ZFTurbo/Keras-inference-time-optimizer

The Keras-inference-time-optimizer is a historical utility that addresses layer fusion, specifically the merging of Batch Normalization (BN) layers into preceding Convolutional or Dense layers. While this was a valuable manual optimization step circa 2016-2018, it has since become a standard, automated feature of virtually every modern inference engine and compiler. Projects like NVIDIA's TensorRT, Intel's OpenVINO, and Google's XLA (Accelerated Linear Algebra) and TFLite perform these optimizations (and many more, such as constant folding and graph pruning) automatically at the graph level. With an age of nearly 8 years and zero current velocity, the project is effectively a legacy tool. Its defensibility is minimal because the logic is well-understood and the niche it served has been absorbed by the primary frameworks (TensorFlow/Keras) and hardware-specific runtimes. A technical investor would classify this as 'solved at the platform level,' making it obsolete for modern production pipelines.