some preceding string of characters.
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Doing this repetedly builds up a text, charachter by character.
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</p>
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</section>
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<section>
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<p class='section-head'>Status</p>
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<div id="app-status">
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Please select a text data source or enter your custom text in the text box below and click <em>"Load source data"</em>.
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</div>
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</section>
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<section>
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<p class='section-head'>Source Data</p>
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<select id="text-data-select"></select>
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<button id="load-text-data">Load source data</button>
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<div>
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<textarea class="monospace" id="test-text" value="" rows="10"></textarea>
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</div>
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</section>
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<section>
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<p class='section-head'>Model Loading/Creation</p>
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<div>
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<p>
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<em>
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Model saved in IndexedDB:
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<span id="model-available">Load text data first.</span>
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</em>
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</p>
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<div class="vertical-sections">
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<select id="text-data-select"></select>
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<button id="load-text-data">Load text data</button>
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<div>
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<textarea class="monospace" id="test-text" value="" rows="10"></textarea>
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<span class="input-title">LSTM layer size(s) (e.g., 128 or 100,50):</span>
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<input id="lstm-layer-sizes" value="128"></input>
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<button id="create-or-load-model" disabled="true">Create or load model</button>
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<button id="delete-model" disabled="true">Delete existing model</button>
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</div>
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</div>
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</section>
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<div class="vertical-sections">
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<div class="monospace">
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<span class="input-title">Model saved in IndexedDB:</span>
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<input class="monospace" id="model-available" readonly="true" size="60" value="(Load text data first.)"></input>
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</div>
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<div class="horizontal-sections">
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<div class="monospace">
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<span class="input-title">LSTM layer size(s)<br/>(e.g., 128 or 100,50):</span>
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<input class="monospace" id="lstm-layer-sizes" value="128"></input>
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</div>
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<section>
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<p class='section-head'>Model Training</p>
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<p>
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It can take a while to generate an effective model. Try increasing the number of <em>epochs</em> to improve the
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results, we have found that about <strong>50-100 epochs</strong> are needed to start generating reasonable
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text.
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</p>
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<div class="with-cols">
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<div>
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<div>
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<button id="create-or-load-model" disabled="true">Create or load model</button>
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<button id="delete-model" disabled="true">Delete existing model</button>
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<span class="input-title">Number of Epochs:</span>
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<input id="epochs" value="5"></input>
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</div>
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</div>
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<div class="horizontal-sections">
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<div class="monospace">
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<div>
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<span class="input-title">Examples per epoch:</span>
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<input class="monospace" id="examples-per-epoch" value="2048"></input>
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<input id="examples-per-epoch" value="2048"></input>
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</div>
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<div class="monospace">
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<div>
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<span class="input-title">Batch size:</span>
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<input class="monospace" id="batch-size" value="128"></input>
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</div>
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<div class="monospace">
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<span class="input-title">Epochs:</span>
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<input class="monospace" id="epochs" value="5"></input>
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<input id="batch-size" value="128"></input>
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</div>
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<div class="monospace">
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<div>
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<span class="input-title">Validation spilt:</span>
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<input class="monospace" id="validation-split" value="0.0625"></input>
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<input id="validation-split" value="0.0625"></input>
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</div>
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<div class="monospace">
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<div>
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<span class="input-title">Learning rate:</span>
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<input class="monospace" id="learning-rate" value="1e-2"></input>
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<input id="learning-rate" value="1e-2"></input>
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</div>
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<div>
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<button id="train-model" disabled="true">Train model</button>
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</div>
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<div class="horizontal-sections">
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<div class="canvases" id="loss-canvas"></div>
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</div>
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</div>
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<div class="canvases" id="batch-loss-canvas"></div>
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<div class="canvases" id="epoch-loss-canvas"></div>
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</div>
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</section>
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<div class="vertical-sections">
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<div class="monospace">
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<span class="input-title">Generation length:</span>
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<input class="monospace" id="generate-length" value="200"></input>
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</div>
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<div class="monospace">
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<span class="input-title">Generation temperature:</span>
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<input class="monospace" id="temperature" value="0.75"></input>
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</div>
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<div>
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<button id="generate-text" disabled="true">Generate text</button>
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<span id="text-generation-status"></span>
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</div>
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<div>
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<span class="input-title">Seed text:</span>
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<textarea class="monospace" id="seed-text" value="" rows="4"></textarea>
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</div>
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<div>
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<span class="input-title">Generated text:</span>
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<textarea class="monospace" id="generated-text" readonly="true" value="" rows="10"></textarea>
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</div>
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<section>
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<p class='section-head'>Text Generation Parameters</p>
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<p>
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To generate text the model needs to have some number of preceding characters from which it continues,
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we call these characters the <em>seed text</em>. You can type one in, or we will extract a random substring from
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the input text to be the seed text. Note that the seed text must be at least 40 charachters long.
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</p>
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<div>
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<span class="input-title">Length of generated text:</span>
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<input id="generate-length" value="200"></input>
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</div>
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<div>
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<span class="input-title">Generation temperature:</span>
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<input id="temperature" value="0.75"></input>
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</div>
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<div>
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<button id="generate-text" disabled="true">Generate text</button>
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<span id="text-generation-status"></span>
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</div>
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</div>
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<div>
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<span class="input-title">Seed text:</span>
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<textarea class="monospace" id="seed-text" value="" rows="4"></textarea>
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</div>
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<p class='section-head'>Model Output</p>
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<div>
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<span class="input-title">Generated text:</span>
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<textarea class="monospace" id="generated-text" readonly="true" value="" rows="10"></textarea>
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</div>
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</section>
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</body>
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‎lstm-text-generation/index.js‎

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const t1 = new Date().getTime();
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const examplesPerSec = batchSize / ((t1 - t) / 1e3);
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t = t1;
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onTrainBatchEnd(
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logs.loss, ++batchCount / totalBatches, examplesPerSec);
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onTrainBatchEnd(logs, ++batchCount / totalBatches, examplesPerSec);
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},
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onEpochEnd: async (epoch, logs) => {
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onTrainEpochEnd(logs.val_loss);
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onTrainEpochEnd(logs);
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},
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}
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});

‎lstm-text-generation/package.json‎

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},
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"dependencies": {
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"@tensorflow/tfjs": "^0.13.3",
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"vega-embed": "^3.0.0"
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"@tensorflow/tfjs-vis": "^0.3.0"
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},
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"scripts": {
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"watch": "cross-env NODE_ENV=development parcel index.html --no-hmr --open",

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