Tutorials

These tutorials are ordered, runnable introductions to the main tenferro workflows. They complement the guides: tutorials show one complete path, while guides describe the broader APIs and tradeoffs.

All non-trivial code in this section is sourced from docs/tutorial-code and is run by the workspace test workflow.

Suggested Order

Tutorial	Use it when
TypedTensor for numeric computation without autodiff	You know the scalar type in Rust and want ndarray-like CPU tensor computation without AD.
Eager autodiff, PyTorch style	You want immediate execution, scalar losses, backward(), and accumulated gradients.
Traced autodiff, JAX style	You want to build a graph, compile/run it, and use grad or jvp on the traced graph.
Einsum: subscripts to gradients	You contract more than two tensors and want planned contraction order plus AD.
XLA backend: einsum to StableHLO	You want to lower a fixed-shape N-ary einsum path through the experimental XLA executor.
Dynamic shapes: truncated SVD	Output ranks depend on runtime values such as singular-value thresholds.

Running The Tutorial Code

From the repository root:

cargo test -p tenferro-tutorial-code --release

The CI workflow runs this package through the existing workspace test command, so tutorial execution does not add a second tenferro compilation step after unit tests.