feat(config)!: registry-key adapter resolution, drop unsafe _target_ (#301)

.github/workflows/code-quality.yaml

@@ -116,6 +116,11 @@ jobs:
       - name: Pyright
         run: uv run pyright
 
+      - name: Config schema freshness
+        run: |
+          uv run raitap config-schema -o /tmp/raitap.schema.json
+          git diff --exit-code --no-index -- src/raitap/schema/raitap.schema.json /tmp/raitap.schema.json
+
       - name: Pytest on 3.13 (with coverage)
         run: uv run pytest -m "not e2e and not cuda" -v --cov=src/raitap --cov-report=term-missing --cov-report=html
 

.gitignore

@@ -100,3 +100,6 @@ contributor-configs/*/images/
 /metrics/
 /reports/
 /transparency/
+
+# Generated at docs build by docs/_ext/raitap_adapters.py (issue #301)
+docs/modules/_generated_adapters.md

contributor-configs/fasterrcnn-udacity/assessment.yaml

@@ -40,15 +40,15 @@ data:
     source: ${hydra:runtime.cwd}/contributor-configs/fasterrcnn-udacity/labels/udacity-boxes.json
 
 metrics:
-  _target_: DetectionMetrics
+  use: detection
 
 transparency:
   # One per-box Integrated Gradients run. ``call.target`` must be 0 — the
   # ScalarDetectionWrapper exposes a single scalar channel, so ``auto_pred``
   # is rejected (see docs/modules/transparency/configuration.md "Detection
   # knobs"). ``max_boxes: 3`` keeps the K-loop small enough for CPU CI.
   detection_ig:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: IntegratedGradients
     call:
       target: 0
@@ -65,10 +65,10 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: DetectionImageVisualiser
+      - use: detection_image
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: fasterrcnn_udacity_report
   # Force all 4 samples into the local-detail section (default cap is 3).
   sample_selection: [0, 1, 2, 3]

contributor-configs/imagecorruptions-imagenet/assessment.yaml

@@ -36,20 +36,20 @@ metrics:
 robustness:
   # Average-case: ImageNet-C common corruption at a fixed severity.
   gaussian_noise:
-    _target_: ImageCorruptionsAssessor
+    use: imagecorruptions
     algorithm: gaussian_noise   # any of the 15 ImageNet-C corruptions
     constructor:
       severity: 3               # 1..5
     visualisers:
-      - _target_: CorruptionAccuracyVisualiser
+      - use: corruption_accuracy
   # Worst-case: bounded PGD adversarial attack (torchattacks).
   pgd:
-    _target_: TorchattacksAssessor
+    use: torchattacks
     algorithm: PGD
     constructor:
       eps: 0.03
       alpha: 0.008
       steps: 10
     visualisers:
-      - _target_: ImagePairVisualiser
-      - _target_: PerturbationHeatmapVisualiser
+      - use: image_pair
+      - use: perturbation_heatmap

contributor-configs/lwise-ham10000/assessment.yaml

@@ -30,12 +30,12 @@ data:
     column: label
 
 metrics:
-  _target_: MulticlassClassificationMetrics
+  use: multiclass_classification
   num_classes: 7
 
 transparency:
   gradcam_localisation:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: LayerGradCam
     constructor:
       layer_path: 1.layer4.2.conv3
@@ -49,7 +49,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: heat_map
           sign: positive
@@ -60,7 +60,7 @@ transparency:
           max_samples: 4
 
   saliency_evidence:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: Saliency
     call:
       target: auto_pred
@@ -72,7 +72,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: blended_heat_map
           sign: positive
@@ -81,7 +81,7 @@ transparency:
           title: "Positive lesion evidence"
         call:
           max_samples: 4
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: masked_image
           sign: positive
@@ -92,7 +92,7 @@ transparency:
           max_samples: 4
 
   occlusion_check:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: Occlusion
     call:
       target: auto_pred
@@ -106,7 +106,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: heat_map
           sign: absolute_value
@@ -117,7 +117,7 @@ transparency:
           max_samples: 4
 
   integrated_evidence_detail:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: IntegratedGradients
     call:
       target: auto_pred
@@ -130,7 +130,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: blended_heat_map
           sign: absolute_value
@@ -142,7 +142,7 @@ transparency:
 
 robustness:
   fgsm_linf_fast:
-    _target_: TorchattacksAssessor
+    use: torchattacks
     algorithm: FGSM
     constructor:
       eps: 0.03
@@ -153,15 +153,15 @@ robustness:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: ImagePairVisualiser
+      - use: image_pair
         constructor:
           max_samples: 4
-      - _target_: PerturbationHeatmapVisualiser
+      - use: perturbation_heatmap
         constructor:
           max_samples: 4
 
