Dynamic quantization has emerged as a cornerstone in the evolution of deep learning optimization, bridging the gap between computational efficiency and model performance. In this article, we dive deep into Dynamic Quantized Kernels in PyTorch, starting with a simplified explanation of quantization and progressively transitioning to advanced concepts, their current applications, and their potential future … Continue reading Dynamic Quantized Kernels in PyTorch: Unlocking Efficient Deep Learning Models