Kernels, in the context of machine learning, are the optimized computational building blocks that power neural network operations. They are the “engine” of deep learning frameworks like PyTorch, enabling efficient execution of operations such as matrix multiplications, convolutions, and activation functions. This article delves into the role of kernels in PyTorch, their relationship with Just-In-Time … Continue reading Kernels in PyTorch: The Nexus of Efficiency with JIT, TorchScript, and Quantization