Why is TensorFlow Lite slower than TensorFlow on desktop?

Question

I\'m currently working on Single Image Superresolution and I\'ve managed to freeze an existing checkpoint file and convert it into tensorflow lite. However, when performing

Answer 1

Yes, the current TensorFlow Lite op kernels are optimized for ARM processor (using NEON instruction set). If SSE is available, it will try to use NEON_2_SSE to adapt NEON calls to SSE, so it should be still running with some sort of SIMD. However we didn't put much effort to optimize this code path.

Regarding number of threads. There is a SetNumThreads function in C++ API, but it's not exposed in Python API (yet). When it's not set, the underlying implementation may try to probe number of available cores. If you build the code by yourself, you can try to change the value and see if it affects the result.

Hope these helps.