v1.1.0

Changes

• Tensoracle now supports recording one EngineExecution.enqueue call with CUDA stream capture and replaying the resulting graph. The README and the documentation describe the requirements: enqueue once and wait after setting input shapes, capture and replay on a nondefault stream, and use a dedicated execution unit for each graph. They also state that a graph fixes the input shapes, tensor addresses, and execution unit, and which engines cannot be captured. The application owns graph creation, recapture, and destruction; tensoracle adds no capture or replay operations.
• GPU tests verify that replayed graphs match ordinary enqueue output for an engine with standard layers, an engine with a cubin TensorRT plugin, and a ranged-input engine that keeps one execution unit and graph per shape.

Upgrade note

The code, public API, saved engine file format, cache identity, and dependencies are unchanged from 1.0.1. Engines saved by 1.0.1 are reused without a rebuild. Applications that capture enqueue into CUDA graphs can require tensoracle>=1.1.0 to depend on this guarantee.

Install

pip install tensoracle==1.1.0