mbarrett97 commented on a change in pull request #4543: [FRONTEND][TFLITE] Add support for TFLite_Detection_PostProcess URL: https://github.com/apache/incubator-tvm/pull/4543#discussion_r371276909
########## File path: tests/python/frontend/tflite/test_forward.py ########## @@ -1113,6 +1113,49 @@ def test_forward_fully_connected(): _test_fully_connected([5, 1, 1, 150], [150, 100], [100]) +####################################################################### +# Custom Operators +# ------- + +def test_detection_postprocess(): + tf_model_file = tf_testing.get_workload_official( + "http://download.tensorflow.org/models/object_detection/" + "ssd_mobilenet_v2_quantized_300x300_coco_2019_01_03.tar.gz", Review comment: This test is a bit misleading because it doesn't actually run ssd mobilenet, it just test the postprocess op. I couldn't find a way to create the op using the tflite python API, so what I did instead was take a model that has it and then run it through the tflite converter but with the converter inputs set to the inputs of the postprocess op rather than the input to the network. This has the net effect of producing a single postprocess op, so this should already be a unit test (and it passes). I can add the end-to-end tests if/when we resolve the QNN accuracy issue. I'll open an RFC shortly to describe why rounding is a particularly significant in the case of this operator. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services