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torch.profiler # Created On: | Last Updated On: Overview # PyTorch Profiler is a tool that allows the collection of performance metrics during training and inference. Profiler’s context manager API can be used to better understand what model operators are the most expensive, examine their input shapes and stack traces, study device kernel activity and visualize the ...
This tutorial seeks to teach users about using profiling tools such as nvsys, rocprof, and the torch profiler in a simple transformers training loop. We will cover how to use the PyTorch profiler to identify performance bottlenecks, understand GPU efficiency metrics, and perform initial ...
Profiling Schedules: For long training jobs or complex inference pipelines, use the schedule argument to torch.profiler.profile to capture specific iterations after an initial warmup period, avoiding large trace files and focusing on steady-state behavior.