TensorFlow 2 quickstart for beginners

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devsite-nav-title-no-path"> <span class="devsite-nav-text" tooltip>More text loading</span> </div></li><li class="devsite-nav-item devsite-nav-external"><a href="/text/guide/unicode" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /text/guide/unicode" track-type="bookNav" track-name="click" track-metadata-eventdetail="/text/guide/unicode" ><span class="devsite-nav-text" tooltip>Unicode</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/text/guide/subwords_tokenizer" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /text/guide/subwords_tokenizer" track-type="bookNav" track-name="click" track-metadata-eventdetail="/text/guide/subwords_tokenizer" ><span class="devsite-nav-text" tooltip>Subword Tokenization</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-divider devsite-nav-heading"><div class="devsite-nav-title devsite-nav-title-no-path"> <span class="devsite-nav-text" tooltip>Advanced</span> </div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Customization</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/customization/basics" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/customization/basics" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/customization/basics" ><span class="devsite-nav-text" tooltip>Tensors and operations</span></a></li><li class="devsite-nav-item"><a href="/tutorials/customization/custom_layers" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/customization/custom_layers" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/customization/custom_layers" ><span class="devsite-nav-text" tooltip>Custom layers</span></a></li><li class="devsite-nav-item"><a href="/tutorials/customization/custom_training_walkthrough" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/customization/custom_training_walkthrough" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/customization/custom_training_walkthrough" ><span class="devsite-nav-text" tooltip>Custom training: walkthrough</span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Distributed training</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/distribute/keras" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/keras" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/keras" ><span class="devsite-nav-text" tooltip>Distributed training with Keras</span></a></li><li class="devsite-nav-item devsite-nav-experimental"><a href="/tutorials/distribute/dtensor_ml_tutorial" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/dtensor_ml_tutorial" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/dtensor_ml_tutorial" ><span class="devsite-nav-text" tooltip>Distributed training with DTensors</span><span class="devsite-nav-icon material-icons" data-icon="experimental" data-title="Experimental!" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-experimental"><a href="/tutorials/distribute/dtensor_keras_tutorial" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/dtensor_keras_tutorial" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/dtensor_keras_tutorial" ><span class="devsite-nav-text" tooltip>Using DTensors with Keras</span><span class="devsite-nav-icon material-icons" data-icon="experimental" data-title="Experimental!" aria-hidden="true"></span></a></li><li class="devsite-nav-item"><a href="/tutorials/distribute/custom_training" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/custom_training" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/custom_training" ><span class="devsite-nav-text" tooltip>Custom training loops</span></a></li><li class="devsite-nav-item"><a href="/tutorials/distribute/multi_worker_with_keras" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/multi_worker_with_keras" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/multi_worker_with_keras" ><span class="devsite-nav-text" tooltip>Multi-worker training with Keras</span></a></li><li class="devsite-nav-item"><a href="/tutorials/distribute/multi_worker_with_ctl" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/multi_worker_with_ctl" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/multi_worker_with_ctl" ><span class="devsite-nav-text" tooltip>Multi-worker training with CTL</span></a></li><li class="devsite-nav-item devsite-nav-experimental"><a href="/tutorials/distribute/parameter_server_training" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/parameter_server_training" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/parameter_server_training" ><span class="devsite-nav-text" tooltip>Parameter Server Training</span><span class="devsite-nav-icon material-icons" data-icon="experimental" data-title="Experimental!" aria-hidden="true"></span></a></li><li class="devsite-nav-item"><a href="/tutorials/distribute/save_and_load" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/save_and_load" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/save_and_load" ><span class="devsite-nav-text" tooltip>Save and load</span></a></li><li class="devsite-nav-item"><a href="/tutorials/distribute/input" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/distribute/input" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/distribute/input" ><span class="devsite-nav-text" tooltip>Distributed input</span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Vision</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/images" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images" ><span class="devsite-nav-text" tooltip>Computer