- Add tinytorch.utils.profiler following PyTorch's utils pattern
- Includes SimpleProfiler class for educational performance measurement
- Provides timing, memory usage, and system metrics
- Follows PyTorch's torch.utils.* organizational pattern
- Module 11: Kernels uses profiler for performance demonstrations
Features:
- Wall time and CPU time measurement
- Memory usage tracking (peak, delta, percentages)
- Array information (shape, size, dtype)
- CPU and system metrics
- Clean educational interface for ML performance learning
Import pattern:
from tinytorch.utils.profiler import SimpleProfiler
- Move testing utilities from tinytorch/utils/testing.py to tito/tools/testing.py
- Update all module imports to use tito.tools.testing
- Remove testing utilities from core TinyTorch package
- Testing utilities are development tools, not part of the ML library
- Maintains clean separation between library code and development toolchain
- All tests continue to work correctly with improved architecture
