TensorFlow Addons

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href="https://www.tensorflow.org/addons?hl=tr" /><link rel="alternate" hreflang="vi" href="https://www.tensorflow.org/addons?hl=vi" /><title>TensorFlow Addons</title> <meta property="og:title" content="TensorFlow Addons"><meta name="description" content="A library of useful extra functionality for TensorFlow maintained by SIG-addons with community contributions that conform to well-established API patterns."> <meta property="og:description" content="A library of useful extra functionality for TensorFlow maintained by SIG-addons with community contributions that conform to well-established API patterns."><meta property="og:url" content="https://www.tensorflow.org/addons"><meta property="og:image" content="https://www.tensorflow.org/static/images/tf_logo_social.png"> <meta property="og:image:width" content="1200"> <meta property="og:image:height" content="675"><meta property="og:locale" content="en"><meta name="twitter:card" content="summary_large_image"><script 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it"> <devsite-bookmark></devsite-bookmark> <span slot="popout-heading"> Stay organized with collections </span> <span slot="popout-contents"> Save and categorize content based on your preferences. </span> </devsite-feature-tooltip> <devsite-toc class="devsite-nav" depth="2" devsite-toc-embedded disabled> </devsite-toc> <div class="devsite-article-body clearfix devsite-no-page-title"> <section class="devsite-landing-row devsite-landing-row-1-up" header-position="top" > <div class="devsite-landing-row-inner"> <header class="devsite-landing-row-header" > <div class="devsite-landing-row-header-text"> <h2 id="the-future-of-tensorflow-addons" data-text="The Future of TensorFlow Addons" tabindex="0"> The Future of TensorFlow Addons </h2> </div> </header> <div class="devsite-landing-row-group"> <div class="devsite-landing-row-item devsite-landing-row-50" description-position="bottom" > <div class="devsite-landing-row-item-media "> <div class="devsite-landing-row-item-code"> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><span class="devsite-syntax-kn">import</span> <span class="devsite-syntax-nn">tensorflow</span> <span class="devsite-syntax-k">as</span> <span class="devsite-syntax-nn">tf</span> <span class="devsite-syntax-kn">import</span> <span class="devsite-syntax-nn">tensorflow_addons</span> <span class="devsite-syntax-k">as</span> <span class="devsite-syntax-nn">tfa</span> <span class="devsite-syntax-n">train</span><span class="devsite-syntax-p">,</span><span class="devsite-syntax-n">test</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">keras</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">datasets</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">mnist</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">load_data</span><span class="devsite-syntax-p">()</span> <span class="devsite-syntax-n">x_train</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">y_train</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">train</span> <span class="devsite-syntax-n">x_train</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">x_train</span><span class="devsite-syntax-p">[</span><span class="devsite-syntax-o">...</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">newaxis</span><span class="devsite-syntax-p">]</span> <span class="devsite-syntax-o">/</span> <span class="devsite-syntax-mf">255.0</span> <span class="devsite-syntax-c1"># TFA layers and activations</span> <span class="devsite-syntax-n">model</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">keras</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">Sequential</span><span class="devsite-syntax-p">([</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">keras</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">layers</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">Conv2D</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">filters</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">10</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">kernel_size</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-mi">3</span><span class="devsite-syntax-p">,</span><span class="devsite-syntax-mi">3</span><span class="devsite-syntax-p">),</span> <span class="devsite-syntax-n">activation</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-n">tfa</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">activations</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">gelu</span><span class="devsite-syntax-p">),</span> <span class="devsite-syntax-n">tfa</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">layers</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">GroupNormalization</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">groups</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">5</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">axis</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">3</span><span class="devsite-syntax-p">),</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">keras</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">layers</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">Flatten</span><span class="devsite-syntax-p">(),</span> <span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">keras</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">layers</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">Dense</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-mi">10</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">activation</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-s1">'softmax'</span><span class="devsite-syntax-p">)</span> <span class="devsite-syntax-p">])</span> <span class="devsite-syntax-c1"># TFA optimizers, losses and metrics</span> <span class="devsite-syntax-n">model</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">compile</span><span class="devsite-syntax-p">(</span> <span class="devsite-syntax-n">optimizer</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-n">tfa</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">optimizers</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">RectifiedAdam</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-mf">0.001</span><span class="devsite-syntax-p">),</span> <span class="devsite-syntax-n">loss</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-n">tfa</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">losses</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">TripletSemiHardLoss</span><span class="devsite-syntax-p">(),</span> <span class="devsite-syntax-n">metrics</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-p">[</span><span