docs/build/html/_generated/deepof.model_utils.TransformerDecoderLayer.html
<!DOCTYPE html>
<html class="writer-html5" lang="en" >
<head>
<meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>deepof.model_utils.TransformerDecoderLayer — deepof 0.6.2 documentation</title>
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
<link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
<link rel="stylesheet" href="../_static/jupyter-sphinx.css" type="text/css" />
<link rel="stylesheet" href="../_static/thebelab.css" type="text/css" />
<link rel="stylesheet" href="../_static/custom.css" type="text/css" />
<link rel="shortcut icon" href="../_static/deepof.ico"/>
<!--[if lt IE 9]>
<script src="../_static/js/html5shiv.min.js"></script>
<![endif]-->
<script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
<script src="../_static/jquery.js"></script>
<script src="../_static/underscore.js"></script>
<script src="../_static/_sphinx_javascript_frameworks_compat.js"></script>
<script src="../_static/doctools.js"></script>
<script src="../_static/sphinx_highlight.js"></script>
<script src="../_static/thebelab-helper.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/@jupyter-widgets/html-manager@^1.0.1/dist/embed-amd.js"></script>
<script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script>
<script src="../_static/js/theme.js"></script>
<link rel="index" title="Index" href="../genindex.html" />
<link rel="search" title="Search" href="../search.html" />
</head>
<body class="wy-body-for-nav">
<div class="wy-grid-for-nav">
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
<div class="wy-side-scroll">
<div class="wy-side-nav-search" >
<a href="../index.html">
<img src="../_static/deepof_sidebar.ico" class="logo" alt="Logo"/>
</a>
<div role="search">
<form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
<input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
<!-- Local TOC -->
<div class="local-toc"><ul>
<li><a class="reference internal" href="#">deepof.model_utils.TransformerDecoderLayer</a><ul>
<li><a class="reference internal" href="#deepof.model_utils.TransformerDecoderLayer"><code class="docutils literal notranslate"><span class="pre">TransformerDecoderLayer</span></code></a><ul>
<li><a class="reference internal" href="#deepof.model_utils.TransformerDecoderLayer.__init__"><code class="docutils literal notranslate"><span class="pre">TransformerDecoderLayer.__init__()</span></code></a></li>
<li><a class="reference internal" href="#id0"><code class="docutils literal notranslate"><span class="pre">TransformerDecoderLayer.__init__()</span></code></a></li>
</ul>
</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</nav>
<section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
<i data-toggle="wy-nav-top" class="fa fa-bars"></i>
<a href="../index.html">deepof</a>
</nav>
<div class="wy-nav-content">
<div class="rst-content">
<div role="navigation" aria-label="Page navigation">
<ul class="wy-breadcrumbs">
<li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
<li class="breadcrumb-item active">deepof.model_utils.TransformerDecoderLayer</li>
<li class="wy-breadcrumbs-aside">
<a href="../_sources/_generated/deepof.model_utils.TransformerDecoderLayer.rst.txt" rel="nofollow"> View page source</a>
</li>
</ul>
<hr/>
</div>
<div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
<div itemprop="articleBody">
<style>
/* CSS overrides for sphinx_rtd_theme */
/* 24px margin */
.nbinput.nblast.container,
.nboutput.nblast.container {
margin-bottom: 19px; /* padding has already 5px */
}
/* ... except between code cells! */
.nblast.container + .nbinput.container {
margin-top: -19px;
}
.admonition > p:before {
margin-right: 4px; /* make room for the exclamation icon */
}
/* Fix math alignment, see https://github.com/rtfd/sphinx_rtd_theme/pull/686 */
.math {
text-align: unset;
}
</style>
<section id="deepof-model-utils-transformerdecoderlayer">
<h1>deepof.model_utils.TransformerDecoderLayer<a class="headerlink" href="#deepof-model-utils-transformerdecoderlayer" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="deepof.model_utils.TransformerDecoderLayer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">deepof.model_utils.</span></span><span class="sig-name descname"><span class="pre">TransformerDecoderLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#deepof.model_utils.TransformerDecoderLayer" title="Permalink to this definition"></a></dt>
<dd><p>Transformer decoder layer. Based on <a class="reference external" href="https://www.tensorflow.org/text/tutorials/transformer">https://www.tensorflow.org/text/tutorials/transformer</a>.</p>
<dl class="py method">
<dt class="sig sig-object py" id="deepof.model_utils.TransformerDecoderLayer.__init__">
<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dff</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#deepof.model_utils.TransformerDecoderLayer.__init__" title="Permalink to this definition"></a></dt>
<dd><p>Construct the transformer decoder layer.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>key_dim</strong> – dimensionality of the time series</p></li>
<li><p><strong>num_heads</strong> – number of heads of the multi-head-attention layers</p></li>
<li><p><strong>dff</strong> – dimensionality of the embeddings</p></li>
<li><p><strong>rate</strong> – dropout rate</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<p class="rubric">Methods</p>
<table class="autosummary longtable docutils align-default">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="#id0" title="deepof.model_utils.TransformerDecoderLayer.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(key_dim, num_heads, dff[, rate])</p></td>
<td><p>Construct the transformer decoder layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_loss</span></code>(losses, **kwargs)</p></td>
<td><p>Add loss tensor(s), potentially dependent on layer inputs.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_metric</span></code>(value[, name])</p></td>
<td><p>Adds metric tensor to the layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_update</span></code>(updates)</p></td>
<td><p>Add update op(s), potentially dependent on layer inputs.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_variable</span></code>(*args, **kwargs)</p></td>
<td><p>Deprecated, do NOT use! Alias for <cite>add_weight</cite>.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">add_weight</span></code>([name, shape, dtype, ...])</p></td>
<td><p>Adds a new variable to the layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">build</span></code>(input_shape)</p></td>
<td><p>Creates the variables of the layer (for subclass implementers).</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">build_from_config</span></code>(config)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">call</span></code>(x, enc_output, training, ...)</p></td>
<td><p>Call the transformer decoder layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">compute_mask</span></code>(inputs[, mask])</p></td>
<td><p>Computes an output mask tensor.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">compute_output_shape</span></code>(input_shape)</p></td>
<td><p>Computes the output shape of the layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">compute_output_signature</span></code>(input_signature)</p></td>
<td><p>Compute the output tensor signature of the layer based on the inputs.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">count_params</span></code>()</p></td>