vision</span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="https://keras.io/keras_cv/" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: https://keras.io/keras_cv/" track-type="bookNav" track-name="click" track-metadata-eventdetail="https://keras.io/keras_cv/" ><span class="devsite-nav-text" tooltip>KerasCV</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/cnn" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/cnn" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/cnn" ><span class="devsite-nav-text" tooltip>Convolutional Neural Network</span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/classification" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/classification" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/classification" ><span class="devsite-nav-text" tooltip>Image classification</span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/transfer_learning" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/transfer_learning" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/transfer_learning" ><span class="devsite-nav-text" tooltip>Transfer learning and fine-tuning</span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/transfer_learning_with_hub" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/transfer_learning_with_hub" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/transfer_learning_with_hub" ><span class="devsite-nav-text" tooltip>Transfer learning with TF Hub</span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/data_augmentation" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/data_augmentation" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/data_augmentation" ><span class="devsite-nav-text" tooltip>Data Augmentation</span></a></li><li class="devsite-nav-item"><a href="/tutorials/images/segmentation" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/images/segmentation" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/images/segmentation" ><span class="devsite-nav-text" tooltip>Image segmentation</span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/hub/tutorials/tf2_object_detection" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /hub/tutorials/tf2_object_detection" track-type="bookNav" track-name="click" track-metadata-eventdetail="/hub/tutorials/tf2_object_detection" ><span class="devsite-nav-text" tooltip>Object detection with TF Hub</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-new"><a href="/tutorials/video/video_classification" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/video/video_classification" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/video/video_classification" ><span class="devsite-nav-text" tooltip>Video classification</span><span class="devsite-nav-icon material-icons" data-icon="new" data-title="New!" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-new"><a href="/tutorials/video/transfer_learning_with_movinet" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/video/transfer_learning_with_movinet" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/video/transfer_learning_with_movinet" ><span class="devsite-nav-text" tooltip>Transfer learning with MoViNet</span><span class="devsite-nav-icon material-icons" data-icon="new" data-title="New!" aria-hidden="true"></span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Text</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/text" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/text" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/text" ><span class="devsite-nav-text" tooltip>Text and natural language processing</span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="https://keras.io/guides/keras_nlp/getting_started/" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: https://keras.io/guides/keras_nlp/getting_started/" track-type="bookNav" track-name="click" track-metadata-eventdetail="https://keras.io/guides/keras_nlp/getting_started/" ><span class="devsite-nav-text" tooltip>Get started with KerasNLP</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/text" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /text" track-type="bookNav" track-name="click" track-metadata-eventdetail="/text" ><span class="devsite-nav-text" tooltip>Text and NLP guide</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Audio</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/audio/simple_audio" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/audio/simple_audio" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/audio/simple_audio" ><span class="devsite-nav-text" tooltip>Simple audio recognition</span></a></li><li class="devsite-nav-item"><a href="/tutorials/audio/transfer_learning_audio" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/audio/transfer_learning_audio" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/audio/transfer_learning_audio" ><span class="devsite-nav-text" tooltip>Transfer learning for audio recognition</span></a></li><li class="devsite-nav-item"><a href="/tutorials/audio/music_generation" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/audio/music_generation" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/audio/music_generation" ><span class="devsite-nav-text" tooltip>Generate music with an RNN</span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Structured data</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/structured_data/preprocessing_layers" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/structured_data/preprocessing_layers" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/structured_data/preprocessing_layers" ><span