refactor(mypy): un-ignore callbacks/health_logging#295
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Fix each module's single pre-existing type error with a pure annotation or setattr change (no behavior change) and remove it from the [[tool.mypy.overrides]] ignore_errors list: - callbacks/train_logging: loss_trackers: dict[str, MeanMetric] - callbacks/metrics_logging: seen_examples: set[str] - common: setattr(wrapper, "_has_run", True) for the @wraps wrapper - hydra/resolvers: attribute_path: str | None (body already guards) - inference_engines/base: base_overrides: dict[str, Any] 13 modules remain on the ignore list. mypy now type-checks the 5 newly-included modules cleanly. Co-authored-by: Sergey Lyskov <sergey.lyskov@jhu.edu>
Resolve the type errors in and remove from the [[tool.mypy.overrides]] ignore_errors list. Mostly narrowing / annotation fixes; two deliberate type-honesty fixes flagged below. - utils/weights: lowercase `any` -> `Any` in _PatternPolicyMixin (4x); assert-narrow fallback_policy at the call site (matches get_policy idiom) - model/layers/blocks: class-level w/b: torch.Tensor for the registered buffers (avoids nn.Module's Tensor | Module __getattr__ fallback) - utils/components: is-None narrowing + tip_names local in get_name_mask's TIP branch (exists() can't narrow for mypy); drop orphaned exists import - utils/logging: str(field) for the tree key; assign to a new hparams local rather than reassigning the typed cfg param - foundry_cli/download_checkpoints: guard on `hasher is not None`; total_size = 0.0 for the float accumulation - training/schedulers: SchedulerConfig.scheduler is now a required field (was = None, but documented required and assumed non-None everywhere) - utils/xpu/xpu_accelerator: name @Property -> @staticmethod to match lightning's Accelerator ABC 6 hard-tier modules remain on the ignore list. Co-authored-by: Sergey Lyskov <sergey.lyskov@jhu.edu>
Fix the 11 type errors in foundry.metrics.metric and remove it from the [tool.mypy.overrides] ignore_errors list (5 hard-tier modules remain). - str(name) coercion of DictConfig.items() keys (str|bytes|int|... union) - exists() -> 'is not None' narrowing; drop orphaned atomworks import - widen compute_from_kwargs -> dict|list and kwargs_to_compute_args -> dict|None to match the actual returns / documented contract (callers already handle them) - three type: ignore[arg-type] on nested_dict.get/getitem for an upstream atomworks annotation bug (param typed dict[tuple,...] but navigated as nested dict[str,Any]); warn_unused_ignores will flag them if upstream is fixed No behavior change. All gates green (ruff, mypy 41 files, pytest 27 passed). Co-authored-by: Sergey Lyskov <sergey.lyskov@jhu.edu>
Clear the three remaining foundry.utils.* modules off the mypy ignore_errors list (47 errors: ddp 12, rigid 16, datasets 19). Type-honesty and annotation fixes only, no behavior change: narrow DictConfig|dict params to DictConfig where attribute access requires it (item access kept where a plain-dict default is real), honest int|None / Tensor|None widenings, variable renames to avoid type-reuse, str() coercion of DictConfig keys, the file's own if/elif/else narrowing pattern, and documented type: ignore / cast for genuine torch and atomworks stub limitations. Two hard-tier modules remain (callbacks/health_logging, trainers/fabric). Co-authored-by: lyskov-ai <277346777+lyskov-ai@users.noreply.github.com>
Clear foundry.callbacks.health_logging off the mypy ignore_errors list by fixing its 23 type errors (annotation / type-honesty only, no behavior change): - import the stdlib 'types' module directly instead of relying on 'from typing import types' (worked at runtime but fragile/untyped) - replace 'callable'-used-as-a-type with Mapping[str, Callable[..., Any]] on the stat/histogram dict params and Callable[..., bool] | None on the filter params; annotate the two MappingProxyType default constants to match - annotate the _hooks / _temp_cache / _cache instance vars - make implicit-Optional defaults explicit (... | None) on the two plot_tensor_* helpers, matching their is-not-None guards - in plot_tensor_hist, replace two type-changing param reassignments with equivalent always-set locals (display_values, step_labels) Only trainers/fabric remains on the ignore list. Co-authored-by: lyskov-ai <277346777+lyskov-ai@users.noreply.github.com>
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Type-checking: fix the type errors in
foundry.callbacks.health_loggingand remove it from theignore_errorslist (2 → 1 remaining), so mypy now type-checks the module. No behavior change.Annotation / type-honesty only:
callable-used-as-a-type →Mapping[str, Callable[..., Any]]on the stat/histogram params (and the twoMappingProxyTypeconstants),Callable[..., bool] | Noneon the filter params, three instance-var annotations, explicit… | Noneon the two plot helpers, and twoif-reassignment → ternary rewrites to avoid retypingTensorparams.Per-module details are in the commit message.