optimizing-attention-flash
Pass
Audited by Gen Agent Trust Hub on Oct 8, 2026
Risk Level: SAFECOMMAND_EXECUTIONEXTERNAL_DOWNLOADS
Full Analysis
- [COMMAND_EXECUTION]: The documentation contains standard shell commands for environment setup and verification, such as checking PyTorch versions (
python -c "import torch; print(torch.__version__)") and verifying GPU hardware (nvidia-smi). - [EXTERNAL_DOWNLOADS]: The skill provides instructions for installing well-known machine learning libraries from standard package registries using
pip install flash-attnandpip install --upgrade torch. These are standard installation procedures for the described optimization tasks. - [SAFE]: All code snippets are routine implementations of Flash Attention using established APIs (PyTorch's
scaled_dot_product_attentionand theflash_attnlibrary). The benchmarks and integration guides align with the stated purpose of optimizing transformer performance. No malicious patterns, obfuscation, or unauthorized data access attempts were detected.
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