class="devsite-nav-text" tooltip>Classify structured data with preprocessing layers</span></a></li><li class="devsite-nav-item"><a href="/tutorials/structured_data/imbalanced_data" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/structured_data/imbalanced_data" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/structured_data/imbalanced_data" ><span class="devsite-nav-text" tooltip>Classification on imbalanced data</span></a></li><li class="devsite-nav-item"><a href="/tutorials/structured_data/time_series" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/structured_data/time_series" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/structured_data/time_series" ><span class="devsite-nav-text" tooltip>Time series forecasting</span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/decision_forests/tutorials/beginner_colab" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /decision_forests/tutorials/beginner_colab" track-type="bookNav" track-name="click" track-metadata-eventdetail="/decision_forests/tutorials/beginner_colab" ><span class="devsite-nav-text" tooltip>Decision forest models</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/recommenders/examples/quickstart" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /recommenders/examples/quickstart" track-type="bookNav" track-name="click" track-metadata-eventdetail="/recommenders/examples/quickstart" ><span class="devsite-nav-text" tooltip>Recommenders</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Generative</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item devsite-nav-new"><a href="/tutorials/generative/generate_images_with_stable_diffusion" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/generate_images_with_stable_diffusion" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/generate_images_with_stable_diffusion" ><span class="devsite-nav-text" tooltip>Stable Diffusion</span><span class="devsite-nav-icon material-icons" data-icon="new" data-title="New!" aria-hidden="true"></span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/style_transfer" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/style_transfer" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/style_transfer" ><span class="devsite-nav-text" tooltip>Neural style transfer</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/deepdream" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/deepdream" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/deepdream" ><span class="devsite-nav-text" tooltip>DeepDream</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/dcgan" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/dcgan" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/dcgan" ><span class="devsite-nav-text" tooltip>DCGAN</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/pix2pix" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/pix2pix" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/pix2pix" ><span class="devsite-nav-text" tooltip>Pix2Pix</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/cyclegan" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/cyclegan" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/cyclegan" ><span class="devsite-nav-text" tooltip>CycleGAN</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/adversarial_fgsm" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/adversarial_fgsm" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/adversarial_fgsm" ><span class="devsite-nav-text" tooltip>Adversarial FGSM</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/autoencoder" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/autoencoder" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/autoencoder" ><span class="devsite-nav-text" tooltip>Intro to Autoencoders</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/cvae" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/cvae" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/cvae" ><span class="devsite-nav-text" tooltip>Variational Autoencoder</span></a></li><li class="devsite-nav-item"><a href="/tutorials/generative/data_compression" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/generative/data_compression" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/generative/data_compression" ><span class="devsite-nav-text" tooltip>Lossy data compression</span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Model optimization</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/optimization/compression" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /tutorials/optimization/compression" track-type="bookNav" track-name="click" track-metadata-eventdetail="/tutorials/optimization/compression" ><span class="devsite-nav-text" tooltip>Scalable model compression with EPR</span></a></li><li class="devsite-nav-item devsite-nav-external"><a href="/model_optimization" class="devsite-nav-title gc-analytics-event" data-category="Site-Wide Custom Events" data-label="Book nav link, pathname: /model_optimization" track-type="bookNav" track-name="click" track-metadata-eventdetail="/model_optimization" ><span class="devsite-nav-text" tooltip>TensorFlow model optimization</span><span class="devsite-nav-icon material-icons" data-icon="external" data-title="External" aria-hidden="true"></span></a></li></ul></div></li> <li class="devsite-nav-item devsite-nav-expandable devsite-nav-accordion"><div class="devsite-expandable-nav"> <a class="devsite-nav-toggle" aria-hidden="true"></a><div class="devsite-nav-title devsite-nav-title-no-path" tabindex="0" role="button"> <span