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python/03-May-2024-786585

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tensorflow_graph_matching/03-May-2024-1,117734

tflite/03-May-2024-7,2395,803

BUILDD03-May-202416.4 KiB507483

README.mdD03-May-20241.3 KiB3022

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allocate_transient_arrays.hD03-May-20241.9 KiB4513

args.ccD03-May-20246.1 KiB172118

args.hD03-May-20247.2 KiB197126

dump_graphviz.ccD03-May-202426.2 KiB786583

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export_tensorflow.ccD03-May-2024108.7 KiB2,5592,301

export_tensorflow.hD03-May-20241.1 KiB3110

format_port.hD03-May-20242.6 KiB7234

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import_tensorflow_test.ccD03-May-202424.7 KiB740578

model.hD03-May-202477.3 KiB2,4911,063

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model_cmdline_flags_test.ccD03-May-20242.3 KiB6743

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tensorflow_util.ccD03-May-20247.6 KiB200180

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toco.ccD03-May-20242.2 KiB5936

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toco_cmdline_flags.hD03-May-20241.6 KiB3815

toco_cmdline_flags_test.ccD03-May-20241.9 KiB6132

toco_convert.ccD03-May-20244.8 KiB11478

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toco_flags.protoD03-May-202410.9 KiB238205

toco_graphviz_dump_options.ccD03-May-2024887 237

toco_graphviz_dump_options.hD03-May-20241.1 KiB3311

toco_port.ccD03-May-20247.8 KiB278208

toco_port.hD03-May-20243.8 KiB12082

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toco_tooling.ccD03-May-202421.3 KiB514389

toco_tooling.hD03-May-20242.3 KiB6029

toco_types.hD03-May-20241.1 KiB3817

tooling_util.ccD03-May-202488.3 KiB2,4742,152

tooling_util.hD03-May-202415.3 KiB370201

tooling_util_test.ccD03-May-20247.5 KiB215152

types.protoD03-May-20241.5 KiB7152

README.md

1# TensorFlow Lite Converter
2
3The TensorFlow Lite Converter converts TensorFlow graphs into
4TensorFlow Lite graphs. There are additional usages that are also detailed in
5the usage documentation.
6
7## Usage documentation
8
9Usage information is given in these documents:
10
11*   [Command-line glossary](../g3doc/r1/convert/cmdline_reference.md)
12*   [Command-line examples](../g3doc/r1/convert/cmdline_examples.md)
13*   [Python API examples](../g3doc/r1/convert/python_api.md)
14
15## Where the converter fits in the TensorFlow landscape
16
17Once an application developer has a trained TensorFlow model, the TensorFlow
18Lite Converter will accept
19that model and generate a TensorFlow Lite
20[FlatBuffer](https://google.github.io/flatbuffers/) file. The converter currently supports
21[SavedModels](https://www.tensorflow.org/guide/saved_model#using_savedmodel_with_estimators),
22frozen graphs (models generated via
23[freeze_graph.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py)),
24and `tf.Keras` model files.  The TensorFlow Lite FlatBuffer file can be shipped
25to client devices, generally mobile devices, where the TensorFlow Lite
26interpreter handles them on-device.  This flow is represented in the diagram
27below.
28
29![drawing](../g3doc/r1/images/convert/workflow.svg)
30