   pgd_linf_small:
-    _target_: TorchattacksAssessor
+    use: torchattacks
     algorithm: PGD
     constructor:
       eps: 0.03
@@ -174,25 +174,25 @@ robustness:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: ImagePairVisualiser
+      - use: image_pair
         constructor:
           max_samples: 4
-      - _target_: PerturbationHeatmapVisualiser
+      - use: perturbation_heatmap
         constructor:
           max_samples: 4
   marabou_linf:
-    _target_: MarabouAssessor
+    use: marabou
     algorithm: linf-box
     constructor:
       epsilon: 0.05
       norm: Linf
       timeout_s: 300
     visualisers:
-      - _target_: VerdictSummaryVisualiser
+      - use: verdict_summary
 
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: lwise_ham10000_report.pdf
   include_config: true
   include_metadata: true

contributor-configs/lwise-ham10000/assessment_mlflow.yaml

@@ -3,7 +3,7 @@ defaults:
   - _self_
 
 tracking:
-  _target_: MLFlowTracker
+  use: mlflow
   output_forwarding_url: http://127.0.0.1:5001
   backend_store_uri: sqlite:///mlflow/mlflow.db
   default_artifact_root: ./mlflow/artifacts

contributor-configs/marabou-mnist/assessment.yaml

@@ -39,11 +39,11 @@ model:
 
 robustness:
   marabou_linf:
-    _target_: MarabouAssessor
+    use: marabou
     algorithm: linf-box
     constructor:
       epsilon: 0.05
       norm: Linf
       timeout_s: 300
     visualisers:
-      - _target_: VerdictSummaryVisualiser
+      - use: verdict_summary

contributor-configs/noisetunnel-smoothgrad/assessment.yaml

@@ -33,7 +33,7 @@ metrics:
 
 transparency:
   smoothgrad_over_saliency:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: NoiseTunnel
     constructor:
       base_algorithm: Saliency
@@ -49,7 +49,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: blended_heat_map
           sign: absolute_value
@@ -60,7 +60,7 @@ transparency:
           max_samples: 4
 
   saliency_baseline:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: Saliency
     call:
       target: auto_pred
@@ -72,7 +72,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: blended_heat_map
           sign: absolute_value
@@ -83,7 +83,7 @@ transparency:
           max_samples: 4
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: noisetunnel_smoothgrad_report
   include_config: true
   include_metadata: true

contributor-configs/quantus-eval/assessment.yaml

@@ -49,7 +49,7 @@ metrics:
 
 transparency:
   integrated_gradients:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: IntegratedGradients
     call:
       target: auto_pred
@@ -60,7 +60,7 @@ transparency:
         layout: NCHW
       show_sample_names: true
     visualisers:
-      - _target_: CaptumImageVisualiser
+      - use: captum_image
         constructor:
           method: blended_heat_map
           sign: absolute_value
@@ -69,13 +69,13 @@ transparency:
         call:
           max_samples: 4
     evaluation:
-      _target_: raitap.transparency.QuantusEvaluator
+      use: quantus
       metrics: [faithfulness_correlation, sparseness]
       constructor:
         faithfulness_correlation: {nr_runs: 10, subset_size: 32}
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: quantus_eval_report
   include_config: true
   include_metadata: true

contributor-configs/text-classification-sst2/assessment.yaml

@@ -47,7 +47,7 @@ metrics:
 
 transparency:
   token_ig:
-    _target_: CaptumExplainer
+    use: captum
     algorithm: LayerIntegratedGradients
     constructor:
       # LayerIntegratedGradients attributes wrt. the embedding layer output.
@@ -61,10 +61,10 @@ transparency:
         kind: text
         layout: TOKENS
     visualisers:
-      - _target_: CaptumTextVisualiser
+      - use: captum_text
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: text_classification_sst2_report
   include_config: true
   include_metadata: true

contributor-configs/tree-xgboost-shap/assessment.yaml

@@ -28,7 +28,7 @@ data:
 
 transparency:
   treeshap:
-    _target_: ShapExplainer
+    use: shap
     algorithm: TreeExplainer
     call:
       # Binary XGBoost SHAP returns stacked (B, F, 2); pick the positive class.
@@ -39,12 +39,12 @@ transparency:
         layout: "(B,F)"
       show_sample_names: true
     visualisers:
-      - _target_: ShapBarVisualiser
+      - use: shap_bar
         constructor:
           feature_names: [f0, f1, f2, f3, f4, f5]
 
 reporting:
-  _target_: HTMLReporter
+  use: html
   filename: tree_xgboost_shap_report
   include_config: true
   include_metadata: true