class="devsite-nav-text" tooltip>Model Understanding</span> </div><ul class="devsite-nav-section"><li class="devsite-nav-item"><a href="/tutorials/interpretability/integrated_gradients" 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analytics-category="Site-Wide Custom Events" analytics-action-show="Callout Profile displayed" analytics-action-close="Callout Profile dismissed" analytics-label="Create Collection Callout" class="devsite-page-bookmark-tooltip nocontent" dismiss-button="true" id="devsite-collections-dropdown" dismiss-button-text="Dismiss" close-button-text="Got 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> <div class="devsite-page-title-meta"><devsite-view-release-notes></devsite-view-release-notes></div> <devsite-toc class="devsite-nav" depth="2" devsite-toc-embedded > </devsite-toc> <div class="devsite-article-body clearfix "> <p></p>  <div itemscope itemtype="http://developers.google.com/ReferenceObject"> <meta itemprop="name" content="TensorFlow 2 quickstart for beginners" /> <meta itemprop="path" content="Guide & Tutorials" /> <meta itemprop="property" content="tf.keras.Sequential"/> <meta itemprop="property" content="tf.keras.layers.Dense"/> <meta itemprop="property" content="tf.keras.layers.Dropout"/> <meta itemprop="property" content="tf.keras.layers.Flatten"/> <meta itemprop="property" content="tf.keras.layers.Softmax"/> <meta itemprop="property" content="tf.keras.losses.SparseCategoricalCrossentropy"/> <meta itemprop="property" content="tf.nn.softmax"/> </div> <table class="tfo-notebook-buttons" align="left"> <td> <a target="_blank" href="https://www.tensorflow.org/tutorials/quickstart/beginner"><img src="https://www.tensorflow.org/images/tf_logo_32px.png">View on TensorFlow.org</a> </td> <td> <a target="_blank" href="https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png">Run in Google Colab</a> </td> <td> <a target="_blank" href="https://github.com/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb"><img src="https://www.tensorflow.org/images/GitHub-Mark-32px.png">View source on GitHub</a> </td> <td> <a href="https://storage.googleapis.com/tensorflow_docs/docs/site/en/tutorials/quickstart/beginner.ipynb"><img src="https://www.tensorflow.org/images/download_logo_32px.png">Download notebook</a> </td> </table> <p>This short introduction uses <a href="https://www.tensorflow.org/guide/keras/overview">Keras</a> to:</p> <ol> <li>Load a prebuilt dataset.</li> <li>Build a neural network machine learning model that classifies images.</li> <li>Train this neural network.</li> <li>Evaluate the accuracy of the model.</li> </ol> <p>This tutorial is a <a href="https://colab.research.google.com/notebooks/welcome.ipynb">Google Colaboratory</a> notebook. Python programs are run directly in the browser—a great way to learn and use TensorFlow. To follow this tutorial, run the notebook in Google Colab by clicking the button at the top of this page.</p> <ol> <li>In Colab, connect to a Python runtime: At the top-right of the menu bar, select <em>CONNECT</em>.</li> <li>To run all the code in the notebook, select <strong>Runtime</strong> > <strong>Run all</strong>. To run the code cells one at a time, hover over each cell and select the <strong>Run cell</strong> icon.</li> </ol> <p><img src="/static/tutorials/quickstart/images/beginner/run_cell_icon.png" alt="Run cell icon"></p> <h2 id="set_up_tensorflow" data-text="Set up TensorFlow" tabindex="-1">Set up TensorFlow</h2> <p>Import TensorFlow into your program to get started:</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><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-nb">print</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-s2">"TensorFlow version:"</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">__version__</span><span class="devsite-syntax-p">)</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> 2024-08-16 07&colon;45&colon;15.387747&colon; E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc&colon;485] Unable to register cuFFT factory&colon; Attempting to register factory for plugin cuFFT when one has already been registered 2024-08-16 07&colon;45&colon;15.408731&colon; E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc&colon;8454] Unable to register cuDNN factory&colon; Attempting to register factory for plugin cuDNN when one has already been registered 2024-08-16 07&colon;45&colon;15.415209&colon; E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc&colon;1452] Unable to register cuBLAS factory&colon; Attempting to register factory for plugin cuBLAS when one has already been registered TensorFlow version&colon; 2.17.0 </pre></devsite-code> <p>If you are following along in your own development environment, rather than <a href="https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/beginner.ipynb">Colab</a>, see the <a href="https://www.tensorflow.org/install">install guide</a> for setting up TensorFlow for development.</p> <aside class="note"><strong>Note:</strong><span> Make sure you have upgraded to the latest <code translate="no" dir="ltr">pip</code> to install the TensorFlow 2 package if you are using your own development environment. See the <a href="https://www.tensorflow.org/install">install guide</a> for details.