Add optional graph-modification report to optimize()

[take-cheeze]

The optimization passes already compute how many positive transforms each pass applies to the graph (CountBasedPassAnalysis), but every layer discarded this information, so optimize() only returned the optimized model.

This threads a per-pass modification report through the whole stack:

• PassManagerAnalysis now carries a transform_counts map (pass name -> total positive transforms); both GeneralPassManager::run and FixedPointPassManager::run populate it instead of returning an empty analysis.
• Optimizer::optimize / Optimize / OptimizeFixed accept an optional report out-parameter (defaults to nullptr, fully backward compatible).
• New nanobind bindings optimize_report / optimize_fixedpoint_report and the path-based optimize_from_path_report / optimize_fixedpoint_from_path_report return the report alongside the model.
• Python optimize() gains a return_report keyword. When True it returns a (model, report) tuple where report is a dict mapping pass name to the number of graph modifications; the default return type is unchanged.

Add tests covering the tuple return, the counted transform, and the zero-count (pass ran but matched nothing) case.

Claude-Session: https://claude.ai/code/session_01TSYXLexqD5r4Lkg3KfeGZj