[pull] master from deepmodeling:master - #299
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## Summary - resolve one concrete scalable graph backend for each PT-expt training run - reuse the selected backend across eager, compiled, and validation paths - support HybridMuon together with the shared compiler compatibility safeguards and Inductor options - validate graph-builder dispatch and training integration ## Checks Not run per request; the changes were tested separately on another machine. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added configurable `training.neighbor_graph_method` (`auto`, `dense`, `nv`) with consistent runtime selection for graph-eligible energy models. * Expanded training optimizer configuration support (including `Adam`, `AdamW`, and `HybridMuon`). * **Bug Fixes** * Improved NV neighbor-list capacity estimation and neighbor-graph dispatch/selection for eager, compiled, and validation paths. * Updated HybridMuon bias routing for more bias-like parameter names. * **Documentation** * Documented `training.neighbor_graph_method` behavior and resolution timing. * **Tests** * Added method-resolution, CPU-CUDA validation, and NV-vs-dense equivalence coverage (plus compile-support gating for compile tests). <!-- end of auto-generated comment: release notes by coderabbit.ai -->
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