Using the API from your model code should still look familiar, but it's now friendly to eager execution while remaining graph-mode compatible. The two halves are tightly integrated, and now individual tf.summary ops write their data immediately when executed. The v1.rge_all() op made this easier by using a graph collection to aggregate all summary op outputs, but this approach still worked poorly for eager execution and control flow, making it especially ill-suited for TF 2.x. The two halves had to be manually wired together - by fetching the summary op outputs via n() and calling FileWriter.add_summary(output, step). Writing logic that collects these individual summaries and writes them to a specially formatted log file (which TensorBoard then reads to generate visualizations).A set of ops for recording individual summaries - summary.scalar(), summary.histogram(), summary.image(), dio(), and summary.text() - which are called inline from your model code.It's useful to think of the tf.summary API as two sub-APIs: TensorFlow 2.x includes significant changes to the tf.summary API used to write summary data for visualization in TensorBoard. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. 12:08:16.683485: W tensorflow/compiler/tf2tensorrt/utils/py_:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. 12:08:16.683474: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer_plugin.so.7' dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory 12:08:16.683364: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer.so.7' dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory If you are using tf.keras there may be no action you need to take to upgrade to TensorFlow 2.x. If you're new to TensorBoard, see the get started doc instead. Note: This doc is for people who are already familiar with TensorFlow 1.x TensorBoard and who want to migrate large TensorFlow code bases from TensorFlow 1.x to 2.x.
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