The analysis and refinement of the large-scale deep learning model's performance is a constant challenge that increases in importance with the model’s size. Owing to a lack of available resources, PyTorch users had a hard time overcoming this problem. There were common GPU hardware-level debugging tools, but PyTorch-specific background of operations was not available. Users had to merge multi-tools or apply minimal correlation information manually to make sense of the data to retrieve the missing information. The PyTorch Profiler came to the rescue, an open-source tool for precise, efficient, and troubleshooting performance investigations of large-scale deep learning models.  What is