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Use subclass as the default model parameter tracker - #155
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Make
subclassthe default tracker for newly collected model traces. It keeps models as native PyTorch modules and tracks their parameters;proxyremains explicitly selectable through CLI and YAML. This is a default/coverage change, not a performance claim.Help and examples explain the parameter-focused coverage and migration rule: retain explicit proxy mode for existing proxy-derived invariants, or recollect/reinfer and verify actual activation. Saved instrumentation options remain explicit and unchanged. Selective immediate-variable rules use the selected tracker; consistency-only rules retain the sampler policy.
Merge #154 first. Both PRs target
maindirectly. #157 separately fixes the broader--use-full-instrstartup recursion.Validation:
035f7f1976c5d84bd01f5d96bb095fb07c9cc059passes real two-step Transformer CLI runs: ordinary default (956 API +72 VAR), selective default (4 API +48 VAR), and full default (1,628 API +72 VAR). All 12 parameter paths appear, with complete call pairs and no duplicate raw records.test_inject_eval_loopfails identically on unchanged main9ba90ac. Pinned hooks and configured mypy across all 78 production files pass. Strict new-code/tests checking with installed Torch types passes; stronger legacy CLI checking retains its same ten errors, with none introduced.All commits are signed. Exact commands, source hashes, raw traces and coverage reports are retained at
/Users/matt/gitrepos/traincheck/outputs/instrumenter-final-cli-20261027/validation.json; composed checker evidence is inoutputs/instrumenter-final-validation-20261027. Ordinary, selective and full CLI times are single whole-process completion checks, not overhead estimates.