update metrics

autointent/nodes/_optimization/_node_optimizer.py

@@ -35,11 +35,11 @@ def __init__(
         """
         self.node_type = node_type
         self.node_info = NODES_INFO[node_type]
-        self.decision_metric_name = target_metric
+        self.target_metric = target_metric
 
         self.metrics = metrics if metrics is not None else []
-        if self.decision_metric_name not in self.metrics:
-            self.metrics.append(self.decision_metric_name)
+        if self.target_metric not in self.metrics:
+            self.metrics.append(self.target_metric)
 
         self.modules_search_spaces = search_space  # TODO search space validation
         self._logger = logging.getLogger(__name__)  # TODO solve duplicate logging messages problem
@@ -73,7 +73,7 @@ def fit(self, context: Context) -> None:
 
                 self._logger.debug("scoring %s module...", module_name)
                 metrics_score = module.score(context, "validation", self.metrics)
-                metric_value = metrics_score[self.decision_metric_name]
+                metric_value = metrics_score[self.target_metric]
 
                 context.callback_handler.log_metrics(metrics_score)
                 context.callback_handler.end_module()
@@ -91,7 +91,7 @@ def fit(self, context: Context) -> None:
                     module_name,
                     module_kwargs,
                     metric_value,
-                    self.decision_metric_name,
+                    self.target_metric,
                     module.get_assets(),  # retriever name / scores / predictions
                     module_dump_dir,
                     module=module if not context.is_ram_to_clear() else None,

autointent/nodes/schemes.py

@@ -56,7 +56,8 @@ class DecisionNodeValidator(BaseModel):
     """Search space configuration for the Decision node."""
 
     node_type: NodeType = NodeType.decision
-    metric: DecisionMetrics
+    target_metric: DecisionMetrics
+    metrics: list[DecisionMetrics] | None = None
     search_space: list[DecisionSearchSpaceType]
 
 
@@ -70,7 +71,8 @@ class EmbeddingNodeValidator(BaseModel):
     """Search space configuration for the Embedding node."""
 
     node_type: NodeType = NodeType.embedding
-    metric: EmbeddingMetrics
+    target_metric: EmbeddingMetrics
+    metrics: list[EmbeddingMetrics] | None = None
     search_space: list[EmbeddingSearchSpaceType]
 
 
@@ -84,7 +86,8 @@ class ScoringNodeValidator(BaseModel):
     """Search space configuration for the Scoring node."""
 
     node_type: NodeType = NodeType.scoring
-    metric: ScoringMetrics
+    target_metric: ScoringMetrics
+    metrics: list[ScoringMetrics] | None = None
     search_space: list[ScoringSearchSpaceType]
 
 
@@ -98,7 +101,8 @@ class RegexNodeValidator(BaseModel):
     """Search space configuration for the Regexp node."""
 
     node_type: NodeType = NodeType.regexp
-    metric: RegexpMetrics
+    target_metric: RegexpMetrics
+    metrics: list[RegexpMetrics] | None = None
     search_space: list[RegexpSearchSpaceType]
 
 

tests/configs/test_combined_config.py

@@ -13,7 +13,7 @@ def valid_optimizer_config():
     return [
         {
             "node_type": "scoring",
-            "metric": "scoring_roc_auc",
+            "target_metric": "scoring_roc_auc",
             "search_space": [
                 {
                     "module_name": "dnnc",
@@ -28,7 +28,7 @@ def valid_optimizer_config():
         },
         {
             "node_type": "embedding",
-            "metric": "retrieval_hit_rate",
+            "target_target_metric": "retrieval_hit_rate",
             "search_space": [
                 {
                     "module_name": "retrieval",
@@ -62,7 +62,7 @@ def test_invalid_optimizer_config_missing_field():
     invalid_config = [
         {
             "node_type": "scoring",
-            # Missing "metric"
+            # Missing "target_metric"
             "search_space": [
                 {"module_name": "dnnc", "cross_encoder_name": ["cross-encoder/ms-marco-MiniLM-L-6-v2"], "k": [1, 3]}
             ],
@@ -78,7 +78,7 @@ def test_invalid_optimizer_config_wrong_type():
     invalid_config = [
         {
             "node_type": "scoring",
-            "metric": "scoring_roc_auc",
+            "target_metric": "scoring_roc_auc",
             "search_space": [
                 {
                     "module_name": "dnnc",

tests/configs/test_decision.py

@@ -10,7 +10,7 @@ def valid_decision_config():
     return [
         {
             "node_type": "decision",
-            "metric": "decision_roc_auc",
+            "target_metric": "decision_roc_auc",
             "search_space": [
                 {"module_name": "argmax"},
                 {"module_name": "jinoos", "search_space": [[0.3, 0.5, 0.7]]},
@@ -29,7 +29,7 @@ def test_valid_decision_config(valid_decision_config):
     """Test that a valid decision config passes validation."""
     config = OptimizationConfig(valid_decision_config)
     assert config[0].node_type == "decision"
-    assert config[0].metric == "decision_roc_auc"
+    assert config[0].target_metric == "decision_roc_auc"
     assert isinstance(config[0].search_space, list)
     assert config[0].search_space[0].module_name == "argmax"
 
