Pinterest introduced ModuleLens, a module-first engineering framework for isolated debugging and profiling of PyTorch modules used in large-scale recommendation systems1. The tool comprises three components — ModuleTracer, Module Repo, and a Consumption Layer — with ModuleTracer capturing input/output tensors, parameter weights, and initialization arguments. ModuleLens stores captured modules in a backend built on the Weights & Biases Registry and exposes capabilities through a Jupyter extension, IPython CLI, and agent skills for AI tools including Claude Code and Cursor.
Pinterest Open-Sources ModuleLens for Isolated PyTorch Module Debugging
Pinterest released ModuleLens, a framework for isolated PyTorch module debugging and profiling, with integrations for Jupyter, IPython, and AI coding…