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Observability and Control for TensorRT Engine Builds

Observability and Control for TensorRT Engine Builds

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2026

This feature thread tracks the evolution of making NVIDIA TensorRT engine builds more observable and controllable. Initially, long-running builds lacked visibility, leading to wasted GPU hours and user frustration. Recent advancements, exemplified by the introduction of `IProgressMonitor` in TensorRT, provide fine-grained, thread-safe progress tracking and cancellation capabilities. This allows developers to integrate real-time progress reporting into terminals, IDEs, services, and agent runtimes, and enables cancellation of builds via Python or C++ implementations.

2026

Make Long-Running NVIDIA TensorRT Engine Builds Observable and Cancelable in Python or C++ | NVIDIA Technical Blog

7/22/2026

Introduces a detailed guide on implementing and utilizing the `IProgressMonitor` API in TensorRT for both Python and C++. This includes subclassing `IProgressMonitor` to override `phase_start`, `step_complete`, and `phase_finish` methods, managing nested phase states, ensuring thread safety with locks, and rendering progress bars using virtual-terminal escapes. It also demonstrates how to integrate cancellation logic into `step_complete` and provides code examples for Python and C++.