@@ -39,7 +39,7 @@ def test_invalid_decision_config_missing_field():
     invalid_config = [
         {
             "node_type": "decision",
-            # Missing "metric"
+            # Missing "target_metric"
             "search_space": [{"module_name": "tunable", "n_trials": [100]}],
         }
     ]
@@ -53,7 +53,7 @@ def test_invalid_decision_config_wrong_type():
     invalid_config = [
         {
             "node_type": "decision",
-            "metric": "decision_roc_auc",
+            "target_metric": "decision_roc_auc",
             "search_space": [
                 {
                     "module_name": "threshold",

tests/configs/test_embedding.py

@@ -10,7 +10,7 @@ def valid_embedding_config():
     return [
         {
             "node_type": "embedding",
-            "metric": "retrieval_mrr",
+            "target_metric": "retrieval_mrr",
             "search_space": [
                 {"module_name": "logreg_embedding", "embedder_name": ["sergeyzh/rubert-tiny-turbo"], "cv": [3, 5]},
                 {"module_name": "retrieval", "embedder_name": ["sentence-transformers/all-MiniLM-L6-v2"], "k": [5, 10]},
@@ -23,7 +23,7 @@ def test_valid_embedding_config(valid_embedding_config):
     """Test that a valid embedding config passes validation."""
     config = OptimizationConfig(valid_embedding_config)
     assert config[0].node_type == "embedding"
-    assert config[0].metric == "retrieval_mrr"
+    assert config[0].target_metric == "retrieval_mrr"
     assert isinstance(config[0].search_space, list)
     assert config[0].search_space[0].module_name == "logreg_embedding"
     assert "embedder_name" in config[0].search_space[0].model_dump()
@@ -34,7 +34,7 @@ def test_invalid_embedding_config_missing_field():
     invalid_config = [
         {
             "node_type": "embedding",
-            # Missing "metric"
+            # Missing "target_metric"
             "search_space": [
                 {"module_name": "retrieval", "embedder_name": ["sentence-transformers/all-MiniLM-L6-v2"], "k": [5, 10]}
             ],
@@ -50,7 +50,7 @@ def test_invalid_embedding_config_wrong_type():
     invalid_config = [
         {
             "node_type": "embedding",
-            "metric": "retrieval_mrr",
+            "target_metric": "retrieval_mrr",
             "search_space": [
                 {
                     "module_name": "logreg_embedding",

tests/configs/test_regex.py

@@ -7,14 +7,14 @@
 @pytest.fixture
 def valid_regexp_config():
     """Fixture for a valid RegExp node configuration."""
-    return [{"node_type": "regexp", "metric": "regexp_partial_accuracy", "search_space": [{"module_name": "regexp"}]}]
+    return [{"node_type": "regexp", "target_metric": "regexp_partial_accuracy", "search_space": [{"module_name": "regexp"}]}]
 
 
 def test_valid_regexp_config(valid_regexp_config):
     """Test that a valid RegExp config passes validation."""
     config = OptimizationConfig(valid_regexp_config)
     assert config[0].node_type == "regexp"
-    assert config[0].metric == "regexp_partial_accuracy"
+    assert config[0].target_metric == "regexp_partial_accuracy"
     assert isinstance(config[0].search_space, list)
     assert config[0].search_space[0].module_name == "regexp"
 
@@ -23,7 +23,7 @@ def test_invalid_regexp_config_missing_field():
     """Test that a missing required field raises ValidationError."""
     invalid_config = {
         "node_type": "regexp",
-        # Missing "metric"
+        # Missing "target_metric"
         "search_space": [{"module_name": "regexp"}],
     }
 
@@ -35,7 +35,7 @@ def test_invalid_regexp_config_wrong_type():
     """Test that an invalid field type raises ValidationError."""
     invalid_config = {
         "node_type": "regexp",
-        "metric": "regexp_partial_accuracy",
+        "target_metric": "regexp_partial_accuracy",
         "search_space": "should_be_a_list",  # Should be a list of dicts
     }
 

tests/configs/test_scoring.py

@@ -10,7 +10,7 @@ def valid_scoring_config():
     return [
         {
             "node_type": "scoring",
-            "metric": "scoring_roc_auc",
+            "target_metric": "scoring_roc_auc",
             "search_space": [
                 {
                     "module_name": "dnnc",
@@ -61,7 +61,7 @@ def test_valid_scoring_config(valid_scoring_config):
     """Test that a valid scoring config passes validation."""
     config = OptimizationConfig(valid_scoring_config)
     assert config[0].node_type == "scoring"
-    assert config[0].metric == "scoring_roc_auc"
+    assert config[0].target_metric == "scoring_roc_auc"
     assert isinstance(config[0].search_space, list)
     assert config[0].search_space[0].module_name == "dnnc"
 
@@ -70,7 +70,7 @@ def test_invalid_scoring_config_missing_field():
     """Test that a missing required field raises ValidationError."""
     invalid_config = {
         "node_type": "scoring",
-        # Missing "metric"
+        # Missing "target_metric"
         "search_space": [
             {"module_name": "dnnc", "cross_encoder_name": ["cross-encoder/ms-marco-MiniLM-L-6-v2"], "k": [5, 10]}
         ],
@@ -84,7 +84,7 @@ def test_invalid_scoring_config_wrong_type():
     """Test that an invalid field type raises ValidationError."""
     invalid_config = {
         "node_type": "scoring",
-        "metric": "scoring_roc_auc",
+        "target_metric": "scoring_roc_auc",
         "search_space": [
             {
                 "module_name": "knn",