</span></aside> <h2 id="load_a_dataset" data-text="Load a dataset" tabindex="-1">Load a dataset</h2> <p>Load and prepare the MNIST dataset. The pixel values of the images range from 0 through 255. Scale these values to a range of 0 to 1 by dividing the values by <code translate="no" dir="ltr">255.0</code>. This also converts the sample data from integers to floating-point numbers:</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">mnist</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-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-p">(</span><span class="devsite-syntax-n">x_test</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">y_test</span><span class="devsite-syntax-p">)</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">x_test</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">x_train</span> <span class="devsite-syntax-o">/</span> <span class="devsite-syntax-mf">255.0</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">x_test</span> <span class="devsite-syntax-o">/</span> <span class="devsite-syntax-mf">255.0</span> </code></pre></devsite-code> <h2 id="build_a_machine_learning_model" data-text="Build a machine learning model" tabindex="-1">Build a machine learning model</h2> <p>Build a <a href="https://www.tensorflow.org/api_docs/python/tf/keras/Sequential"><code translate="no" dir="ltr">tf.keras.Sequential</code></a> model:</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><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">models</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">Flatten</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">input_shape</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-mi">28</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-mi">28</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">128</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">'relu'</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">Dropout</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-mf">0.2</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-p">])</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> /tmpfs/src/tf_docs_env/lib/python3.9/site-packages/keras/src/layers/reshaping/flatten.py&colon;37&colon; UserWarning&colon; Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead. super().__init__(**kwargs) WARNING&colon; All log messages before absl&colon;&colon;InitializeLog() is called are written to STDERR I0000 00&colon;00&colon;1723794318.490455 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.494342 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.497584 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.501312 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.512702 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.516197 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.519187 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.522647 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.526047 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.529503 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.532428 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794318.535893 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.771712 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.773840 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.775826 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.777872 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.779874 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.781821 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.783693 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.785644 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.787540 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.789499 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.791369 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.793317 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.831749 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.833814 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.835738 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.837736 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.839701 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.841655 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.843526 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.845500 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.847443 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.849923 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.852250 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 I0000 00&colon;00&colon;1723794319.854736 241277 cuda_executor.cc&colon;1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https&colon;//github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355 </pre></devsite-code> <p><a href="https://www.tensorflow.org/guide/keras/sequential_model"><code translate="no" dir="ltr">Sequential</code></a> is useful for stacking layers where each layer has one input <a href="https://www.tensorflow.org/guide/tensor">tensor</a> and one output tensor. Layers are functions with a known mathematical structure that can be reused and have trainable variables. Most TensorFlow models are composed of layers. This model uses the <a href="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Flatten"><code translate="no" dir="ltr">Flatten</code></a>, <a href="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense"><code translate="no" dir="ltr">Dense</code></a>, and <a href="https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dropout"><code translate="no" dir="ltr">Dropout</code></a> layers.</p> <p>For each example, the model returns a vector of <a href="https://developers.google.com/machine-learning/glossary#logits">logits</a> or <a href="https://developers.google.com/machine-learning/glossary#log-odds">log-odds</a> scores, one for each class.