Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler

The article introduces the `torch.profiler` tool in PyTorch, designed to help developers analyze and optimize the performance of their models. It details the API's features, including the ability to record and visualize performance metrics such as CPU and GPU utilization, memory consumption, and execution time of operations. This tool is crucial for practitioners aiming to enhance the efficiency of their deep learning workflows, particularly in identifying bottlenecks and optimizing resource usage.