Analyze PyTorch model architecture for Ascend NPU compatibility. Use when examining model structure, CUDA usage, distributed training patterns, and identifying migration requirements.
2
AI 85
dependency-analysis
FeRhodium1/29/2026
Analyze Python package dependencies for Ascend NPU compatibility. Use when examining requirements.txt, setup.py, environment files, and checking for CUDA-dependent packages.
1
AI 95
memory-analysis
FeRhodium1/29/2026
Analyze memory access patterns and optimization opportunities for Ascend NPU. Use when examining data loading, host-device transfers, mixed precision training, and memory efficiency.
1
computation-analysis
FeRhodium1/29/2026
Analyze computation-intensive operators and performance for Ascend NPU. Use when examining model operations, performance bottlenecks, and CANN operator library support.
