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Guides#

Practical guidance for using Attention Gym and PyTorch attention features in real workloads.

  • Ragged CUDA Graphs — capture and replay variable-length attention workloads efficiently, from device-driven scheduling to graph capacity planning.
  • Deterministic FlexAttention — understand sources of nondeterminism and configure deterministic forward and backward execution.