TensorFlow Lite inference typically follows the following steps: This page describes how to access to the TensorFlow Lite interpreter and performĪn inference using C++, Java, and Python, plus links to other resources for each The interpreter uses a static graph ordering and a custom (less-dynamic) memoryĪllocator to ensure minimal load, initialization, and execution latency. The TensorFlow Lite interpreter is designed to be lean and fast. Inference with a TensorFlow Lite model, you must run it through an On-device in order to make predictions based on input data. The term inference refers to the process of executing a TensorFlow Lite model
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