<td><p>Count the total number of scalars composing the weights.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">finalize_state</span></code>()</p></td>
<td><p>Finalizes the layers state after updating layer weights.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_config</span></code>(config)</p></td>
<td><p>Creates a layer from its config.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_build_config</span></code>()</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_config</span></code>()</p></td>
<td><p>Returns the config of the layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_input_at</span></code>(node_index)</p></td>
<td><p>Retrieves the input tensor(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_input_mask_at</span></code>(node_index)</p></td>
<td><p>Retrieves the input mask tensor(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_input_shape_at</span></code>(node_index)</p></td>
<td><p>Retrieves the input shape(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_output_at</span></code>(node_index)</p></td>
<td><p>Retrieves the output tensor(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_output_mask_at</span></code>(node_index)</p></td>
<td><p>Retrieves the output mask tensor(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_output_shape_at</span></code>(node_index)</p></td>
<td><p>Retrieves the output shape(s) of a layer at a given node.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_weights</span></code>()</p></td>
<td><p>Returns the current weights of the layer, as NumPy arrays.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">set_weights</span></code>(weights)</p></td>
<td><p>Sets the weights of the layer, from NumPy arrays.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">with_name_scope</span></code>(method)</p></td>
<td><p>Decorator to automatically enter the module name scope.</p></td>
</tr>
</tbody>
</table>
<p class="rubric">Attributes</p>
<table class="autosummary longtable docutils align-default">
<tbody>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">activity_regularizer</span></code></p></td>
<td><p>Optional regularizer function for the output of this layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">compute_dtype</span></code></p></td>
<td><p>The dtype of the layer's computations.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">dtype</span></code></p></td>
<td><p>The dtype of the layer weights.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">dtype_policy</span></code></p></td>
<td><p>The dtype policy associated with this layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">dynamic</span></code></p></td>
<td><p>Whether the layer is dynamic (eager-only); set in the constructor.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">inbound_nodes</span></code></p></td>
<td><p>Return Functional API nodes upstream of this layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input</span></code></p></td>
<td><p>Retrieves the input tensor(s) of a layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_mask</span></code></p></td>
<td><p>Retrieves the input mask tensor(s) of a layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_shape</span></code></p></td>
<td><p>Retrieves the input shape(s) of a layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">input_spec</span></code></p></td>
<td><p><cite>InputSpec</cite> instance(s) describing the input format for this layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">losses</span></code></p></td>
<td><p>List of losses added using the <cite>add_loss()</cite> API.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">metrics</span></code></p></td>
<td><p>List of metrics added using the <cite>add_metric()</cite> API.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">name</span></code></p></td>
<td><p>Name of the layer (string), set in the constructor.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">name_scope</span></code></p></td>
<td><p>Returns a <cite>tf.name_scope</cite> instance for this class.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">non_trainable_variables</span></code></p></td>
<td><p>Sequence of non-trainable variables owned by this module and its submodules.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">non_trainable_weights</span></code></p></td>
<td><p>List of all non-trainable weights tracked by this layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">outbound_nodes</span></code></p></td>
<td><p>Return Functional API nodes downstream of this layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output</span></code></p></td>
<td><p>Retrieves the output tensor(s) of a layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_mask</span></code></p></td>
<td><p>Retrieves the output mask tensor(s) of a layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">output_shape</span></code></p></td>
<td><p>Retrieves the output shape(s) of a layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">stateful</span></code></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">submodules</span></code></p></td>
<td><p>Sequence of all sub-modules.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">supports_masking</span></code></p></td>
<td><p>Whether this layer supports computing a mask using <cite>compute_mask</cite>.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">trainable</span></code></p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">trainable_variables</span></code></p></td>
<td><p>Sequence of trainable variables owned by this module and its submodules.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">trainable_weights</span></code></p></td>
<td><p>List of all trainable weights tracked by this layer.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">updates</span></code></p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">variable_dtype</span></code></p></td>
<td><p>Alias of <cite>Layer.dtype</cite>, the dtype of the weights.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">variables</span></code></p></td>
<td><p>Returns the list of all layer variables/weights.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">weights</span></code></p></td>
<td><p>Returns the list of all layer variables/weights.</p></td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt class="sig sig-object py" id="id0">
<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key_dim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_heads</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dff</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#id0" title="Permalink to this definition"></a></dt>
<dd><p>Construct the transformer decoder layer.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>key_dim</strong> – dimensionality of the time series</p></li>
<li><p><strong>num_heads</strong> – number of heads of the multi-head-attention layers</p></li>
<li><p><strong>dff</strong> – dimensionality of the embeddings</p></li>
<li><p><strong>rate</strong> – dropout rate</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
</div>
</div>
<footer>
<hr/>
<div role="contentinfo">
<p>© Copyright 2024, Lucas Miranda.</p>
</div>
Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
<a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
provided by <a href="https://readthedocs.org">Read the Docs</a>.
</footer>
</div>
</div>
</section>
</div>
<script>
jQuery(function () {
SphinxRtdTheme.Navigation.enable(true);
});
</script>
</body>
</html>