</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">predictions</span> <span class="devsite-syntax-o">=</span> <span class="devsite-syntax-n">model</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-mi">1</span><span class="devsite-syntax-p">])</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">numpy</span><span class="devsite-syntax-p">()</span> <span class="devsite-syntax-n">predictions</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> array([[ 0.68130803, -0.03935227, -0.53304887, 0.22200397, -0.3079031 , -0.6267688 , 0.43393654, 0.5691322 , 0.31098977, 0.32141146]], dtype=float32) </pre></devsite-code> <p>The <a href="https://www.tensorflow.org/api_docs/python/tf/nn/softmax"><code translate="no" dir="ltr">tf.nn.softmax</code></a> function converts these logits to <em>probabilities</em> for each class: </p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">tf</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">nn</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">softmax</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">predictions</span><span class="devsite-syntax-p">)</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">numpy</span><span class="devsite-syntax-p">()</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> array([[0.16339162, 0.07947874, 0.04851112, 0.10321827, 0.06076043, 0.0441712 , 0.12758444, 0.14605366, 0.11282429, 0.11400625]], dtype=float32) </pre></devsite-code> <aside class="note"><strong>Note:</strong><span> It is possible to bake the <a href="https://www.tensorflow.org/api_docs/python/tf/nn/softmax"><code translate="no" dir="ltr">tf.nn.softmax</code></a> function into the activation function for the last layer of the network. While this can make the model output more directly interpretable, this approach is discouraged as it's impossible to provide an exact and numerically stable loss calculation for all models when using a softmax output. </span></aside> <p>Define a loss function for training using <a href="https://www.tensorflow.org/api_docs/python/tf/keras/losses/SparseCategoricalCrossentropy"><code translate="no" dir="ltr">losses.SparseCategoricalCrossentropy</code></a>:</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">loss_fn</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">losses</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">SparseCategoricalCrossentropy</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">from_logits</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-kc">True</span><span class="devsite-syntax-p">)</span> </code></pre></devsite-code> <p>The loss function takes a vector of ground truth values and a vector of logits and returns a scalar loss for each example. This loss is equal to the negative log probability of the true class: The loss is zero if the model is sure of the correct class.</p> <p>This untrained model gives probabilities close to random (1/10 for each class), so the initial loss should be close to <code translate="no" dir="ltr">-tf.math.log(1/10) ~= 2.3</code>.</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">loss_fn</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-mi">1</span><span class="devsite-syntax-p">],</span> <span class="devsite-syntax-n">predictions</span><span class="devsite-syntax-p">)</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">numpy</span><span class="devsite-syntax-p">()</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> 3.1196823 </pre></devsite-code> <p>Before you start training, configure and compile the model using Keras <a href="https://www.tensorflow.org/api_docs/python/tf/keras/Model#compile"><code translate="no" dir="ltr">Model.compile</code></a>. Set the <a href="https://www.tensorflow.org/api_docs/python/tf/keras/optimizers"><code translate="no" dir="ltr">optimizer</code></a> class to <code translate="no" dir="ltr">adam</code>, set the <code translate="no" dir="ltr">loss</code> to the <code translate="no" dir="ltr">loss_fn</code> function you defined earlier, and specify a metric to be evaluated for the model by setting the <code translate="no" dir="ltr">metrics</code> parameter to <code translate="no" dir="ltr">accuracy</code>.</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><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-s1">'adam'</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">loss_fn</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-s1">'accuracy'</span><span class="devsite-syntax-p">])</span> </code></pre></devsite-code> <h2 id="train_and_evaluate_your_model" data-text="Train and evaluate your model" tabindex="-1">Train and evaluate your model</h2> <p>Use the <a href="https://www.tensorflow.org/api_docs/python/tf/keras/Model#fit"><code translate="no" dir="ltr">Model.fit</code></a> method to adjust your model parameters and minimize the loss: </p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><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">5</span><span class="devsite-syntax-p">)</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> Epoch 1/5 WARNING&colon; All log messages before absl&colon;&colon;InitializeLog() is called are written to STDERR I0000 00&colon;00&colon;1723794322.305243 241442 service.cc&colon;146] XLA service 0x7effb8008d30 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices&colon; I0000 00&colon;00&colon;1723794322.305276 241442 service.cc&colon;154] StreamExecutor device (0)&colon; Tesla T4, Compute Capability 7.5 I0000 00&colon;00&colon;1723794322.305281 241442 service.cc&colon;154] StreamExecutor device (1)&colon; Tesla T4, Compute Capability 7.5 I0000 00&colon;00&colon;1723794322.305284 241442 service.cc&colon;154] StreamExecutor device (2)&colon; Tesla T4, Compute Capability 7.5 I0000 00&colon;00&colon;1723794322.305287 241442 service.cc&colon;154] StreamExecutor device (3)&colon; Tesla T4, Compute Capability 7.5 112/1875 ━━━━━━━━━━━━━━━━━━━━ 2s 1ms/step - accuracy&colon; 0.6089 - loss&colon; 1.3300 I0000 00&colon;00&colon;1723794323.392324 241442 device_compiler.h&colon;188] Compiled cluster using XLA! This line is logged at most once for the lifetime of the process. 