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# TOCO: TensorFlow Lite Optimizing Converter
The TensorFlow Lite Optimizing Converter converts TensorFlow graphs into
TensorFlow Lite graphs. There are additional usages that are also detailed in
the usage documentation.
## Usage documentation
Usage information is given in these documents:
* [Command-line glossary](g3doc/cmdline_reference.md)
* [Command-line examples](g3doc/cmdline_examples.md)
* [Python API examples](g3doc/python_api.md)
## Where the converter fits in the TensorFlow landscape
Once an application developer has a trained TensorFlow model, TOCO will accept
that model and generate a TensorFlow Lite
[FlatBuffer](https://google.github.io/flatbuffers/) file. TOCO currently supports
[SavedModels](https://www.tensorflow.org/guide/saved_model#using_savedmodel_with_estimators),
frozen graphs (models generated via
[freeze_graph.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py)),
and `tf.Keras` model files. The TensorFlow Lite FlatBuffer file can be shipped
to client devices, generally mobile devices, where the TensorFlow Lite
interpreter handles them on-device. This flow is represented in the diagram
below.
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