layer: ResNet-style skip connections for 1D and 2D CNNs

## Feature

ResNet-style residual blocks for 1D and 2D CNNs: identity shortcut around conv→norm→act→conv→norm with an elementwise-add merge, plus the projection shortcut (kernel-size-1 conv) for blocks that change channel count or stride.

## Blockers

- **#329 (topology epic)** — branch/merge forward+backward is the hard prerequisite: Add-merge node, gradient accumulation at the fork.
- 2D variant additionally blocked by **#330** (2D layer family). The 1D variant has no other missing kernels.

## Notes

- The 1D variant should ship first: the Conv1d family and Add arithmetic exist, so a residual block is the *minimal* consumer of #329's Add-merge — a good acceptance vehicle for the epic itself.
- Projection shortcut = Conv1d/Conv2d with kernel size 1 — no new kernel needed.
- SYM configs: the merge-add of two differently-scaled SYM wires depends on #329's quantized-merge semantics; keep the first residual example FLOAT32 until that spec lands.

## Acceptance

A small residual CNN example (HAR or ECG variant) with a PyTorch twin; trajectory comparison over ≥10 seeds per repo rule.

Start with blocker #329 to understand the Add-merge node and gradient accumulation, then inspect the existing Conv1d family and Add arithmetic. The 1D residual example should be implemented first; done means a small HAR or ECG CNN has a PyTorch twin and trajectory comparisons across at least 10 seeds, using FLOAT32 for the initial merge.

Written by the indexing model from the issue text.