October 2018
Intermediate to advanced
246 pages
6h 26m
English
TensorFlow uses FlatBuffers for the model. FlatBuffers is a cross-platform, open source serialization library. The main advantage of using FlatBuffers is that it does not need a secondary representation before accessing the data through packing/unpacking. It is often coupled with per-object memory allocation. FlatBuffers is more memory-efficient than Protocol Buffers because it helps us to keep the memory footprint small.
FlatBuffers was originally developed for gaming platforms. It is also used in other platforms since it is performance-sensitive. At the time of conversion, TensorFlow Lite pre-fuses the activations and biases, allowing TensorFlow Lite to execute faster. The interpreter uses static ...
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