class="devsite-syntax-n">tfa</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">metrics</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">MultiLabelConfusionMatrix</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">num_classes</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">10</span><span class="devsite-syntax-p">)])</span> <span class="devsite-syntax-n">history</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">model</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">fit</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">x_train</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">y_train</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">epochs</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">10</span><span class="devsite-syntax-p">)</span></pre></devsite-code> </div> </div> <div class="devsite-landing-row-item-description" > <div class="devsite-landing-row-item-body"> <div class="devsite-landing-row-item-description-content"> <p>TensorFlow Addons (TFA) is a repository of community maintained and contributed extensions for TensorFlow, first created in 2018 and maintained by the <a href="https://github.com/tensorflow/community/blob/master/sigs/addons/CHARTER.md"> SIG-Addons</a> community. Over the course of 4 years, 200 contributors have built the TFA repository into a community owned and managed success that is being utilized by over 8,000 github repositories according to our dependency graph. We’d like to take a moment to sincerely thank everyone involved as a contributor or community member for their efforts.</p> <p>Recently, there has been increasing overlap in contributions and scope between TFA and the <a href="https://github.com/keras-team/keras-cv">Keras-CV</a>, and <a href="https://github.com/keras-team/keras-nlp">Keras-NLP</a> libraries. To prevent future overlap, we believe that new and existing addons to TensorFlow will be best maintained in Keras project repositories, where possible.</p> <h2 id="decision-to-wind-down-tensorflow-addons" data-text="Decision to Wind Down TensorFlow Addons" tabindex="-1">Decision to Wind Down TensorFlow Addons</h2> <p>We believe that it is in the best interest of the TensorFlow community to consolidate where TensorFlow extensions can be utilized, maintained and contributed. Because of this, it is bittersweet that we are announcing our plans to move TensorFlow Addons to a minimal maintenance and release mode.</p> <p>TFA SIG Addons will be ending development and introduction of new features to this project. TFA will be transitioning to a minimal maintenance and release mode for one year (until May 2024) in order to give appropriate time for you to adjust any dependencies to the overlapping repositories in our TensorFlow community ( <a href="https://github.com/keras-team/keras">Keras</a>, <a href="https://github.com/keras-team/keras-cv">Keras-CV</a>, and <a href="https://github.com/keras-team/keras-nlp">Keras-NLP</a>). Going forward, please consider contributing to the Keras-CV and Keras-NLP projects.</p> <h3 id="background:" data-text="Background:" tabindex="-1">Background:</h3> <p>The <a href="https://github.com/tensorflow/community/blob/master/rfcs/20181214-move-to-addons.md"> original RFC proposal</a> for TFA was dated <b>2018-12-14</b> with the stated goal of building a community managed repository for contributions that conform to well-established API patterns, but implement new functionality not available in core TensorFlow as defined in our <a href="https://github.com/tensorflow/community/blob/master/sigs/addons/CHARTER.md"> Special Interest Group (SIG) charter</a>.</p> <p>As the years have progressed, new repositories with healthy contributor communities (Keras-CV, Keras-NLP, etc.) have been created with similar goals to ours and the criteria for contribution acceptance overlaps significantly (e.g. number of required citations). Additionally, since <a href="https://github.com/tensorflow/community/blob/master/rfcs/20200205-standalone-keras-repository.md"> Keras split out of core TensorFlow in 2020</a>, the barrier for community contribution has been substantially lowered.</p> <p>Understandably, there has been increasing ambiguity regarding where contributions should land and where they will be best maintained. Many features that are available in TFA are simultaneously available in other TensorFlow Community repositories. As just a few examples:</p> <ul> <li><b>Random Cutout:</b> <a href="https://www.tensorflow.org/addons/api_docs/python/tfa/image/random_cutout">TFA</a> & <a href="https://keras.io/api/keras_cv/layers/preprocessing/random_cutout/">Keras-CV</a></li> <li><b>AdamW Optimizer:</b> <a href="https://www.tensorflow.org/addons/api_docs/python/tfa/optimizers/AdamW">TFA</a> & <a href="https://www.tensorflow.org/api_docs/python/tf/keras/optimizers/experimental/AdamW">Keras</a></li> <li><b>Multihead Attention:</b> <a href="https://www.tensorflow.org/addons/api_docs/python/tfa/layers/MultiHeadAttention">TFA</a> & <a href="https://www.tensorflow.org/api_docs/python/tf/keras/layers/MultiHeadAttention">Keras</a></li> </ul> <p>As part of the original RFC, our <a href="https://github.com/tensorflow/community/blob/master/sigs/addons/CHARTER.md"> Special Interest Group</a> agreed to migrate code from <code translate="no" dir="ltr">tf.contrib</code> and <a href="https://github.com/keras-team/keras-contrib"><code translate="no" dir="ltr"> keras.contrib</code></a> repositories. In doing so, TFA inherited C++ custom-ops, which made TFA a unique place in the TensorFlow community to contribute C++ custom ops to be built and distributed. However, we’ve recently <a href="https://github.com/keras-team/keras-cv/pull/890#event-7642725159">migrated much of that infrastructure to Keras-CV</a> so that they can compile and distribute custom ops as they see fit.</p> <h3 id="what’s-next:" data-text="What’s Next:" tabindex="-1">What’s Next:</h3> <ul> <li>Maintenance releases will continue for 1 year (until May 2024).</li> <li>Import-warnings in the 0.20 TFA release.</li> <li>This information is also published on the <a href="https://github.com/tensorflow/addons/issues/2807">GitHub tracking issue<a/></li> <li>An inventory of equivalent functionality is <a href="https://docs.google.com/spreadsheets/d/1YMPudb7Otqx_TQu_oTHMm5IRZolyPcah8-qkMs_wI-I/edit#gid=0">available here</a>.</li> </ul> </div> </div> </div> </div> </div> </div> </section> <section class="devsite-landing-row devsite-landing-row-3-up devsite-landing-row-cards" header-position="top" > <div class="devsite-landing-row-inner"> <div class="devsite-landing-row-group"> <div 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