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STT-tensorflow/tensorflow/lite/testing/model_coverage
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Thai Nguyen 2eea17699f Support MaxUnpooling2D in TFLite converter 
PiperOrigin-RevId: 348406335
Change-Id: Iaf6293114beb9f76a9e856f752a378961b017bfc
2020-12-20 20:13:00 -08:00
..
testdata Quantization tests: compare TFLite model output agains pre-computed golden values. 2020-12-16 23:26:25 -08:00
BUILD Remove keras dependency from TFLite tests and BUILD files 2020-10-31 10:02:05 -07:00
model_coverage_lib_test.py Remove keras dependency from TFLite tests and BUILD files 2020-10-31 10:02:05 -07:00
model_coverage_lib.py Support MaxUnpooling2D in TFLite converter 2020-12-20 20:13:00 -08:00
README.md Quantization tests: compare TFLite model output agains pre-computed golden values. 2020-12-16 23:26:25 -08:00

README.md

TensorFlow Lite model coverage tests

Various conversion tests on popular mobile models.

Golden values

Some tests rely on pre-computed golden values. The main goal is to detect changes affecting unintended parts of TFLite.

Should a golden value test fail after an intended change, the golden values can be updated with the following command:

bazel run //third_party/tensorflow/lite/testing/model_coverage:<target> --test_output=all -- --update_goldens

Notice bazel run instead of bazel test and the addition of the --update_golden flag.

The updated golden data files must then be included in the change list.