1875/1875 ━━━━━━━━━━━━━━━━━━━━ 4s 1ms/step - accuracy&colon; 0.8622 - loss&colon; 0.4811 Epoch 2/5 1875/1875 ━━━━━━━━━━━━━━━━━━━━ 2s 1ms/step - accuracy&colon; 0.9547 - loss&colon; 0.1539 Epoch 3/5 1875/1875 ━━━━━━━━━━━━━━━━━━━━ 2s 1ms/step - accuracy&colon; 0.9676 - loss&colon; 0.1107 Epoch 4/5 1875/1875 ━━━━━━━━━━━━━━━━━━━━ 2s 1ms/step - accuracy&colon; 0.9738 - loss&colon; 0.0843 Epoch 5/5 1875/1875 ━━━━━━━━━━━━━━━━━━━━ 2s 1ms/step - accuracy&colon; 0.9764 - loss&colon; 0.0769 <keras.src.callbacks.history.History at 0x7f0184ec7490> </pre></devsite-code> <p>The <a href="https://www.tensorflow.org/api_docs/python/tf/keras/Model#evaluate"><code translate="no" dir="ltr">Model.evaluate</code></a> method checks the model's performance, usually on a <a href="https://developers.google.com/machine-learning/glossary#validation-set">validation set</a> or <a href="https://developers.google.com/machine-learning/glossary#test-set">test set</a>.</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">model</span><span class="devsite-syntax-o">.</span><span class="devsite-syntax-n">evaluate</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">x_test</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">y_test</span><span class="devsite-syntax-p">,</span> <span class="devsite-syntax-n">verbose</span><span class="devsite-syntax-o">=</span><span class="devsite-syntax-mi">2</span><span class="devsite-syntax-p">)</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> 313/313 - 1s - 3ms/step - accuracy&colon; 0.9782 - loss&colon; 0.0729 [0.07293704897165298, 0.9782000184059143] </pre></devsite-code> <p>The image classifier is now trained to ~98% accuracy on this dataset. To learn more, read the <a href="https://www.tensorflow.org/tutorials/">TensorFlow tutorials</a>.</p> <p>If you want your model to return a probability, you can wrap the trained model, and attach the softmax to it:</p> <div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">probability_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">model</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">Softmax</span><span class="devsite-syntax-p">()</span> <span class="devsite-syntax-p">])</span> </code></pre></devsite-code><div></div><devsite-code><pre class="devsite-click-to-copy" translate="no" dir="ltr" is-upgraded syntax="Python"><code translate="no" dir="ltr"><span class="devsite-syntax-n">probability_model</span><span class="devsite-syntax-p">(</span><span class="devsite-syntax-n">x_test</span><span class="devsite-syntax-p">[:</span><span class="devsite-syntax-mi">5</span><span class="devsite-syntax-p">])</span> </code></pre></devsite-code> <div></div><devsite-code><pre class="tfo-notebook-code-cell-output" translate="no" dir="ltr" is-upgraded> <tf.Tensor&colon; shape=(5, 10), dtype=float32, numpy= array([[1.5427084e-07, 7.5027339e-11, 3.1343968e-06, 4.6326011e-05, 8.9990645e-13, 1.5266414e-07, 2.0456495e-13, 9.9994934e-01, 2.1858141e-07, 7.8530559e-07], [1.7771253e-08, 8.4947787e-05, 9.9989736e-01, 1.8331458e-06, 8.3026415e-15, 3.4793761e-08, 6.2480517e-08, 7.9319728e-12, 1.5733674e-05, 3.5440111e-15], [3.3602277e-07, 9.9804592e-01, 5.7737787e-05, 5.8099768e-06, 6.3599517e-05, 2.3768812e-06, 2.3459031e-06, 1.6781164e-03, 1.4260423e-04, 1.0617223e-06], [9.9997318e-01, 8.7561805e-11, 9.8983969e-07, 9.0878149e-10, 1.0803159e-07, 3.3033965e-07, 2.3622524e-05, 6.7567669e-07, 4.7765565e-09, 1.1131582e-06], [1.1404303e-05, 2.4895797e-09, 6.0792736e-06, 4.9114313e-08, 9.9449867e-01, 5.9158310e-06, 2.9842497e-05, 4.8574508e-05, 8.5193824e-06, 5.3910208e-03]], dtype=float32)> </pre></devsite-code> <h2 id="conclusion" data-text="Conclusion" tabindex="-1">Conclusion</h2> <p>Congratulations! You have trained a machine learning model using a prebuilt dataset using the <a href="https://www.tensorflow.org/guide/keras/overview">Keras</a> API.</p> <p>For more examples of using Keras, check out the <a href="https://www.tensorflow.org/tutorials/keras/">tutorials</a>. To learn more about building models with Keras, read the <a href="https://www.tensorflow.org/guide/keras">guides</a>. If you want learn more about loading and preparing data, see the tutorials on <a href="https://www.tensorflow.org/tutorials/load_data/images">image data loading</a> or <a href="https://www.tensorflow.org/tutorials/load_data/csv">CSV data loading</a>.</p> </div> <devsite-thumb-rating position="footer"> </devsite-thumb-rating> <div class="devsite-floating-action-buttons"> </div> </article> <devsite-content-footer class="nocontent"> <p>Except as otherwise noted, the content of this page is licensed under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 License</a>, and code samples are licensed under the <a href="https://www.apache.org/licenses/LICENSE-2.0">Apache 2.0 License</a>. For details, see the <a href="https://developers.google.com/site-policies">Google Developers Site Policies</a>. 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