Roadmap and Task List

Development progress summarized from repo/Hahaha/doc/zh-cn/Task.md:

Completed (v0.0.1)

• Tensor core: dimension management, memory ownership, nested initialization, broadcasting adaptation.
• Linear algebra basics: matrix multiplication (matmul), transpose (transpose), sum (sum).
• Autograd engine: dynamic graph nodes, topological sorting, backpropagation.
• Optimizer basics: SGD (stochastic gradient descent).
• Visualization: real-time training curve rendering via ImGui.
• Infrastructure: logging system, Docker dev env, Meson build flow.

In progress (v0.1.0 target)

• Better broadcasting: support more complex cross-dimension tensor operations.
• Dataset implementation: create dataset abstraction and finish dataset loading.
• Modern ML models: linear regression, KNN template implementation.
• Logging enhancements: integrate std::stacktrace for crash-site tracing.

Future (backlog)

• Backend acceleration: CUDA VRAM management and core kernels.
• Neural network layers: fully-connected, convolution, batch normalization.
• Advanced math: SVD, matrix inverse, eigenvalue computations.
• Python bindings: provide Python API via Pybind11.