From TensorFlow / TFLite

About Tensorflow

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.[4][5]
TensorFlow was developed by the Google Brain team for internal Google use in research and production.[6][7][8] The initial version was released under the Apache License 2.0 in 2015.[1][9]Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019.[10]
TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java.[11] This flexibility lends itself to a range of applications in many different sectors.

Model deployment from Tensorflow

Model deployment from Tensorflow (or the subeset of tensorflow optimized for edge devices called tflite) is simple to achieve by exporting your Tensorflow model to ONNX and subsequently using (if neccesary) the sclblonnx package to clean and check the resulting graph for an upload to the Scailable platform.
  • Exporting from TF to ONNX is easy using the tf2onnx tools. Alternatively, you can use keras2onnx.
  • You can find an example using keras2onnx and sclblonnx here.
  • We provide a super simply utility to convert TensorFlowLite models to ONNX as a webservice here.