Hi,
I am working through the gallery/how_to/work_with_microtvm/micro_aot.py tutorial in order to get to know how to run microTVM with mlperf tiny. I am running the inference on the host machine, i.e. no micro controller involved. The example works as described, but I am struggling with preparing the input data for different examples. The input data are presented to TVM as numpy arrays, but I do not know how to convert the input data into the correct format. E.g. The KWS dataset provided by Google consists of wav files, which are converted to nested int8 numpy arrays of shape (1, 49, 10, 1).
How do I make this conversion? And what does this shape represent?
In order to get some understanding, I tried to convert the given npy files to wav files, but with no success. I am aware of the repo github.com/tlc-pack/web-data which contains prepared input for the tests/micro/common/test_mlperftiny.py example, but they did not provide a script or documentation how they did this preparaion.
Thank you and best regards, Benedikt