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Learn advanced debugging techniques for JAX and Flax NNX in this 13-minute tutorial that builds upon foundational debugging concepts to explore more specialized approaches for neural network development. Discover how to temporarily disable JIT compilation to simplify debugging workflows and leverage the powerful built-in inspection tools provided by Flax NNX for deeper code analysis. Explore debugging strategies specifically tailored to JAX's compilation model while drawing connections to familiar PyTorch debugging experiences to ease the transition. Master techniques for effectively troubleshooting neural network code using the Flax NNX API, with practical demonstrations of advanced debugging workflows that go beyond basic error identification. Gain insights into optimizing your debugging process when working with JAX's high-performance computing framework and understand how to navigate the unique challenges posed by compiled code execution in machine learning development.
