✳flâneur — a map of the web's best reading

⏱️ Performance Profiling - Composer

docs.mosaicml.com · 1,497 words · saved by 1 readers

Introduction: The Composer Profiler enables practitioners to collect, analyze, and visualize performance metrics during training which can be used to diagnose bottlenecks and facilitate model devel...

⏱️ Performance Profiling # Introduction # The Composer Profiler enables practitioners to collect, analyze, and visualize performance metrics during training which can be used to diagnose bottlenecks and facilitate model development. The profiler enables users to capture the following metrics: Duration of each Event, Callback, and Algorithm during training Time taken by the data loader to return a batch Host metrics such as CPU, system memory, disk, and network utilization over time Execution order, latency, and attributes of PyTorch operators and GPU kernels (see torch.profiler ) This tutorial

Explore this link on the map →

saved by

related reading