test: extend Configure* coverage to 67 tests / 13 buckets + 6 source wiring fixes

CHANGELOG.md

@@ -7,6 +7,89 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased] - 2025-12-18
 
+### Breaking changes (PR #1368)
+
+- **`AiModelBuilder<T,TInput,TOutput>`'s test-only `Configured*` accessors
+  moved behind an explicit-interface implementation.** PR #1368 extracted
+  the 8 `internal Configured*` properties on `AiModelBuilder` into an
+  explicitly-implemented `internal interface IConfiguredView<T,TInput,TOutput>`
+  to keep them off the regular type surface. **Migration for other
+  `InternalsVisibleTo` consumers:** cast the builder to
+  `AiDotNet.Configuration.IConfiguredView<T,TInput,TOutput>` before
+  accessing `ConfiguredOptimizer`, `ConfiguredCaching`,
+  `ConfiguredInferenceOptimizations`, `ConfiguredJitCompilation`,
+  `ConfiguredInterpretability`, `ConfiguredMemoryManagement`,
+  `ConfiguredLicenseKey`, or `ConfiguredAgentAssistance`. Source:
+  `src/Configuration/IConfiguredView.cs`, `src/AiModelBuilder.cs` (review
+  #1368 C8eN_).
+
+- **`AiModelResult.Predict` now throws `InvalidOperationException` with a
+  clear diagnostic when `Model` is null.** Previously a null Model would
+  surface as a `NullReferenceException` deep inside the dispatch path.
+  The new path throws "AiModelResult.Model is null; cannot dispatch
+  Predict." at the call site (review #1368 C8eRj). **Migration:** if any
+  caller was catching `NullReferenceException` to detect "no model
+  configured", switch to catching `InvalidOperationException` or check
+  `result.Model is not null` before calling Predict.
+
+- **`ConfigureRegularization` now throws when paired with a non-gradient optimizer.**
+  Previously, calling `ConfigureRegularization(...)` while the active optimizer
+  was `NormalOptimizer` / an evolutionary search / any custom `IOptimizer`
+  outside the `GradientBasedOptimizerBase` family silently dropped the
+  configured regularization (the gradient-application loop where the slot is
+  consumed never runs on non-gradient optimizers, so the value was stored on
+  the builder and forgotten). PR #1368 surfaces this as a `Build`-time
+  `InvalidOperationException` so the misconfiguration is caught before training
+  starts. **Migration:** either remove the `ConfigureRegularization(...)` call
+  on builds that use a non-gradient optimizer, or switch the optimizer to a
+  `GradientBasedOptimizerBase` subclass (`AdamOptimizer`, `SGDOptimizer`,
+  `AdamWOptimizer`, etc.). Source: `src/AiModelBuilder.cs:2699-2719`.
+
+- **`LoRAAdapterBase.CreateLoRALayer` now throws when neither weight-matrix
+  probing nor the shape API can resolve both `inputSize` and `outputSize`.**
+  Previously the adapter silently produced a wrongly-sized LoRA layer using
+  `outSize * 2` as a heuristic fallback, which later crashed at forward time
+  with an opaque shape mismatch. Now the throw surfaces the unresolvable layer
+  at the LoRA wrap step where the upstream cause is obvious. **Migration:**
+  ensure LoRA-wrapped layers have their shape resolved (run one warmup forward
+  through the model before `ConfigureLoRA(...)` fires, or supply a layer that
+  exposes authoritative `GetInputShape()` values) before the wrap loop fires.
+  Source: `src/LoRA/Adapters/LoRAAdapterBase.cs`.
+
+- **`AiModelResult` constructor throws on unfitted `PostprocessingPipeline`.**
+  Previously the unfitted pipeline rode through to `AiModelResult.Predict` and
+  threw on the first inference call — surfacing the misconfiguration at the
+  wrong layer of the stack. The constructor now fail-fasts at Build time.
+  **Migration:** either fit `PostprocessingPipeline.Fit(...)` before passing
+  the options to the ctor, or set
+  `AiModelResultOptions.PostprocessingFitSample` to a representative
+  training-target sample so the ctor can lazy-fit (review #1368 C6WMS).
+  `AiModelBuilder` build paths already do this — the breaking change only
+  affects callers that construct `AiModelResultOptions` manually.
+
+- **Inference fast paths (`InferenceOptimizationConfig`, `JitCompiledFunction`)
+  now flow through postprocessing and the safety filter.** Previously these
+  branches returned the raw model output early, bypassing the
+  `denormalize → PostprocessingPipeline.Transform → SafetyFilter` tail. Now
+  `DispatchModelInference` returns into a single shared tail that all three
+  paths (optimized, JIT, standard) traverse. **Migration:** if downstream
+  consumers relied on the fast paths skipping postprocessing for performance,
+  add `.ConfigurePostprocessing(null)` / leave the pipeline unconfigured —
+  the shared tail short-circuits when no postprocessing is wired. Source:
+  `src/Models/Results/AiModelResult.cs:DispatchModelInference` (review #1368
+  C7HAa).
+
+- **`ConfigureKnowledgeDistillation` on the regular-training (non-LoRA, non-
+  direct-training) NN path now throws `NotSupportedException` at Build time.**
+  Previously the second throw site was on this path; the option was stored but
+  never reached the tape-based training flow. The throw is preserved (not
+  downgraded to a Trace-warning) so users discover the missing KD-tape
+  integration at Build time rather than getting standard supervised training
+  silently substituted for the requested distillation. **Migration:** either
+  configure LoRA / a direct-training path (where the options ARE attached to
+  the result without going through the regular tape loop), or wait for the
+  upstream KD-tape integration to land. Source: `src/AiModelBuilder.cs:3636`.
+
 ### Added
 - **iMAML (implicit Model-Agnostic Meta-Learning) Algorithm**
   - True implicit differentiation implementation with constant memory complexity