@MJKlaiber @areusch I’ve ran the latest uma test pipeline on a custom tflite model and would like to raise one issue. I checked out the latest TVM on main branch (SHA1 038f15b5e204120709186a8791e5b49986060bb0). Then ran tvm/tests/python/contrib/test_uma/test_uma_pipeline.py UMA successfully generated .c code, and here is the issue: The c code for convolution implementation is repeated for each convolution function.
e.g. tvmgen_default_vanilla_accelerator_main_0, tvmgen_default_vanilla_accelerator_main_1, … tvmgen_default_vanilla_accelerator_main_k
These functions contain the same convolution implementation code. Based on Michael’s RFC I assumed there would be multiple calls to the Vanila my_ai_hw_conv2dnchw() function with the relevant kernel and input sizes.
Please let me know what you think, whether this is the way TVM is built, or maybe I did some mistake in my setup. How can UMA generate a .c code that will call my custom convolution implementation (function call and not a duplicated c code)?
Thanks, Slava.